SETPOINT ADJUSTMENT FOR ENERGY OPTIMIZATION

Abstract

Examples techniques for optimizing energy usage in a premises are described. At an optimizer, data corresponding to a setpoint specified for each of a plurality of zones of premises is received. Each specified setpoint is a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones. The specified setpoint of each zone is compared to a predefined value associated with a predetermined level of energy efficiency for an air handling unit (AHU) coupled to the VAV units. A rogue zone is identified from the plurality of zones. The rogue zone has a specified setpoint that exceeds the predefined value by a predetermined threshold. Further, data corresponding to current physical condition of the rogue zone is received. The specified setpoint of the rogue zone is adjusted to reduce a difference between the specified setpoint and the predefined value.

Description

BACKGROUND

Sustainable building operations have become increasingly important in recent years as organizations and individuals seek to reduce their environmental impact and improve energy efficiency. Sustainable building operations may refer to practices and strategies that minimize resource consumption, reduce waste, and enhance the overall performance of assets that regulate physical conditions in premises throughout their lifecycle. Such approaches may be helpful in addressing global challenges such as climate change, resource depletion, and rising energy costs. The concept of the sustainable building operations may encompass various aspects, including but not limited to, energy management, water conservation, waste reduction, indoor environmental quality, and occupant comfort. By focusing on these areas, premises owners and operators may significantly reduce their carbon footprint, lower operational costs, and create healthier, more productive spaces for occupants.

One of the key components of the sustainable building operations is the optimization of operations of the assets installed in a premises, for example, to save energy. The optimization of the operations of the assets installed in the premises may play a crucial role in achieving sustainable operations and energy savings. By fine-tuning the performance of the assets, operators may significantly reduce energy consumption, extend the lifespan of the assets, and improve overall performance of the assets. The process of optimization may involve the use of advanced technologies, such as building management systems, sensors, and data analytics, to monitor and control various operating parameters of the assets for optimal energy efficiency.

Effective optimization strategies for energy savings may include demand-based control, predictive maintenance, and adaptive scheduling of premises systems. These approaches may allow for more precise management of energy use, better alignment with occupancy patterns, and proactive identification of issues before they lead to asset failures or energy waste. For example, heating, cooling, and lighting systems may be automatically adjusted based on real-time occupancy, weather conditions, and time of day to minimize unnecessary energy consumption. Furthermore, the integration of energy management systems and advanced control algorithms may further enhance the energy efficiency of premises operations.

As the built environment continues to evolve, the importance of sustainable building operations and asset optimization for energy savings becomes increasingly apparent. These practices not only contribute to environmental conservation through reduced energy consumption and greenhouse gas emissions but also offer significant economic benefits through lower utility costs and improved asset longevity. Moreover, they may enhance occupant comfort and well-being by maintaining optimal indoor environmental conditions, leading to increased productivity and satisfaction in both residential and commercial settings.

SUMMARY

The details of some embodiments of the invention described in this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the invention will become apparent from the description, the drawings, and the claims.

The present invention relates to methods, systems, and non-transitory computer-readable media for optimizing energy usage in a premises.

According to an aspect of the present invention, a method for optimizing the energy usage in the premises includes determining a setpoint specified for each of a plurality of zones in the premises. The setpoint is a target value for an operating parameter of a variable air volume (VAV) unit that is configured to regulate physical conditions in the respective zones. The specified setpoint for each of the plurality of zones is based on requirements for physical conditions according to user demand in the respective zones. The method further includes comparing the specified setpoint of each of the plurality of zones to a predefined value computed based on a predetermined level of energy efficiency expected during operation of an air handling unit (AHU) coupled to the VAV unit of each of the plurality of zones. Furthermore, the method includes identifying at least one rogue zone from the plurality of zones. In the at least one rogue zone, the specified setpoint exceeds the predefined value by a predetermined threshold. The method further includes determining current physical conditions of the at least one rogue zone. Furthermore, the method includes regulating, based on the current physical conditions, the specified setpoint of the at least one rogue zone such that the specified setpoint is adjusted towards the predefined value.

In accordance with an embodiment of the present invention, the system for optimizing energy usage in a premises includes a processor to receive data corresponding to a setpoint specified for each of a plurality of zones in the premises. Each specified setpoint is a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones. The processor further compares the specified setpoint of each of the plurality of zones to a predefined value associated with a predetermined level of energy efficiency for an air handling unit (AHU) coupled to the VAV units. Furthermore, the processor identifies at least one rogue zone from the plurality of zones. The at least one rogue zone has a specified setpoint that exceeds the predefined value by a predetermined threshold. The processor further receives data corresponding to current physical condition of the at least one rogue zone. Furthermore, the processor adjusts the specified setpoint of the at least one rogue zone to reduce a difference between the specified setpoint and the predefined value while maintaining the current physical conditions within a predetermined range of acceptable physical conditions.

In accordance with an embodiment of the present invention, the non-transitory computer-readable medium contains instructions that enable a processing resource to determine a setpoint specified for each of a plurality of zones in a premises. The specified setpoint is a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones. The specified setpoint for each of the plurality of zones is based on requirements for physical conditions according to user demand in the respective zones. The processing resource is to compare the specified setpoint of each of the plurality of zones to a predefined value computed based on a predetermined level of energy efficiency in operation of an air handling unit (AHU) coupled to the VAV unit of each of the plurality of zones. Furthermore, the processing resource is to identify at least one rogue zone from the plurality of zones. In the at least one rogue zone, the specified setpoint exceeds the predefined value by a predetermined threshold. Further, the processing resource is to determine current physical conditions of the at least one rogue zone. Furthermore, the processing resource calculates a new setpoint for the at least one rogue zone based in the current physical conditions. The new setpoint has a value between the specified setpoint and the predefined value. The processing resource is regulate the VAV unit of the at least one rogue zone according to the new setpoint.

Embodiments of the present subject matter optimize energy usage in a premises by dynamically adjusting setpoints in identified rogue zones. By targeting zones where setpoints exceed predefined energy efficiency thresholds, the present subject matter allows for reducing energy consumption through air handling units (AHUs). This enables more efficient operation of a heating, ventilation, and air conditioning (HVAC) system, leading to substantial energy savings and reduced operational costs, while still maintaining effective ambient condition throughout the premises.

Furthermore, the present subject matter enables implementing approaches to setpoint adjustment that prioritize maintaining required conditions in each zone. While pursuing energy efficiency, the present subject allows for ensuring that any changes to the setpoints in the rogue zones maintain current physical conditions within a predetermined range of acceptable parameters. This allows for optimization of energy usage without compromising the specific requirements of the corresponding rogue zones, whether these requirements are for occupant comfort or for specialized environments such as laboratories. By considering both energy efficiency and the unique needs of each zone, the present subject matter provides a solution that enhances overall performance of the premises while meeting diverse spatial requirements, from personal comfort to required environmental control for sensitive operations.

Additional features and advantages are realized through the concepts of the present invention. Other embodiments and aspects of the invention are described in detail herein and are considered a part of the claimed invention.

BRIEF DESCRIPTION OF FIGURES

The following detailed description references the drawings, wherein:

FIG. 1 illustrates a network environment for implementing example techniques for optimizing energy usage in a premises, in accordance with an example implementation of the present invention;

FIG. 2 illustrates a system for optimizing energy usage in a premises, in accordance with an example implementation of the present invention;

FIG. 3 illustrates the system for optimizing the energy usage in the premises, in accordance with another example implementation of the present subject matter;

FIG. 4 illustrates an exemplary interface for identifying a rogue zone from amongst a plurality of zones in a premises, in accordance with an example implementation of the present invention.

FIG. 5 illustrates a signal flow in a process to manage optimization of energy usage in the premises, in accordance with an example implementation of the present subject matter.

FIG. 6 illustrates a method for optimizing energy usage in a premises, in accordance with an example implementation of the present invention.

FIG. 7 illustrates a flow diagram of a process for adjusting setpoint of operating parameters for a rogue zone, according to an example implementation of the present subject matter.

FIG. 8 illustrates a flow diagram of a process of regulating variable air volume (VAV) unit in a rogue zone, according to an example implementation of the present subject matter;

FIG. 9 illustrates a computing environment for optimizing energy usage in a premises, according to an example implementation of the present invention.

In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components.

DETAILED DESCRIPTION

Building management systems (BMSs) are implemented to monitor and control assets installed in a premises, such as residential buildings, commercial complexes, industrial facilities, healthcare installations, educational campuses, and/or data centers, to create desired physical conditions in the premises. A physical condition of the premises may correspond to indoor ambient condition of the premises, and may be created in accordance with the purpose that the premises is designed to serve. For example, a laboratory may be designed to maintain specific temperature and humidity levels to support experiments and equipment functionality. An office space may require a comfortable environment with consistent temperature and air quality to enhance productivity. A data center may need ongoing cooling and airflow management to support equipment operation. A hospital operating room may call for enhanced air filtration and pressure control to promote a clean environment. As premises are designed for a wide variety of purposes, the required physical conditions vary significantly to cater to such diverse needs.

A BMS may include a control system that is configured to monitor and regulate the physical conditions of the premises. The control system may include various assets, such as heating, ventilation, and air conditioning (HVAC) systems, that may be operated to achieve the desired physical conditions within the premises. An HVAC system may include components like chillers, air handling units (AHUs), and variable air volume (VAV) units. These components of the HVAC system work together to regulate variables, such as temperature, humidity, and air flow within the premises in such a manner that the physical conditions desired in the premises are achieved. This may help ensure occupant comfort and/or meet predefined indoor ambient condition for the premises.

To operate the components of the HVAC system in accordance with the desired physical conditions, setpoints may be defined for operating parameters of AHUs of the HVAC system. Herein, a “setpoint” may be a predefined value for an operating parameter of an AHU to achieve the desired physical conditions within the premises. Referring to the previous example of the laboratory, a temperature setpoint for the laboratory may be predefined as 22° C. that may correspond to a desired physical condition for the laboratory. To meet this temperature setpoint in order to achieve/maintain the desired physical condition in the laboratory, the AHU may be configured to operate valves of the AHU in such a manner that the predefined temperature setpoint is achieved in the laboratory. For example, if the actual temperature in the laboratory is higher than the predefined temperature setpoint, the AHU may open the valve controlling the flow of chilled water through cooling coils of the AHU to increase cooling in the laboratory. Conversely, if the temperature is lower than the predefined temperature setpoint, the AHU may open the valve controlling the flow of hot water through heating coils of the AHU to increase heating. The AHU may continuously monitor the temperature inside the laboratory and adjusts valves of the AHU as necessary to maintain the temperature at or near the setpoint.

In some examples, one AHU may be configured to serve a plurality of zones within the premises. Herein, a ‘zone’ may correspond to a physical space within the premises that has its own physical conditions requirements. The zone may be an individual room, a section of an open office area, a specific functional area such as a laboratory or conference room, a floor, or any other defined area within the premises. Each zone may have a requirement of physical conditions different than other areas or zones within the premises that may be based on factors such as occupancy, equipment heat load, or specific activities conducted within the zone. Based on the desired physical conditions for each of the zones, setpoints for the operating parameters of the AHU serving the corresponding zones may be defined. A variable air volume (VAV) unit may be implemented for each of these zones that may accommodate different requirements of the physical conditions of the corresponding zones, for example, by interacting with the AHU.

The VAV units may regulate the volume of conditioned air supplied by the AHU to each zone, allowing for individualized control of temperature and airflow. These VAV units may adjust their damper positions to increase or decrease the amount of conditioned air entering the zone, based on the specific physical condition requirements and current physical conditions. The AHU, in turn, may adjust its operation to meet the collective demands of all the VAV units the AHU serves, modifying its supply air temperature or fan speed to efficiently meet the varying needs of different zones.

The BMS controls the AHUs of the HVAC system to automate the operation of AHUs and achieve/maintain the setpoints predefined in accordance with the desired physical conditions in the premises. Sensors in the AHUs work with the BMS to monitor ongoing physical conditions and the operating parameters of the AHUs. The BMS may collect and analyze data from the sensors coupled to an AHU in order to regulate the operation of the AHU. Based on the data from the sensors, the BMS may adjust the setpoints for the operating parameters of the AHU, for example, through actuators that execute physical changes (e.g., opening valves). The sensors may provide real-time data to the BMS which may pass instructions to adjust the setpoints for the operating parameters of the AHU to maintain the desired physical conditions in the premises.

Generally, the control of the AHUs of the HVAC system is managed through a proportional-integral-derivative (PID) loop within the BMS. The PID loop may refer to a control algorithm implemented in the HVAC systems to adjust the setpoints of the operating parameters of the AHUs to achieve optimal performance. For example, if the temperature of a zone of the premises rises above a predefined threshold, the PID loop may respond by increasing the flow of chilled water through the corresponding AHU to cool the zone down.

However, this traditional method of controlling the operation of the AHUs focuses primarily on reacting to changes in physical conditions rather than proactively managing them. While PID loops are effective for basic control tasks, these conventional PID loops may have limitations in complex environments like large commercial premises or pharmaceutical facilities. One issue is that PID loops may not account for the variable demand at an end-user level. The conventional PID loops operate on predefined settings and react to changes in the physical conditions rather than anticipating such changes. This may lead to inefficiencies in dynamic environments where the demand may fluctuate due to factors like changes in premises occupancy or external weather conditions. For example, in a multi-zone office building, a PID loop controlling an AHU may maintain a constant supply air temperature based on a fixed setpoint, even when some zones require less cooling due to reduced occupancy, potentially resulting in overcooling and energy waste.

Moreover, traditional BMSs with PID loop-based control may not incorporate advanced technologies such as artificial intelligence (AI) or machine learning (ML), which may predict and adjust to changes more efficiently. Without these capabilities, the BMS may not optimally adjust the operation of chillers, boilers, AHUs, and VAV units based on real-time data or predictive insights. This may result in zones within the premises that are either over-conditioned or under-conditioned, leading to energy waste and discomfort for the occupants.

The problem may be further compounded in settings where the desired physical conditions are required to adhere to strict regulatory standards, such as in clean rooms in pharmaceutical manufacturing facilities. In these environments, deviations from the desired physical conditions may have implications for product quality and compliance. Traditional BMSs may face challenges in maintaining these physical conditions consistently when faced with external changes or system demands that exceed the initial design considerations of the HVAC system.

Additionally, manual adjustment of the setpoints by operators in response to changing physical conditions or system inefficiencies may lead to a reactive rather than a proactive management of the environment. This not only requires significant human intervention but also increases the likelihood of error and inefficiency. The operators may run the AHUs and zones at higher setpoints, pushing the HVAC system to operate at or near its capacity limits. This may result in formation of rogue zones within the premises where the demand for cooling or heating is consistently high. Consequently, any upstream asset of the HVAC system, for example, a boiler or a chiller, may not provide any optimization results, which leads to a lost opportunity for energy optimization.

One of the conventional approaches to solving the above mentioned problem of the rogue zones through the BMS may include pausing energy optimization algorithms run by the BMS for the entire HVAC system. This is done to prevent the BMS from making the setpoint adjustments that may further exacerbate the problem in the rogue zones or cause discomfort in other zones. However, this approach results in the entire HVAC system operating sub-optimally, even in areas not affected by the rogue zone.

Another conventional approach to solve the issue of rogue zones is to configure the BMS to disregard the rogue zone in the optimization process and continue optimization for other zones only. While this may allow for continued efficiency in unaffected areas, the approach leaves the rogue zone unaddressed, leading to ongoing comfort issues or regulatory non-compliance along with the lost opportunity to save energy by potential optimization in such rogue zones.

As a result, the conventional solutions implemented for optimization of the energy usage by the HVAC system may not be able to effectively address the challenges posed by the rogue zones, dynamic physical conditions, and complex regulatory requirements. These conventional solutions may lead to suboptimal energy efficiency, inconsistent comfort levels across different zones, and potential non-compliance with environmental standards in specialized facilities.

According to example implementations of the present subject matter, techniques for managing operations of the HVAC systems installed in the premises that optimize energy usage in the premises are described. The present subject matter includes determining a setpoint specified for each of a plurality of zones in the premises. In an example, the setpoint corresponds to a target value for an operating parameter of a variable air volume (VAV) unit that is configured to regulate physical conditions, such as temperature, humidity, and airflow, in the corresponding zone. In another example, the setpoint for each zone may be specified by a user based on requirements for the physical conditions desired in the corresponding zone. For example, in a third floor (zone A) of a premises, temperature setpoint of 73° F. may be specified by users of the third floor to maintain slightly cooler environment. Similarly, a user of a second floor (zone B) of the premises may requests a temperature setpoint of 75° F., as the user finds this temperature more comfortable for their tasks.

Furthermore, in an embodiment, the setpoint specified for each of the zones of the premises may be compared to a predefined value of the setpoint. This predefined value of the setpoint may be selected to achieve a predetermined level of energy efficiency in the operation of an air handling unit (AHU) that supplies conditioned air to all the VAV units of the corresponding zones. Based on the comparison, a rogue zone may be identified. In an example, the rogue zone may refer to a zone where the setpoint specified by the user of that zone exceeds the predefined value of the setpoint by a predetermined threshold. For example, if the predefined value of the temperature setpoint is set at 22° C., and the threshold is 1.7° C., any zone from the plurality of zones with a setpoint above 23.9° C. may be identified as a rogue zone.

Furthermore, upon identifying the rogue zone, current physical conditions of the rogue zone may be determined. Based on the current physical conditions of the rogue zone, the specified setpoint of the rogue zone may be regulated, for example, by adjusting the specified setpoint towards the predefined value.

Accordingly, the present subject matter, by identifying and addressing rogue zones individually, the system can optimize energy usage while maintaining comfort levels across all zones. This allows for more efficient operation of the HVAC system as a whole, leading to significant energy savings without compromising user comfort or regulatory compliance in specialized environments. Furthermore, the ability to dynamically adjust setpoints based on current physical conditions enables a more proactive and responsive HVAC management strategy. This may result in improved overall performance of the HVAC system, reduced energy waste, and enhanced user satisfaction.

The above techniques are further described with reference to FIG. 1 to FIG. 9. It should be noted that the description and the Figures merely illustrate the principles of the present invention along with examples described herein and should not be construed as a limitation to the present invention. It is thus understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present invention. Moreover, all statements herein reciting principles, aspects, and implementations of the present invention, as well as specific examples thereof, are intended to encompass equivalents thereof.

FIG. 1 illustrates a network environment 100 for implementing examples techniques for optimizing energy usage in a premises, in accordance with an example implementation of the present invention.

Various operations are carried out in a premises, such as industrial facilities, laboratories, commercial offices, malls, hotels, hospitals, residential complexes, or educational institutions, to create physical conditions within the premises, often, while addressing additional requirements, such as cost-efficient and sustainable operation of the premises. As the premises are designed for a wide variety of purposes, the physical conditions of the premises may vary significantly to cater to the respective purposes.

A heating, ventilation, and air conditioning (HVAC) system 104 may be installed in the premises, such as the premises 102, in accordance with embodiments of the present subject matter. The HVAC system 104 may include one or more assets that may operate in conjunction with each other to achieve and maintain the physical conditions within the premises 102 that may be predefined in accordance with the purpose that the premises 102 is designed to serve. Physical condition of the premises 102 may refer to an environmental state or ambient condition within the premises 102 that is created to serve a purpose in the premises 102. For example, in the context of a laboratory in a pharmaceutical manufacturing facility, the physical conditions may be created in accordance with the requirements of specific experiments or processes being conducted in the laboratory. Examples of these physical conditions may include, but are not limited to, temperature, humidity, air flow, and various combinations thereof in the premises 102.

In an embodiment, the HVAC system 104 may include an air handling unit (AHU) 108. The AHU 108 may be connected to a chiller and boiler plant (not illustrated) which provide chilled and heated water respectively. In an example, the HVAC system 104 may deliver airflow supplied by the AHU 108 to the premises 102 to maintain the desired physical conditions in the premises 102 via air supply ducts (not illustrated) and may provide return air from the premises 102 to the AHU 108 via air return ducts (not illustrated).

In some embodiments, the HVAC system 104 may cater to a plurality of zones 106-1 (e.g., zone 1), 106-2 (e.g., zone 2), . . . , and 106-N (e.g., zone N) within the premises 102. A zone within the premises 102 may refer to a specific area or section of the premises 102 where the physical conditions may be maintained. For example, a zone may be a single room, a group of rooms, or an area within the premises 102 where the HVAC system 104 may be configured to achieve the predefined physical conditions for said zone.

In an example, each zone 106-1, 106-2, . . . , and 106-N may have different occupancy patterns, thermal characteristics, or usage purposes, necessitating individualized control of the physical conditions such as the temperature, humidity, and air flow. For example, the zone 106-1 may correspond to a server room within the premises 102 that may require cooler temperatures and lower humidity compared to other zones of the HVAC system 104. Similarly, the zone 106-2 may correspond to a manufacturing area that may need specific temperature control and higher air circulation rates.

As may be understood, the HVAC system 104 installed in any premises, such as the premises 102, may need to be configured in such a manner that achieving and maintaining the physical conditions of the premises 102 or the different zones of the premises 102 also account for a safe and energy-efficient operation of the HVAC system 104 that brings about said physical conditions. Thus, the HVAC system 104 to be installed in the premises 102 may be selected bearing the purpose of the premises 102 into consideration. In other words, the HVAC system 104 may be selected such that the physical conditions required to serve the purpose of different zones of the premises 102 are achieved by operating the HVAC system 104 in accordance with safe limits of operation of the HVAC system 104 and energy efficiency. For example, when selecting an HVAC system 104 for the premises 102 that includes both office spaces and a server room, it may be need to be ensured that the HVAC system 104 is capable of maintaining comfortable temperatures in the office areas while also providing the cooler temperatures and lower humidity levels required for the server room. This may involve choosing a HVAC system with sufficient capacity and flexibility to meet these diverse needs. The selection process may also consider factors such as the size of the premises 102, layout, insulation, and local ambient condition to ensure the chosen HVAC system may operate efficiently and safely under all expected conditions.

Thus, to ensure that the physical conditions of the zones 106-1, 106-2, . . . and 106-N account for the safe and energy-efficient operation of the HVAC system 104, setpoints of operating parameters of the AHU 108 of the HVAC system 104 may be maintained within predefined safe limits of the operating parameters that may be computed based on a predetermined level of energy efficiency in operation of the HVAC system 104. The operating parameters of the AHU 108 may be understood as measurable attributes of the AHU 108 that may be controlled to control an output of the AHU 108 for creating the desired physical condition in the respective zones. Examples of the operating parameters, for example, of the HVAC system 104, may include air temperature, and/or the air speed, among others, that may be sensed, for example, by a corresponding sensor of the AHU 108.

In an example, the predefined safe limits of the operating parameters for the AHU 108 may be defined by a manufacturer of the HVAC system 104, for example, based on a rated capacity, design, and other factors relating to the energy-efficient performance capability of the HVAC system 104 to prevent malfunctions and/or energy-inefficient operation of the HVAC system 104 during its operation in the premises 102.

As explained previously, maintaining desired physical conditions in the zones 106-1, 106-2, . . . and 106-N may involve regulating the physical conditions based on changes in factors that influence the physical conditions. For example, maintaining physical conditions in a zone, such as the zone 106-1, throughout a day may involve altering temperature of the zone 106-1 in the morning, afternoon, and night.

Regulation of the physical conditions may refer to a process of monitoring and adjusting setpoint of operating parameters, such as temperature, air flow, humidity, and other factors of the AHU 108 that contribute to physical conditions of the zones 106-1, 106-2, . . . and 106-N. This regulation is usually done to respond to changes in external environmental conditions, occupancy patterns, and specific requirements of the use of the zones 106-1, 106-2, . . . and 106-N. For example, the external environmental conditions, such as changes in weather, may influence the physical conditions of the zones 106-1, 106-2, . . . and 106-N requiring adjustments to the operating parameters of the AHU 108 catering to the zones 106-1, 106-2, . . . and 106-N. Additionally, the use of the zones 106-1, 106-2, . . . and 106-N may change over time, for example, an office space in the premises 102 generally becomes vacant after business hours, prompting a change in the desired physical conditions to conserve energy while still preventing environmental extremes that may cause damage to the premises 102 or the HVAC system 104.

In some embodiments, to address dynamic requirements corresponding to the physical conditions of the zones 106-1, 106-2, . . . , and 106-N, each zone may include a separate variable air volume (VAV) unit (e.g., zone 106-1 may include a VAV unit 110-1, zone 106-2 may include a VAV unit 110-2, . . . zone 106-N may include a VAV unit 110-N). Each VAV unit 110-1, 110-2, . . . , and 110-N may include a damper, such as dampers 112-1, 112-2, . . . and 112-N or other flow control elements that may be operated to control an amount of airflow provided through the AHU 108 to the individual zones 106-1, 106-2, . . . and 106-N of the HVAC system 104. In an example, the VAV units 110-1, 110-2,. and 110-N may operate by varying the airflow through each zone 106-1, 106-2, . . . , and 106-N while maintaining a constant temperature. This may allow for accurate control of the temperature in each zone 106-1, 106-2,. . . , and 106-N, as the amount of conditioned air may be adjusted based on the requirement of the physical condition of that zone 106-1, 106-2, . . . , and 106-N. For example, if zone 106-1 requires cooling while zone 106-2 does not, the VAV unit 110-1 may increase its airflow while the VAV unit 110-2 may reduce or stops its airflow. This may enable the HVAC system 104 to manage the diverse and changing needs corresponding to the physical conditions of different zones 106-1, 106-2, . . . , and 106-N.

In an example, a VAV unit, such as the VAV units 110-1, 110-2,. and 110-N, may be any computing device, such as a microcontroller, a programmable logic controller (PLC), or an embedded system. The VAV units 110-1, 110-2, . . . , and 110-N may include a processor, memory, and input/output interfaces to control the respective damper 112-1, 112-2, . . . , and, 112-N and communicate with other components of the HVAC system 104, such as the AHU 108. The VAV units 110-1, 110-2, . . . , and 110-N may also include sensors 114-1, 114-2, . . . and 114-N to measure airflow, temperature, and other attributes of the airflow, allowing the VAV units 110-1, 110-2, . . . , and 110-N to make real-time adjustments in the airflow based on current physical conditions of the corresponding zones 106-1, 106-2, . . . , and 106-N.

In some embodiments, the HVAC system 104 may deliver the airflow into one or more zones 106-1, 106-2, . . . , and 106-N of the HVAC system 104 (e.g., via supply ducts) without using intermediate VAV units 110-1, 110-2, . . . , and 110-N or other flow control elements. In such embodiments, the AHU 108 may include various sensors (e.g., temperature sensors, pressure sensors, etc.) (not illustrated) configured to measure attributes of the airflow supplied through the AHU 108. The AHU 108 may receive input from the sensors 114-1, 114-2, . . . and 114-N within the zones 106-1, 106-2, . . . and 106-N and may adjust the air flow rate, temperature, or other attributes of the airflow supplied through AHU 108 to achieve the desired physical conditions for the corresponding zones 106-1, 106-2, . . . and 106-N of the HVAC system 104.

In operation, to achieve predefined physical conditions, such as those desired by a user, within the zones 106-1, 106-2, . . . and 106-N, the setpoints of the operating parameters of the AHU 108 may be influenced by the demands of the VAV units 110-1, 110-2, . . . , and 110-N corresponding to the zones 106-1, 106-2, . . . and 106-N. In other words, the VAV units 110-1, 110-2, . . . , and 110-N may affect the setpoints of the operating parameters of the AHU 108 by modulating the dampers 112-1, 112-2, . . . , and 112-N to meet the physical conditions the defined for their respective zones 106-1, 106-2, . . . , and 106-N. The AHU 108 may then adjusts the setpoint of the operating parameters to meet this collective demand from all the VAV units 110-1, 110-2, . . . , and 110-N. For example, a predefined physical condition may correspond to a certain level of humidity in a zone, such as the zone 106-1. This specific level of humidity may be understood as a setpoint, which is a target value for the physical condition in the zone 106-1. To achieve said humidity level, a VAV unit of the zone 106-1, such as the VAV unit 110-1 may regulate the corresponding damper 112-1 to control the airflow into the zone 106-1. If the desired humidity level is 45% relative humidity, the VAV unit 110-1 may adjust the damper 112-1 to increase or decrease airflow based on the current humidity level in the zone 106-1.

In accordance with example implementations of the present subject matter, the AHU 108 works in conjunction with a building management system (BMS) 116 to achieve the predefined the physical conditions in the zones 106-1, 106-2, . . . and 106-N. In an example, the BMS 116 may refer to a system that is configured to determine suitable setpoints for various operating parameters of the AHU 108 of the premises 102 for achieving the predefined desired physical conditions in the zones 106-1, 106-2, . . . and 106-N. The BMS 116, in an example, may use tools, such as artificial intelligence-based algorithms and data analytics to determine setpoints corresponding to each of the desired physical conditions, which may often vary significantly.

In an example, the BMS 116 may take into account variables that may affect the physical conditions in the zones 106-1, 106-2, . . . and 106-N and accordingly provide a range of setpoints for the operating parameters of the AHU 108. In an example, the range of setpoints may be set such that the range of setpoints lies within the predefined safe limits of the operating parameters, accounting for both safe and energy-efficient operation of the HVAC system 104. In an example, the variables affecting the physical conditions in the zones 106-1, 106-2, . . . and 106-N may include, but are not limited to, actual occupancy levels and weather conditions, such as outside air temperature, which may impact the physical conditions of each zone 106-1, 106-2, . . . and 106-N. By considering such variables, the BMS 116 may dynamically adjust the setpoints for the operating parameters of the AHU 108. This dynamic adjustment allows the HVAC system 104 to respond to changing conditions and maintain optimal comfort and energy efficiency across all zones.

In an example, a “setpoint” of an operating parameter of an AHU, such as the AHU 108, may be either a single value or a pair of values corresponding to minimum and maximum bounds. For example, a setpoint for an operating parameter, i.e., temperature settings, may be defined as 25° C. The setpoint can also be a range of values comprising values ranging from a minimum to a maximum value. For example, the setpoint for the temperature settings may be defined as 20° C. to 30° C. The setpoints for the operating parameters of the AHU 108 may be prescribed depending on the configuration of the BMS 116 defined as per the requirements of the physical conditions of each zone 106-1, 106-2, . . . and 106-N. For example, if the zone 106-1 requires precise temperature control due to sensitive equipment or processes, temperature setpoint for the zone 106-1 may be a narrower range, such as 22° C. to 24° C. Conversely, for a less critical zone such as the zone 106-2, the temperature setpoint may have a wider range, such as 20° C. to 26° C., allowing for more flexibility in energy management. The BMS 116 may also adjust these setpoints based on factors such as time of day, occupancy levels, or external weather conditions to optimize both comfort and energy efficiency across all zones.

In one example, the adjustments in the setpoints that are determined by the BMS 116 may be communicated via a network 118 to the AHU 108, which, in turn, operate the VAV units 110-1, 110-2, . . . , and 110-n so that the operation of the VAV units 110-1, 110-2, . . . , and 110-n reflects the adjusted setpoints.

In an example, the network 118 may be a single network or a combination of multiple networks and may use a variety of different communication protocols. The network may be a wireless or a wired network, or a combination thereof. Examples of such individual networks include, but are not limited to, Global System for Mobile Communication (GSM) network, Universal Mobile Telecommunications System (UMTS) network, Personal Communications Service (PCS) network, Time Division Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network, Next Generation Network (NON), Public Switched Telephone Network (PSTN). Depending on the technology, the network 118 includes various network entities, such as gateways and routers; however, such details have been omitted for the sake of brevity of the present description.

In an example, the BMS 116 may be implemented on a server or other computing device (not illustrated) that communicatively couples to the AHU 108, for example, via the network 118. The server running the BMS 116 may be a standalone server or maybe a remote server on a cloud computing platform to which the local controller 106 may be connected over the network 118 directly or through the supervisory controller. In an embodiment, the server may be a cloud-based computing system. The server may include one or more servers on which an operating system may be installed that may run the BMS 116. The server may include one or more processing units, one or more storage devices, such as memory units, for storing data and machine-readable instructions for example, applications and application programming interfaces (APIs), and other peripherals required for providing cloud computing functionality.

In accordance with example embodiments of the present subject matter, the network environment 100 may include an energy optimizer 120 (hereinafter “optimizer 120”) for optimizing energy usage of the HVAC system 104 in the premises 102. The optimizer 120 may be configured to analyze the operation of the HVAC system 104 and identify opportunities for energy savings. In doing so, the optimizer 120 may provide set adjustments for the operating parameters of the AHU 108 of the HVAC system 104 thereby improving overall efficiency of the HVAC system 104 while maintaining occupant comfort. By fine-tuning the operation of the AHU 108, the optimizer 120 may reduce unnecessary energy consumption, minimize simultaneous heating and cooling, and balance the load across different zones 106-1, 106-2, . . . and 106-N. This may lead to significant energy savings, reduced operational costs, and improved sustainability for the premises 102. For example, in scenarios where a VAV unit of a zone, such as the VAV unit 110-1 of the zone 106-1, constantly demands cooling that may cause the AHU 108 to operate at maximum load, the optimizer 120 may intervene to optimize energy usage.

The optimizer 120 thus may be operable to handle adjustments in the setpoints of the operating parameters of the AHU 108 that may minimize the energy inefficient operation of the AHU 108, thereby optimizing overall energy consumption of the HVAC system 104. These adjustments may be made dynamically and in real-time, responding to changing conditions and demands across all zones 106-1, 106-2, . . . and 106-N.

Examples of the optimizer 120 may be a computing device, such as a server, a single or a distributed computing device. In an example embodiment, the computing device, such as a server running the BMS 116 may also host the optimizer 120. In some embodiments, the optimizer 120 may be implemented as an additional functionality within the BMS 116. In an alternative embodiment, the optimizer 120 may be a functionality distinct from the BMS 116 and may be hosted on a separate cloud server or the like.

In operation, the optimizer 120 may receive data corresponding to a setpoint specified for each of a plurality of zones 106-1, 106-2, . . . and 106-N in the premises 102. In an example, specified setpoint may refer to a target value for an operating parameter of the VAV unit 110-1, 110-2, . . . and 110-N configured to regulate physical conditions in the respective zones 106-1, 106-2, . . . and 106-N. In an example, the setpoint specified for each zone 106-1, 106-2, . . . and 106-N may be determined by occupant preferences, scheduled activities, or automated control systems within each zone 110-1, 110-2, . . . and 110-N. These setpoints may be entered into the local thermostat or control panel of each VAV unit 110-1, 110-2, . . . and 110-N. The VAV units 110-1, 110-2, . . . and 110-N may be equipped with communication interfaces that allow them to transmit this setpoint information to the BMS 116, for example, over the network 118. The BMS 116 may then aggregate this data from all the zones and transmits it to the optimizer 120, for example, through the network 118. In some implementations, the VAV units 110-1, 110-2, . . . and 110-N may directly communicate with the optimizer 120 through the network 118. The optimizer 120 may receive these setpoint data in real-time or at regular intervals, allowing the optimizer 120 to maintain an up-to-date understanding of the specified setpoint for each zone 110-1, 110-2, . . . and 110-N.

In an embodiment, the optimizer 120 may compare the specified setpoint of each of the plurality of zones 106-1, 106-2, . . . and 106-N to a predefined value of the setpoint associated with a predetermined level of energy efficiency for the AHU 108, herein referred to as energy-efficient setpoint, coupled to the VAV units 110-1, 110-2, . . . and 110-N.

Based on this comparison, the optimizer 120 may identify at least one rogue zone from the plurality of zones 106-1, 106-2, . . . and 106-N. In an example, the rogue zone may have a specified setpoint that exceeds the predefined value of the setpoint that is associated with the predetermined level of energy efficiency by a predetermined threshold. For example, if the predefined energy-efficient cooling setpoint is 24° C., and the predetermined threshold is 2° C., a zone with a cooling setpoint of 21° C. or lower may be identified as the rogue zone.

In some embodiments, each zone 106-1, 106-2, . . . and 106-N may have its own energy-efficient setpoint corresponding to physical condition requirements in the zones 106-1, 106-2, . . . and 106-N based on factors such as its location, size, occupancy, and the like. The optimizer 120 may identify a zone as a rogue zone if the specified setpoint for the zone deviates from its specific energy-efficient setpoint by more than the predetermined threshold.

Further, the optimizer 120 may receive data corresponding to current physical conditions of the rogue zone. In an example, the data corresponding to the current physical conditions of the zones 106-1, 106-2, . . . and 106-N may be provided by the BMS 116 based on inputs from sensors, such as the sensors 114-1, 114-2, . . . and 114-N installed in the premises 102 to sense physical conditions in the zones 106-1, 106-2, . . . and 106-N.

The AHU 108, in example implementations, may serve as an intermediary between the sensors 114-1, 114-2, . . . and 114-N and the optimizer 120. The AHU 108 collects the data corresponding to the current physical conditions of the zones 106-1, 106-2, . . . and 106-N from the corresponding sensors 114-1, 114-2, . . . and 114-N and then transmits this data over the network 118 to the BMS 116. The BMS 116 in turn may transmit this data to the optimizer 120. In an alternative embodiment of the present subject matter, the data corresponding to the current physical conditions of the zones 106-1, 106-2, . . . and 106-N may be sent directly to the optimizer 120 by the sensors 114-1, 114-2, . . . and 114-N.

In accordance with example implementation of the present subject matter, the optimizer 120 may adjust the specified setpoint of the rogue zone through the AHU 108 to reduce a difference between the specified setpoint and the predefined value while maintaining the current physical conditions within a predetermined range of acceptable physical conditions. For example, considering the zone 106-1 as a rogue zone, the energy-efficient setpoint (predefined value) for the zone 106-1 may be 23° C. and the current specified setpoint for the zone 106-1 may be 20° C. The predetermined range of acceptable physical conditions may be 22° C. to 25° C. The current temperature in the zone 106-1 may be 21° C. In this case, the optimizer 120 may receive data indicating that the current temperature in the zone 106-1 is 21° C. and recognize that the specified setpoint (20° C.) is lower than the energy-efficient setpoint (23° C.). The optimizer 120 may gradually adjust the specified setpoint upward, for example, to 22° C. The optimizer 120 may continue monitoring the zone 106-1 to ensure the temperature remains within the acceptable range (22° C. to 25° C.). If the zone temperature rises to 22.5° C. and remains stable, the optimizer 120 may further adjust the setpoint closer to the energy-efficient value, perhaps to 22.5° C. Through this process, the optimizer 120 may reduce the difference between the specified setpoint and the energy-efficient setpoint (from 3° C. to 0.5° C. in this example) while ensuring that the actual temperature in the zone remains within the acceptable range. This may allow for balancing energy efficiency with occupant comfort, potentially leading to energy savings without compromising the functionality of the zone 106-1 or user satisfaction.

Therefore, based on the data corresponding to the specified setpoint and the current physical conditions, the optimizer 120 may adjust the setpoint of the AHU 108, which may then configure the VAV units 110-1, 110-2, . . . and 110-N to adjust the airflow, temperature, and humidity in the respective zones 106-1, 106-2, . . . and 106-N. This adjustment may help bring the conditions of the rogue zone closer to its energy-efficient setpoint while maintaining comfort levels within the predetermined acceptable range. The VAV units 110-1, 110-2, . . . and 110-N may modulate the supply of conditioned air to each zone, allowing for precise control of the thermal environment in response to the adjusted setpoints provided by the optimizer 120.

By bringing the setpoints of the AHU 108 within the predetermined level of energy efficiency, energy inefficient operation of the HVAC system 104 may be prevented.

FIG. 2 shows the optimizer 120 that may be implemented to account for the energy efficient operation of the HVAC system 104 installed in the premises 102, according to an example implementation of the present subject matter.

In an example, the optimizer 120 may be a computing device comprising a processor 202. In an example, the processor 202 may be implemented as microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. The processor 202 may execute instructions stored in a memory of the optimizer 120 to accomplish functionalities of the optimizer 120.

As explained previously, the BMS 116 may be responsible for determining the range of setpoints for the operating parameters of the AHU 108 and manages the operation of the AHU 108 based on the demands from various zones 106-1, 106-2, . . . and 106-N of the premises 102. The optimizer 120 may be configured to enhance the energy efficiency of this operation. In cases where the specified setpoint from one or more zones 106-1, 106-2, . . . and 106-N exceeds predefined value due to extreme demand requirements, the optimizer 120 may optimize the AHU 108 operation to maintain energy efficiency while still meeting these demands. This optimization process may allow the AHU 108 to operate within its optimal energy efficiency range even when faced with challenging zone requirements.

The optimizer 120 is operable to adjust the setpoints of the AHU 108, bringing them closer to the predetermined level of energy efficiency while still maintaining acceptable comfort conditions in the zones. This adjustment may help balance the competing demands of energy efficiency and occupant comfort, resulting in significant energy savings without compromising the functionality of the zones 106-1, 106-2, . . . and 106-N or user comfort.

In doing so, the optimizer 120 receive data corresponding to the setpoint specified for each of the plurality of zones 106-1, 106-2, . . . and 106-N in the premises 102. In an example, each specified setpoint is a target value for the operating parameter of the VAV unit 110-1, 110-2, . . . and 110-N configured to regulate physical conditions in the respective zones 106-1, 106-2, . . . and 106-N. The optimizer 120 further compares the specified setpoint of each of the plurality of zones 106-1, 106-2, . . . and 106-N to a predefined value associated with a predetermined level of energy efficiency for the AHU 108 coupled to the VAV units 110-1, 110-2, . . . and 110-N.

Furthermore, the optimizer 120 identifies the at least one rogue zone from the plurality of zones 106-1, 106-2, . . . and 106-N. In an example, the rogue zone refers to a zone that has a specified setpoint that exceeds the predefined value by a predetermined threshold.

The optimizer 120 receives data corresponding to current physical condition of the at least one rogue zone. In an example, the current physical condition of the rogue zone may refer to temperature, humidity, air flow, occupancy level, or any combination thereof. These physical conditions may be measured by sensors installed in the zone, such as temperature sensors, humidity sensors, pressure sensors, CO₂ sensors, or occupancy sensors. The data may also include information about the current state of HVAC equipment serving the zone, such as the position of dampers 112-1, 112-2 . . . , and 112-N. This set of data allows the optimizer 120 to assess the current physical condition of the rogue zone and determine appropriate adjustments in the setpoints of the AHU 108.

The optimizer 120 may adjust the specified setpoint of the rogue zone to reduce a difference between the specified setpoint and the predefined value while maintaining the current physical conditions within a predetermined range of acceptable physical conditions. This may allow for the energy efficient operation of the AHU 108 while still meeting the comfort requirements of the zones 106-1, 106-2, . . . and 106-N. By minimizing the difference between the specified setpoint and the predefined value, the optimizer 120 may help optimize energy consumption without compromising occupant comfort. Additionally, this may help balance the demands of multiple zones 106-1, 106-2, . . . and 106-N served by the same AHU 108, reducing conflicts between zones 106-1, 106-2, . . . and 106-N with different requirements.

To elaborate on the functioning of the optimizer 120 to provide the optimized range of setpoints to the AHU 108 to control the setpoints of the operating parameters within the predetermined level of energy efficiency, reference is made to FIG. 3.

FIG. 3 illustrates the optimizer 120 configured to provide the setpoint adjustments for the operating parameters of the AHU 108 to optimize energy usage of the AHU 108, in accordance with an example implementation of the present subject matter. The adjusted setpoints may then be communicated to the AHU 108, allowing the AHU 108 to operate in a manner that balances energy efficiency with occupant comfort across all the zones 106-1, 106-2, . . . and 106-N served by the AHU 108.

In an example, the optimizer 120 depicted in FIG. 3 may be any computing device. Examples of the optimizer 120 include but are not restricted to servers, desktop computers, laptops, smartphones, personal digital assistants (PDAs), and tablets.

In an example implementation, the optimizer 120 includes the processor 202. The optimizer 120 also includes interface(s) 302 coupled to the processor 202. The interface(s) 302 may include a variety of software and hardware interfaces that allow interaction of the optimizer 120 with other communication and computing devices, such as network entities, web servers, external repositories, and peripheral devices. For example, the interface(s) 302 may couple the optimizer 120 with the BMS 116. The interface(s) 302 may also enable coupling of internal components, if any, of the optimizer 120 with each other.

Further, the optimizer 120 includes a memory 304 coupled to the processor 202. The memory 304 may include any computer-readable medium known in the art including, for example, volatile memory (e.g., RAM), and/or non-volatile memory (e.g., EPROM, flash memory, etc.). The memory may also be an external memory unit, such as a flash drive, a compact disk drive, an external hard disk drive, or the like. The optimizer 120 may include module(s) 306 and data 318 coupled to the processor 202. In one example, the module(s) 306 and data 318 may reside in the memory 304.

In an example, the data 318 may include specified setpoint data 320, predefined setpoint data 322, physical condition data 324, maximum change limit data 326, and other data 328. The module(s) 306 may include routines, programs, objects, components, data structures, and the like, which perform particular tasks or implement particular abstract data types. The module(s) 306 further includes modules that supplement applications on the optimizer 120, for example, modules of an operating system. The data 318 serves, amongst other things, as a repository for storing data that may be fetched, processed, received, or generated by one or more of the module(s) 306. The module(s) 306 may include a setpoint determination module 308, a rogue zone identification module 310, a physical condition determination module 312, a setpoint regulation module 314, and other module(s) 316. The other module(s) 316 may include programs or coded instructions that supplement applications and functions, for example, programs in the operating system of the optimizer 120.

In an example implementation of the present subject matter, the setpoint determination module 308 may be configured to determines the setpoint specified for each of the plurality of zones 106-1, 106-2, . . . and 106-N in the premises 102. In an example, the specified setpoint may be provided by users of the respective zones 106-1, 106-2, . . . and 106-N and acts as a target value for the operating parameters of VAV units 110-1, 110-2, . . . and 110-N that regulate physical conditions in respective zones 106-1, 106-2, . . . and 106-N.

In an example, when a user specifies a setpoint for a zone, such as the zone 106-1, for example, a desired temperature setpoint for the zone, a control system of the VAV unit 110-1 of the corresponding zone 106-1 may monitor the actual temperature of the zone 106-1 using the corresponding sensor 114-1 of the zone 106-1. If the temperature of the zone 106-1 deviates from the specified setpoint, the VAV unit 110-1 may adjusts its damper 112-1 position to modulate the airflow into the zone 106-1 from the AHU 108. For example, if the zone 106-1 is warmer than the specified setpoint, the VAV unit 110-1 may open its damper 112-1 wider to allow more conditioned air from the AHU 108 to flow into the zone 106-1. Conversely, if the zone 106-1 is cooler than the specified setpoint, the VAV unit 110-1 may partially open its damper 112-1 to increase supply of warm air from the AHU 108. This continuous adjustment of the damper 112-1 position allows the VAV unit 110-1 to maintain the temperature of the zone 106-1 as close to the user-specified setpoint as possible, effectively regulating the physical conditions in the zone 106-1 according to the user demand in the zone 106-1. The setpoint determination module 308 may store the data corresponding to the specified setpoint for each of the zones 106-1, 106-2, . . . and 106-N in the data 318 as the specified setpoint data 320 for further processing.

In an embodiment, the rogue zone identification module 310 may be configured to compare the specified setpoint of each zone 106-1, 106-2, . . . and 106-N to the predefined value of the setpoint associated with the predetermined level of energy efficiency for the AHU 108. In an example, the predetermined level of energy efficiency for the AHU 108 may refer to an optimal setpoint or range of the setpoints where the AHU 108 consumes energy most efficiently while still maintaining comfort conditions. In an example, the predetermined level of energy efficiency for the AHU 108 may be determined based on factors such as the design specifications of the AHU 108, historical performance data, and industry standards, and the requirement of the physical conditions of the zones 106-1, 106-2, . . . and 106-N. In another example, the predefined value of the setpoint may be a specific numerical threshold or range that corresponds to the predetermined level of energy efficiency. The predefined level of the setpoint serves as a benchmark against which the current operation of the AHU 108 is compared. For explanation, an example of an AHU in a commercial building with a cooling capacity of 100 tons may be considered. The AHU may be configured to operate most efficiently within specific parameters: an optimal supply air temperature range of 55° F. to 57° F., fan speed between 70% to 80% of maximum, running at 75-85% of full capacity, return air temperature between 72° F. and 75° F., and a supply-return air temperature differential of 18° F. to 20° F. The predefined values for energy efficiency may be set as an Energy Efficiency Ratio (EER) of 11.5 or higher and power consumption of 0.85 kW per ton of cooling or less. The rogue zone identification module 310 may compare specified setpoint of each zone of the building to these predefined values, which represent the optimal energy efficiency level for the AHU. This level may be determined based on the design specifications of the AHU, historical performance, industry standards, and zone requirements. The comparison may help identify zones causing the AHU to operate outside its efficient range. In an example, data corresponding to the predefined value and the predetermined level of energy efficiency may be stored in the data 318 as the predefined setpoint data 322.

In an embodiment, based on the comparison, the rogue zone identification module 310 may identify a rogue zone from amongst the plurality of zones 106-1, 106-2, . . . and 106-N. In an example, the rogue zone may have the specified setpoint that deviates from the predefined value by more than a predetermined threshold. In an example, the predetermined threshold may be determined based on factors such as the overall energy efficiency goals of the zone, operational characteristics of the HVAC system 104, historical data on zone behavior, and acceptable comfort ranges for the occupants. In an example, the predetermined threshold may be set as an absolute value or a percentage difference from the predefined value. For example, in a building with 10 zones, the predefined value of the setpoint for optimal energy efficiency may be set at 22.2° C., and the predetermined threshold may be set at ±1.7° C. The rogue zone identification module 310 may compare the specified setpoint of each zone of the building to this range: zone 1:21.7° C., zone 2:22.8° C., zone 3:20.0° C., zone 4:22.2° C., zone 5:23.3° C., zone 6:24.4° C., zone 7:21.1° C., zone 8:22.2° C., zone 9:23.9° C., and zone 10:19.4° C. In this scenario, the rogue zone identification module 310 may identify zones 3, 6, and 10 as rogue zones because their specified setpoints fall outside the predetermined threshold range of 20.5° C. to 23.9° C., potentially causing the AHU 108 to operate inefficiently.

In an embodiment, in determining a zone as a rogue zone, the rogue zone identification module 310 may consider the time period for which the specified setpoint for that zone has been outside the predefined value. In an example, the rogue zone identification module 310 may evaluate the operation of the VAV units 110-1, 110-2, . . . and 110-N serving the zones 106-1, 106-2, . . . and 106-N to identify a rogue zone from the zones 106-1, 106-2, . . . and 106-N. For example, the rogue zone identification module 310 may monitor the position of the dampers 112-1, 112-2, . . . and 112-N and airflow rate over time. If a VAV unit consistently operates at or near its maximum open position (e.g., 90-100% open) for an extended period, such as several hours or days, it may indicate that the zone served by said VAV unit is demanding more cooling or heating than the AHU 108 is configured to provide for energy efficient operation. This may be due to an unrealistic setpoint or an underlying issue in the zone. Conversely, if a damper of the VAV unit remains at or near its minimum position (e.g., 10-20% open) for prolonged periods while still not meeting the specified setpoint for the zone, it may suggest that the zone is overcooled or overheated relative to its current load or occupancy. Thus, by evaluating operational parameters of the these VAV units 110-1, 110-2, . . . and 110-N over time, the rogue zone identification module 310 may identify zones that are consistently demanding disproportionate resources or operating outside normal parameters, thereby impacting the overall efficiency of the HVAC system 104 and potentially indicating a rogue zone condition.

In an embodiment, the physical condition determination module 312 may determine the current physical conditions of the identified rogue zone. In an example, the current physical conditions of the rogue zone may refer to temperature, humidity, occupancy level, and other variables that contribute to the overall environmental state of the rogue zone. In an example, the physical condition determination module 312 may receive data corresponding to the current physical conditions of the rogue zone from sensors within the zone. For example, the current physical conditions of the rogue zone may show a temperature of 20° C., relative humidity of 45%, and an occupancy level of 8 people. This scenario may illustrate a case where the rogue zone may be overconsuming energy while meeting preferences of the occupants, thus presenting an opportunity for the optimizer 120 to make minor adjustments in the setpoints for the rogue zone that may improve energy efficiency of the AHU 108. In an example, data corresponding to the current physical conditions of the rogue zone may be stored in the data 318 as the physical condition data 324 for further processing.

In an example, the setpoint regulation module 314 may regulate the specified setpoint of rogue zones based on current physical conditions to reduce the difference between the specified setpoint and a predefined value. This regulation may include changing the specified setpoint to a new value closer to the predefined one. The new setpoint may be determined by considering various factors, including, but not limited to, the physical conditions (temperature, humidity, occupancy) of the rogue zone, historical comfort preferences, predefined comfort ranges, energy consumption, time of day, zone thermal characteristics, capabilities of the assets, such as the AHU 108 and the VAV units 110-1, 110-2 . . . and 110-N of the HVAC system 104, weather forecasts, energy-saving goals, maximum allowable change rates, outside air temperature, and the like.

In an example, the setpoint regulation module 314 may employ a weighted algorithm or optimization model to calculate a new setpoint that balances energy efficiency with occupant comfort. For example, if the rogue zone has the specified setpoint of 20° C., but the predefined value for the optimal energy efficiency is 22° C., and the outside temperature is 24° C., the setpoint regulation module 314 may set the new setpoint at 21° C. This adjustment moves the setpoint 1° C. closer to the predefined value, reducing energy consumption while maintaining occupant comfort.

In an embodiment, the setpoint regulation module 314 may be configured to change the specified setpoint of the rogue zone to the new setpoint at a maximum rate of change predefined for the rogue zone. In an example, the maximum rate of change may be predefined based on a rated capacity of a VAV unit of the rogue zone and stored in the data 318 as the maximum change limit data 326. For example, if the rogue zone has a specified setpoint of 20° C. and the new setpoint is determined to be 22° C., and the maximum rate of change for the rogue zone may be set at 0.5° C. per hour based on the capacity of the VAV unit. The setpoint regulation module 314 may accordingly implement the change over a 4-hour period. The setpoint regulation module 314 may adjust the setpoint by 0.5° C. at the start of each hour, resulting in a gradual increase from 20° C. to 20.5° C., then to 21° C., 21.5° C., and finally reaching 22° C. at the end of the fourth hour. This gradual adjustment ensures that the HVAC system 104 may effectively respond to the changing demand without overloading the VAV unit, while also allowing occupants to acclimate to the temperature change. The gradual changes are implemented because abrupt changes may affect lifetime of a component of the HVAC system 104.

In another embodiment, if the setpoint regulation module 314 determines that the current physical conditions of the rogue zone are within the predetermined range of acceptable physical conditions at the new setpoint, the setpoint regulation module 314 may further adjust the new setpoint to make it equal to the predefined value. For example, after a predetermined observation period (e.g., 24 hours) at 21° C., if the physical conditions in the rogue zone remain within the predetermined range of acceptable physical conditions, the setpoint regulation module 314 may incrementally increase the setpoint to 22° C., matching the predefined value for optimal energy efficiency. This ensures that occupant comfort is prioritized while maximizing energy savings.

In some cases, situations may arise where even if the specified setpoint in the rogue zone is beyond the predefined value of the setpoint, owing to the need for maintaining the current physical conditions for the rogue zone, the setpoint regulation module 314 may prioritize maintaining the specified setpoint for the rogue zone over adjusting the specified setpoint towards the predefined value. For example, considering a rogue zone in a laboratory setting where precise temperature control is critical for ongoing experiments. The specified setpoint may be 18° C., while the predefined value for energy efficiency may be at 22° C. However, if the current experiments require the lower temperature to maintain sample integrity or equipment stability, the setpoint regulation module 314 may choose to maintain the 18° C. setpoint rather than adjusting it towards 22° C. In this case, the setpoint regulation module 314 may recognize, for example, based on a user input, that the specific requirements of the zone take precedence over general energy efficiency goals. The setpoint regulation module 314 may continue to monitor the situation and only implement changes when the critical conditions in the zone no longer require the lower temperature setpoint.

In accordance with example implementation, reducing the energy inefficiency of the rogue zone is carried out such that there is no adverse impact on other zones. For example, if a rogue zone is demanding excessive cooling, lowering the temperature setpoint of the rogue zone may increase the load on adjacent zones as heat transfers from the warmer rogue zone. Alternatively, raising the temperature setpoint of the rogue zone may cause the AHU 108 to reduce its cooling output, which may affect other zones served by the AHU 108. Additionally, these adjustments may reduce the overall chilled water demand, which may impact the efficiency of the chiller plant if not managed properly. Therefore, there may be a need to optimize and balance the HVAC system 104 in a way that achieves positive energy savings while managing the overall zone demands.

Accordingly, in an embodiment, the setpoint regulation module 314 may adjust the specified setpoint of other zones of the plurality of zones in response to regulating the specified setpoint of the rogue zone. In an example, a magnitude of adjustment in the specified setpoint for each of the other zones may be inversely proportional to a distance of the respective zones from the AHU 108. For example, considering an office building with five zones (A, B, C, D, and E) served by a single AHU, such as the AHU 108, zone C may be identified as a rogue zone demanding excessive cooling with a setpoint of 20° C. The setpoint regulation module 314 may raise the temperature setpoint of the zone C to 22.2° C. to reduce energy inefficiency. To balance the HVAC system 104, the setpoint regulation module 314 may adjust the setpoints of other zones inversely proportional to their distance from the AHU 108. In that, zones B and D (adjacent to C) may have their setpoints lowered from 22.2° C. to 21.7° C., while zones A and E (farther from zone C) may have their setpoints lowered from 22.2° C. to 21.9° C. This may help maintain overall comfort and energy efficiency by making larger adjustments to zones closer to the AHU 108 and smaller adjustments to zones farther away, resulting in a balanced HVAC system 104 that achieves energy savings while managing demands across all the zones.

Accordingly, the optimizer 120 may identify rogue zones and adjust setpoints for the AHU 108 serving the rogue zones. This improves energy efficiency by reducing unnecessary consumption, enhanced comfort through more consistent temperature control, extended equipment life due to reduced strain, and significant cost savings from lower energy use and maintenance needs.

FIG. 4 illustrates an example graphical user interface 400 (hereinafter “GUI 400”) for real-time display of status of operation of the zones 106-1, 106-2 . . . and 106-N in a control room of the premises 102, in accordance with an example implementation of the present invention. In an example, the GUI 400 provides an overview of zone-specific setpoints, time periods, predefined ranges, rogue zone status, and recommendations for adjustments. The embodiments of the GUI 400 illustrated in FIG. 4 are for illustration only. FIG. 4 does not limit the scope of the present subject matter to any particular implementation.

According to an example implementation, the GUI 400 displays data table 402, which, in a first column 404, may include a list of zones such as a first zone 106-1, a second zone 106-2, and a third zone 106-3, and so on, similar to the zones 106-1, 106-2, . . . , and 106-N described in reference to FIGS. 1-3.

In an embodiment, the data table 402 may further include a second column 406 that includes the value of a setpoint specified by users for each zone. These setpoints represent the desired temperature settings as input by the occupants or facility managers for the first zone 106-1, the second zone 106-2, and the third zone 106-3, respectively.

In an embodiment, the data table 402 may include a third column 408 that includes the value of the time period observed for each specified setpoint. This third column 408 indicates the duration for which each specified setpoint has been maintained for the first zone 106-1, the second zone 106-2, and the third zone 106-3, respectively.

In an example, an option (not illustrated) to expand the data table 402 may be provided in the GUI 400 to see data corresponding to other zones in the premises 102. This may allow the facility managers to view and analyze information for additional zones beyond the first zone 106-1, second zone 106-2, and third zone 106-3 currently displayed. The expanded view may include scrollable or paginated content, enabling the facility managers to access comprehensive data for all zones under management.

In another embodiment, the data table 402 may include a fourth column 410 that provides a predefined range of setpoints that may correspond to energy-efficient operation of the AHU 108 serving the first zone 106-1, the second zone 106-2, and the third zone 106-3, respectively. As shown in FIG. 4, the fourth column 410 displays the predefined values of the temperature setpoint that may correspond to the optimal energy efficiency for each zone. In the example shown, the predefined value range is 21° C.-23° C. for the first zone 106-1, second zone 106-2, and third zone 106-3. This range serves as a reference point for identifying potential energy-saving opportunities and assessing whether specified setpoints align with energy efficiency goals.

In an example, based on data included in the first column 404, the second column 406, and the third column 408, the optimizer 120 may determine whether any of the first zone 106-1, the second zone 106-2, and the third zone 106-3 are operating as a rogue zone. The optimizer 120 may analyze the specified setpoint, the duration for which the specified setpoint has been maintained, and compare the specified setpoint to the predefined value of the setpoints to identify zones that may be consuming excessive energy or operating outside optimal parameters. This determination may be reflected in a fifth column 412, which may indicate whether each zone is classified as a rogue zone.

In some embodiments, based on the identification of the rogue zone, the GUI 400 may also provide a recommendation of a corrective action corresponding to the rogue zone. For example, as shown in FIG. 4, the optimizer 120 may identify the second zone 106-2 and the third zone 106-3 as potential rogue zones due to their specified setpoints falling outside the predefined energy-efficient range. Accordingly, the optimizer 120 may suggest corrective actions that may include increasing the setpoint for the second zone 106-2 from 20° C. to 21° C., and decreasing the setpoint for the third zone 106-3 from 24° C. to 23° C. These recommendations may be displayed in a sixth column 414 of the data table 402.

In an example, the corrective actions suggested by the optimizer 120 aim to bring the zone setpoints within the predefined energy-efficient range while maintaining occupant comfort. By providing these recommendations, the GUI 400 may enables facility managers or building operators to make informed decisions, for example by allowing the facility managers to provide manual inputs via the GUI 400, about adjusting HVAC system 104 settings to optimize energy usage across all zones.

Thus, the real-time display of specified setpoints of the zones, time periods, predefined energy-efficient ranges, rogue zone identification, and recommended actions, enables facility managers, building operators, or the automated system itself to make informed decisions about energy optimization. This also facilitates quick identification of problematic zones and offers actionable insights to improve energy efficiency while maintaining occupant comfort, ultimately contributing to reduced energy consumption and operational costs in the premises 102.

FIG. 5 illustrates a signal flow 500 in a process to optimize energy usage in a premises, such as the premises 102. As described in reference to FIGS. 1-3, the HVAC system 104 may be installed in the premises 102 to carry out various operations to maintain and regulate desired physical conditions in various zones 106-1, 106-2, . . . , and 106-N of the premises 102 that may include, but is not limited to, temperature, humidity, air flow, and the like. The physical conditions may vary based on various factors such as external weather conditions, occupancy patterns of the zones 106-1, 106-2, . . . , and 106-N, usage of the zones 106-1, 106-2, . . . , and 106-N, or other factors that may influence the physical conditions of the zones 106-1, 106-2, . . . , and 106-N.

As explained previously, to achieve the physical conditions in the zones 106-1, 106-2, . . . , and 106-N in accordance with user demand for the physical conditions in the respective zones 106-1, 106-2, . . . , and 106-N, the specified setpoints are determined based on input from users or occupants of each zone 106-1, 106-2, . . . , and 106-N. These specified setpoints are then used to control the operating parameters of the VAV units 110-1, 110-2, . . . , and 110-N of the respective zones 106-1, 106-2, . . . , and 106-N. The VAV units 110-1, 110-2, . . . , and 110-N receive conditioned air from the AHU 108 and adjust it to meet the specified setpoints, such that the desired temperature, humidity, and air flow are achieved in each zone 106-1, 106-2, . . . , and 106-N.

In an example, this control may involve adjusting the damper 112-1, 112-2, . . . , and 112-N positions of the VAV units 110-1, 110-2, . . . , and 110-N to regulate both the airflow rates and temperature based on feedback from zone sensors, such as the sensors 114-1, 114-2, . . . , and 114-N. The damper 112-1, 112-2, . . . , and 112-N positions are controlled to modulate the amount of conditioned air supplied by each VAV unit 110-1, 110-2, . . . , and 110-N, thereby adjusting the temperature, humidity, and airflow in each zone 106-1, 106-2, . . . , and 106-N to meet the demand for physical conditions as specified by the user defined setpoints.

To ensure that the demand for the physical conditions of a zone does not cause the AHU 108 of the HVAC system 104 to operate outside the energy efficient range, the energy optimizer 120 may be implemented.

In an example implementation of the present subject matter, as indicated in step 502, a request 504 for maintaining a specified setpoint in a zone, such as the zone 106-1, to achieve physical conditions that may be in accordance with the preference of an occupant of the zone 106-1 may be received at a VAV unit, such as the VAV unit 110-1 of the zone 106-1. Upon receiving this request, the VAV unit 110-1 may adjust its operation to meet the specified setpoint, which may involve modulating position of a damper, such as the damper 112-1, of the VAV unit 110-1 adjusting airflow rates, or activating heating or cooling elements if present.

Further, in an embodiment, as indicated in the steps 506, 508, and 510, respectively, data corresponding to the request 504 relating to the specified setpoint may also be communicated to the optimizer 120 via the AHU 108 and BMS 116. In another embodiment, data corresponding to the request 504 may be transmitted directly to the optimizer 120. For example, the VAV unit 110-1 of the zone 106-1 may communicate directly with the optimizer 120.

In an embodiment, after receiving the specified setpoint corresponding to the zone 106-1, the optimizer may compare the specified setpoint of zone 106-1 to the predefined value of the setpoint. As explained previously, the predefined value of the setpoint may be computed based on the predetermined level of energy efficiency expected from the AHU 108 coupled to the VAV unit 110-1 of the zone 106-1.

In an embodiment, based on this comparison, if the optimizer 120 determines that the specified setpoint for the zone 106-1 exceeds the predefined value by a predetermined threshold, the optimizer 120 may identify the zone 106-1 as a rogue zone. For example, if the specified setpoint for temperature in the zone 106-1 is 24° C., and the predefined value range is 21° C.-23° C. with a predetermined threshold of 1° C., the optimizer 120 may identify the zone 106-1 as a rogue zone. In an example, as explained previously, in identifying the zone 106-1 as the rogue zone, the optimizer 120 may determine that the specified setpoint for the zone 106-1 has exceeded the predefined value by the predetermined threshold for a predetermined period of time. For example, if the predefined temperature range for optimal operation is 21° C.-23° C., and the zone 106-1 has maintained a setpoint of 25° C. (which exceeds the upper limit by 2° C.) for a continuous period of 4 hours (considering that the predetermined time threshold is 3 hours), the optimizer 120 may identify the zone 106-1 as a rogue zone. This helps in distinguishing between temporary fluctuations and persistent issues that may significantly impact the overall energy efficiency of the HVAC system 104.

Furthermore, in an embodiment, as indicated in step 512, data 514 corresponding to current physical conditions in the identified rogue zone 106-1 may be received at the optimizer 120 from the sensor 114-1 installed in the zone 106-1. Although the data 514 is shown to be directly transmitted to the optimizer 120 in the embodiment illustrated in FIG. 5, the data 514 may be received by the optimizer from the BMS 116 in other embodiments. As explained previously, the data 514 may include real-time measurements of temperature, humidity, occupancy status, and other relevant parameters that may be used by the optimizer 120 to characterize the current physical conditions of the zone 106-1. This data 514 may allow the optimizer 120 to make decision about how to address the rogue zone condition while maintaining occupant comfort.

In an embodiment, based on the current physical conditions of the rogue zone 106-1, the optimizer 120 may determine a new setpoint for the operating parameters of the AHU 108 corresponding to the rogue zone 106-1. In an example, the new setpoint may be closer to the predefined value of the setpoint. For example, if the rogue zone 106-1 has a specified temperature setpoint of 26° C. and the predefined value range is 21° C.-23° C., the optimizer 120 may determine a new setpoint of 24° C. for the AHU 108 serving this zone 106-1. This adjustment brings the specified setpoint closer to the predefined range while still considering occupant comfort.

As indicated in step 516, a notification 518 corresponding to the new setpoint may be communicated from the optimizer 120 to the BMS 116. Further, as indicated in step 520, from the BMS 116, the notification 518 regarding the new setpoint may be transmitted to the AHU 108 for implementation.

Furthermore, as indicated in step 522, the AHU 108 may send a command 524 to the VAV unit 110-1 of the rogue zone 106-1 to adjust the specified setpoint of the rogue zone 106-1 in accordance with the new setpoint. Accordingly, as indicated in step 526, the VAV unit 110-1 may send an actuation command 528 to the damper 112-1 of the VAV unit 110-1 to regulate the airflow in the rogue zone 106-1 in accordance with the new setpoint. For example, if the new setpoint determined by the optimizer 120 is to reduce the temperature in the rogue zone 106-1 from 26° C. to 24° C., the AHU 108 may adjust its supply air temperature to 22° C. The VAV unit 110-1 may then modulate the damper 112-1 to increase the airflow into the zone 106-1, gradually bringing the temperature down to the new setpoint.

Accordingly, by configuring the VAV unit 110-1 of the rogue zone 106-1 to bring the specified setpoint closer to the predefined value, it may be ensured that the overall energy consumption of the HVAC system 104 is optimized while maintaining occupant comfort. This adjustment helps to balance the load across the HVAC system 104, reducing strain on the AHU 108 and thus lowering energy costs.

FIG. 6 illustrates a flowchart of a method 600 that accounts for the energy efficient operation of an HVAC system, such as the HVAC system 104, of the premises 102, according to an example implementation of the present subject matter. The order in which the method 600 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement the method 600, or an alternative method. Furthermore, the method 600 may be implemented by processor(s) or computing device(s) through any suitable hardware, non-transitory machine-readable instructions, or a combination thereof.

It may be understood that steps of the method 600 may be performed by programmed computing devices and may be executed based on instructions stored in a non-transitory computer-readable medium. The non-transitory computer-readable medium may include, for example, digital memories, magnetic storage media, such as magnetic disks and magnetic tapes, hard drives, or optically readable digital data storage media. In an example, the method 600 may be performed by the optimizer 120.

Referring to FIG. 6, at block 602, a setpoint specified for each of the plurality of zones 106-1, 106-2, . . . and 106-N in the premises 102 may be determined, for example, by the setpoint determination module 308. In an example, the specified setpoint may refer to a target value for the operating parameter of a VAV unit, such as the VAV units 110-1, 110-2, 110-N, configured to regulate the physical conditions in the respective zones 106-1, 106-2, . . . and 106-N. In another example, specified setpoint for each of the plurality of zones 106-1, 106-2, . . . and 106-N may be based on requirements for the physical conditions according to user demand in the respective zones 106-1, 106-2, . . . and 106-N. For example, a user in the zone 106-1 may set a temperature of 22° C. for their office space, while a user in zone 106-2 may require a cooler temperature of 20° C. for a crowded reception area. These user-defined setpoints become the specified setpoints for the respective zones 106-1, 106-2. The VAV units 110-1, 110-2 associated with these zones 106-1, 106-2 may then attempt to maintain these specified setpoints by adjusting the airflow and temperature of the conditioned air supplied by the AHU 108.

At block 604, the specified setpoint of each of the plurality of zones 106-1, 106-2, . . . and 106-N may be compared, for example, by the rogue zone identification module 310, to a predefined value of the setpoints that may be computed based on the predetermined level of energy efficiency in operation of AHU 108. In an example, the predefined value of the setpoints may represent optimal values of the setpoints balancing energy efficiency and occupant comfort. In an example, the predefined value of the setpoints for the operating parameters of the AHU 108 may be determined, for example, through methods such as historical data analysis, building energy modeling, machine learning algorithms, industry standards, and time-based adjustments. In some embodiments, the optimizer 120 may analyze past performance data, simulate various scenarios using building thermal models, employ AI techniques for continuous optimization, incorporate industry best practices, and consider time-of-day and seasonal factors to establish the predefined value of the setpoints that corresponds to energy-efficient operations.

At block 606, a rogue zone from the plurality of zones 106-1, 106-2, . . . and 106-N may be identified, for example, by the rogue zone identification module 310. In an example, in the rogue zone, the specified setpoint exceeds the predefined value by a predetermined threshold. Thus, the comparison between the specified setpoints and the predefined values of the setpoints allows the optimizer 120 to identify rogue zones that may be operating outside the energy-efficient range. For example, if a specified setpoint of a zone significantly deviates from the predefined value, this may indicate that the zone is demanding excessive heating or cooling, leading to inefficient of the AHU 108. This comparison enables the optimizer 120 to identify zones that may require further investigation or adjustment to optimize overall energy consumption while maintaining acceptable comfort levels.

At block 608, current physical conditions of the identified rogue zone may be determined, for example, by the physical condition determination module 312. In an example, the current physical conditions of the rogue zone may correspond to temperature, humidity, air flow, occupancy, and other relevant environmental parameters. These conditions may be measured, for example, using various sensors installed in the rogue zone, such as thermostats, hygrometers, CO2 sensors, and occupancy detectors. The optimizer 120 may collect real-time data from these sensors to assess the current physical conditions of the rogue zone. By analyzing these current physical conditions, the optimizer 120 may make informed decisions about how to address the rogue zone while maintaining occupant comfort and optimizing energy efficiency.

At block 610, based on the current physical conditions, the specified setpoint of the at least one rogue zone may be regulated, for example, by the setpoint regulation module 314, such that the specified setpoint of the rogue zone is adjusted towards the predefined value. In an example, regulating the setpoint of the rogue zone may include gradually modifying the temperature or humidity setpoint of the AHU 108 to bring it closer to the predefined value. In an example, this adjustment may be performed in small increments to avoid sudden changes that may impact occupant comfort.

Consequently, the example method 600 facilitates the reduction in the excessive demand from the rogue zone, thereby improving overall efficiency of the HVAC system 104 while maintaining acceptable physical conditions for the occupants.

FIG. 7 illustrates a flow diagram of a process 700 for adjusting setpoints of operating parameters of an AHU, such as the AHU 108, in response to determining a rogue zone among a plurality of zones, such as the zones 106-1, 106-2, . . . and 106-N served by the AHU 108, according to an example implementation of the present subject matter. The order in which the above-mentioned process is described is not intended to be construed as a limitation, and some of the described process blocks may be combined in a different order to implement the process, or an alternative process.

Furthermore, the above-mentioned process may be implemented in a suitable hardware, computer-readable instructions, or combination thereof. The steps of such process may be performed by either a system under the instruction of machine executable instructions stored on a non-transitory computer readable medium or by dedicated hardware circuits, microcontrollers, or logic circuits. Herein, some examples are also intended to cover non-transitory computer readable medium, for example, digital data storage media, which are computer readable and encode computer-executable instructions, where the instructions perform some or all the steps of the above-mentioned methods. In an example, the process 700 may be implemented by the optimizer 120 of FIGS. 1, 2, and 3.

At block 702, a setpoint specified for each of the plurality of zones 106-1, 106-2, . . . and 106-N, may be monitored, for example, by the optimizer 120, over a period of time. In an example, the specified setpoint may refer to a target value for an operating parameter of a VAV unit, such as the VAV units 110-1, 110-2, . . . , and 110-N, configured to regulate the physical conditions in the respective zones 106-1, 106-2, . . . and 106-N. In an example, the specified setpoint may be defined by the occupants or the facility managers based on requirements for the physical conditions according to user demand in the respective zones 106-1, 106-2, . . . and 106-N. These physical conditions may include temperature, humidity, air flow, or other environmental parameters that may affect occupant comfort and productivity. The specified setpoint may vary depending on factors such as time of day, occupancy patterns, or specific activities occurring within each zone 106-1, 106-2, . . . and 106-N.

In an example, data corresponding to the specified setpoint for each of the zones 106-1, 106-2, . . . and 106-N, i.e., the specified setpoint data 320, set in the VAV unit 110-1, 110-2, . . . ., and 110-N of each zone 106-1, 106-2, . . . and 106-N may be received by the optimizer 120 from the BMS 116 over the network 118. In an alternative embodiment, the specified setpoint data 320 may be transmitted directly from the VAV units 110-1, 110-2, . . . , and 110-N to the optimizer 120.

At block 704, a zone where the specified setpoint for the VAV unit exceeds a predefined value by a predetermined threshold for a predetermined period of time may be identified, for example, by the optimizer 120, as the rogue zone. In an example, the predefined value may be based on a predetermined level of energy efficiency in operation of the AHU 108 coupled to the VAV units 110-1, 110-2, . . . , and 110-N of each of the plurality of zones 106-1, 106-2, . . . and 106-N. For example, if the predefined value for optimal energy efficiency is set at 22° C., and the predetermined threshold is 2° C., a zone with a setpoint of 25° C. maintained for a predetermined period, such as 2 hours, may be identified as a rogue zone.

At block 706, the current physical conditions of the rogue zone may be determined, for example, by the optimizer 120. In an example, determining the current physical conditions may include receiving the physical condition data 324 from the BMS 116. In an example, the BMS 116 may collect the physical condition data 324 from the sensors 114-1, 114-2, . . . , and 114-N installed in the zones 106-1, 106-2, . . . and 106-N. The physical condition data 324 may include various parameters such as temperature, humidity, occupancy status, and the like. The physical condition data 324 may provide the optimizer 120 with an understanding of the current physical conditions in the identified rogue zone, allowing the optimizer 120 to assess whether the current physical conditions of the rogue zone justify its current specified setpoint or if adjustments are necessary to improve energy efficiency while maintaining occupant comfort.

At block 708, a new setpoint for the rogue zone may be calculated, for example, by the optimizer 120. In an example, the new setpoint may lie between the specified setpoint and the predefined value and may be closer to the predefined value. For example, if the specified setpoint for the rogue zone is 26° C. and the predefined value for the optimal energy efficiency is 22° C., the optimizer 120 may calculate a new setpoint to be 24° C. In an example, in calculating the new setpoint, the optimizer 120 may consider various factors such as the current physical conditions of the rogue zone, occupancy patterns, time of day, and external weather conditions. The optimizer 120 may also apply constraints to ensure that the new setpoint does not compromise occupant comfort while still improving energy efficiency. For example, the new setpoint may be limited to a maximum change of 2° C. from the original specified setpoint to avoid sudden large temperature swings.

At block 710, the VAV unit of the rogue zone may be regulated in accordance with the new setpoint, for example, by the optimizer 120. In an example, the new setpoint determined by the optimizer 120 corresponding to the rogue zone may be provided to the AHU 108 either directly over the network 118 or through the BMS 116. Upon receiving the new setpoint, the AHU 108 may adjust its operation to supply conditioned air at a temperature that aligns with the new setpoint.

In an embodiment, the method 700 may further include prioritizing, based on the current physical conditions of the rogue zone, maintaining the specified setpoint for the rogue zone over adjusting the specified setpoint towards the predefined value. This prioritization may occur in situations where the current physical conditions of the rogue zone indicate a need to maintain the existing specified setpoint. For example, if the rogue zone 106-1 is a server room or a medical storage area with strict temperature requirements, the optimizer 120 may prioritize maintaining the specified setpoint even if it deviates from the predefined value.

Accordingly, the rogue zone may be brought back within acceptable operating parameters, improving overall efficiency of the HVAC system 104. By addressing the rogue zones, the optimizer 120 may reduce energy waste, improve occupant comfort, and extend the lifespan of HVAC system 104.

FIG. 8 illustrates a flow diagram of a process of regulating the VAV unit of the rogue zone, according to an example implementation of the present subject matter. The order in which the above-mentioned process is described is not intended to be construed as a limitation, and some of the described process blocks may be combined in a different order to implement the process, or an alternative process.

Furthermore, the above-mentioned process 800 may be implemented in a suitable hardware, computer-readable instructions, or combination thereof. The steps of such process may be performed by either a system under the instruction of machine executable instructions stored on a non-transitory computer readable medium or by dedicated hardware circuits, microcontrollers, or logic circuits. Herein, some examples are also intended to cover non-transitory computer readable medium, for example, digital data storage media, which are computer readable and encode computer-executable instructions, where the instructions perform some or all the steps of the above-mentioned methods. In an example, the process 800 may be implemented by the optimizer 120 of FIGS. 1, 2, and 3.

At block 802, a new setpoint for an AHU, such as the AHU 108, corresponding to the rogue zone may be determined, for example, by the optimizer 120, in response to identifying the rogue zone. In an example, the new setpoint may be a value between the specified setpoint of the rogue zone and the predefined value associated with a predetermined level of energy efficiency of the AHU 108. For example, if the specified setpoint for the rogue zone is 26° C. and the predefined value for optimal energy efficiency is 22° C., the optimizer 120 may determine a new setpoint of 24° C. for the AHU 108. As explained previously, the optimizer 120 may consider factors such as current physical conditions of the rogue zone, occupancy patterns, and capabilities of the AHU 108, and the like, in determining the new setpoint.

At block 804, a maximum rate of change for regulating the specified setpoint of the VAV unit of the rogue zone may be determined, for example, by the optimizer 120, based on a rated capacity of the VAV unit of the rogue zone. For example, if the VAV unit of the rogue zone has a rated capacity of 1000 cubic feet per minute (CFM), the maximum rate of change may be set to 0.5° C. per hour to ensure smooth temperature transitions and prevent strain on the VAV unit.

At block 806, the specified setpoint of the VAV unit of the rogue zone may be adjusted towards the new setpoint at the maximum rate of change of the VAV unit. In an example, adjusting the specified setpoint of the VAV unit of the rogue zone may include modifying damper position of the VAV unit of the rogue zone in accordance with the new setpoint of the AHU corresponding to the rogue zone. For example, if the new setpoint requires a decrease in temperature, the damper position of the VAV unit of the rogue zone may be adjusted to allow cooler air from the AHU 108 to enter the rogue zone. Conversely, if the new setpoint requires an increase in the temperature, the damper position of the VAV unit of the rogue zone may be adjusted to restrict the flow of cool air from the AHU 108. In an example, the adjustment process may be gradual, adhering to the maximum rate of change determined in block 804. For example, if the maximum rate of change is 0.5° C. per hour and the difference between the current setpoint and the new setpoint is 2° C., the optimizer 120 may take approximately 4 hours to fully implement the change. During this time, the optimizer 120 may continuously monitor the zone physical conditions and make fine adjustments to ensure optimal performance and energy efficiency.

At block 808, specified setpoints of zones other than the identified rogue zone may be adjusted in response to regulating the specified setpoint of the VAV unit of the rogue zone. In an example, a magnitude of adjustment in the specified setpoint for each of the other zones may be inversely proportional to a distance of the respective zones from the AHU 108. For example, if the setpoint of the rogue zone is adjusted by 2° C., a nearby zone may have its setpoint adjusted by 1.5° C., while a zone further away may only be adjusted by 0.5° C. This helps maintain overall balance of the HVAC system 104 and energy efficiency by accounting for thermal losses and airflow characteristics across different zones. The optimizer 120 may use factors such as duct length, air velocity, and thermal properties of the building to calculate these proportional adjustments, ensuring that all zones receive appropriate conditioning while addressing the needs of the rogue zone.

Thus, by regulating the specified setpoint of the rogue zone, it may be ensured that the overall HVAC system 104 operates more efficiently and effectively. This approach may help balance the thermal load across all zones, reduce energy consumption, and improve occupant comfort throughout the building. By addressing the needs of the rogue zone while considering the impact on other zones, the optimizer 102 may achieve a more harmonious and optimized operation, leading to reduced wear and tear on components of the HVAC system 104, lower operational costs, and a more sustainable use of energy resources.

FIG. 9 illustrates a computing environment 900 for optimizing energy usage in a premises, such as the premises 102, according to an example implementation of the present subject matter. In an example implementation, the computing environment 900 may include a computing device, such as the above-described optimizer 120. The computing environment 900 includes a processing resource 902 communicatively coupled to the non-transitory computer-readable medium 904 through a communication link 906.

In an example, the processing resource 902 may be a processor of the computing device, such as the processor 202 of the optimizer 120, that fetches and executes computer-readable instructions from the non-transitory computer-readable medium 904.

The non-transitory computer-readable medium 904 can be, for example, an internal memory device or an external memory device. In an example implementation, the communication link 906 may be a direct communication link, such as any memory read/write interface. In another example implementation, the communication link 906 may be an indirect communication link, such as a network interface. In such a case, the processing resource 902 can access the non-transitory computer-readable medium 904 through a network 912. The network 912 may be a single network or a combination of multiple networks and may use a variety of different communication protocols.

The processing resource 902 and the non-transitory computer-readable medium 904 may also be communicatively coupled to data sources 908. In an example implementation, the non-transitory computer-readable medium 904 includes executable instructions 910 for optimizing the energy usage in the premises 102. Optimization of the energy usage is performed to enhance overall efficiency of the HVAC system 104 installed in the premises 102 and reduce operational costs.

In an embodiment, the instructions 910 cause the processing resource 902 to determine a setpoint specified for each of a plurality of zones 106-1, 106-2, . . . , and 106-N in the premises 102. As explained previously, the specified setpoint may refer to a target value for an operating parameter of a VAV unit, such as the VAV units 110-1, 110-2, . . . , and 110-N, configured to regulate the physical conditions in the respective zones 106-1, 106-2, . . . , and 106-N. In an example, the specified setpoint for each of the plurality of zones 106-1, 106-2, . . . , and 106-N may be based on the requirements for the physical conditions according to user demand in the respective zones 106-1, 106-2, . . . , and 106-N.

In an embodiment, the instructions 910 may cause the processing resource 902 may compare the specified setpoint of each of the plurality of zones 106-1, 106-2, . . . , and 106-N to the predefined value. As explained previously, the predefined value may be based on an expected level of energy efficiency in operation of the AHU 108 coupled to the VAV unit 110-1, 110-2, . . . ., and 110-N of the zones 106-1, 106-2, . . . , and 106-N.

In an embodiment, based on the comparison, the instructions 910 may cause the processing resource 902 to identify a rogue zone, such as the rogue zone explained in reference to FIGS. 1-8, from the plurality of zones 106-1, 106-2, . . . , and 106-N. In an example, in the rogue zone, the specified setpoint exceeds the predefined value by the predetermined threshold.

In an embodiment, the instructions 910 may cause the processing resource 902 to determine the current physical conditions of the identified rogue zone.

In an embodiment, the instructions 910 may further cause the processing resource 902 to calculate a new setpoint for the identified rogue zone based on the current physical conditions. As explained previously, the new setpoint may have a value between the specified setpoint and the predefined value.

In an embodiment, the instructions 910 may cause the processing resource 902 to regulate the VAV unit of the rogue zone according to the new setpoint.

In an embodiment, as explained previously, the processing resource 902 may identify a zone to be the rogue zone when the specified setpoint for the zone exceeds the predefined value by the predetermined threshold for a predetermined period of time.

In an embodiment, to regulate the VAV unit of rogue zone according to the new setpoint, the processing resource 902 may change the specified setpoint of the VAV unit at a predefined maximum rate of change. In an embodiment, the maximum rate of change may be predefined based on a rated capacity of the VAV unit of the rogue zone.

In an embodiment, the instructions 910 may further cause the processing resource 902 to prioritize, based on the current physical conditions of the rogue zone, maintaining the specified setpoint for the rogue zone over regulating the VAV unit of the zone in accordance with the new setpoint.

In an embodiment, the instructions 910 may further cause the processing resource 902 to adjust specified setpoint of other zones of the plurality of zones 106-1, 106-2, . . . , and 106-N in response to regulating the VAV unit of the rogue zone. In an example, a magnitude of adjustment in the specified setpoint for each of the other zones may be inversely proportional to a distance of each respective zones from the AHU 108.

In an embodiment, the instructions 910 may cause the processing resource 902 to monitor the specified setpoint of each zone 106-1, 106-2, . . . , and 106-N over a period of time and identify a zone as a rogue zone when the specified setpoint of the zone exceeds the predefined value by the predetermined threshold for a predetermined period of time.

Thus, the present subject matter provides for optimizing energy usage in HVAC systems through setpoint adjustments. Although implementations of this energy optimization method have been described in language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as example implementations of energy optimization of the HVAC system through setpoint adjustments.

Claims

1. A method for optimizing energy usage in a premises, comprising:

determining a setpoint specified for each of a plurality of zones in the premises, the setpoint being a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones, wherein the setpoint for each of the plurality of zones is based on requirements for physical conditions according to user demand in the respective zones;

comparing the setpoint of each of the plurality of zones to a predefined value computed based on a predetermined level of energy efficiency in operation of an air handling unit (AHU) coupled to the VAV unit of each of the plurality of zones;

identifying at least one rogue zone from the plurality of zones, wherein in the at least one rogue zone, the specified setpoint exceeds the predefined value by a predetermined threshold;

determining current physical conditions of the at least one rogue zone; and

based on the current physical conditions, regulating the specified setpoint of the at least one rogue zone such that the specified setpoint is adjusted towards the predefined value.

2. The method of claim 1, wherein identifying the at least one rogue zone comprises determining that the specified setpoint for the zone has exceeded the predefined value by the predetermined threshold for a predetermined period of time.

3. The method of claim 1, wherein regulating the specified setpoint of the at least one rogue zone comprises changing the specified setpoint with a new setpoint that is closer to the predefined value.

4. The method of claim 3, wherein the specified setpoint is changed to the new setpoint at a maximum rate of change predefined for the at least one rogue zone.

5. The method of claim 4, wherein the maximum rate of change is predefined based on a rated capacity of a VAV unit of the at least one rogue zone.

6. The method of claim 1, further comprising prioritizing, based on the current physical conditions of the at least one rogue zone, maintaining the specified setpoint for the at least one rogue zone over adjusting the specified setpoint towards the predefined value.

7. The method of claim 1, further comprising adjusting specified setpoint of other zones of the plurality of zones in response to regulating the specified setpoint of the at least one rogue zone, wherein a magnitude of adjustment in the specified setpoint for each of the other zones is inversely proportional to a distance of the respective zones from the AHU.

8. An energy optimizer for optimizing energy usage in a premises, comprising:

a processor configured to: receive data corresponding to a setpoint specified for each of a plurality of zones in the premises, each specified setpoint being a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones; compare the specified setpoint of each of the plurality of zones to a predefined value associated with a predetermined level of energy efficiency for an air handling unit (AHU) coupled to the VAV units; identify at least one rogue zone from the plurality of zones, wherein the at least one rogue zone has a specified setpoint that exceeds the predefined value by a predetermined threshold; receive data corresponding to current physical condition of the at least one rogue zone; and adjust the specified setpoint of the at least one rogue zone to reduce a difference between the specified setpoint and the predefined value while maintaining the current physical conditions within a predetermined range of acceptable physical conditions.

9. The energy optimizer of claim 8, wherein the processor is further configured to:

monitor the specified setpoint of each zone over time; and

identify a zone as a rogue zone when the specified setpoint of the zone exceed the predefined value by the predetermined threshold for a predetermined period of time.

10. The energy optimizer of claim 8, wherein to adjust the specified setpoint of the at least one rogue zone, the processor is further configured to change the specified setpoint to a new setpoint that is closer to the predefined value.

11. The energy optimizer of claim 10, wherein the processor is configured to change the specified setpoint to the new setpoint at a maximum rate of change predefined for the at least one rogue zone.

12. The energy optimizer of claim 8, wherein the processor is configured to prioritize, based on the current physical conditions of the at least one rogue zone, maintaining the specified setpoint for the at least one rogue zone over reducing the difference between the specified setpoint and the predefined value.

13. The energy optimizer of claim 8, wherein the processor is further configured to adjust the specified setpoint of other zones of the plurality of zones in response to adjustment of the specified setpoint of the at least one rogue zone, wherein a magnitude of adjustment in the specified setpoint for each of the other zones is inversely proportional to a distance of the respective zone from the AHU.

14. A non-transitory computer-readable medium comprising instructions executable by a processing resource to:

determine a setpoint specified for each of a plurality of zones in a premises, the setpoint being a target value for an operating parameter of a variable air volume (VAV) unit configured to regulate physical conditions in the respective zones, wherein the specified setpoint for each of the plurality of zones is based on requirements for physical conditions according to user demand in the respective zones;

compare the specified setpoint of each of the plurality of zones to a predefined value computed based on a predetermined level of energy efficiency in operation of an air handling unit (AHU) coupled to the VAV unit of each of the plurality of zones;

identify at least one rogue zone from the plurality of zones, wherein in the at least one rogue zone, the specified setpoint exceeds the predefined value by a predetermined threshold;

determine current physical conditions of the at least one rogue zone;

calculate, based on the current physical conditions of the at least one rogue zone, a new setpoint for the at least one rogue zone, wherein the new setpoint has a value between the specified setpoint and the predefined value; and

regulate the VAV unit of the at least one rogue zone according to the new setpoint.

15. The non-transitory computer-readable medium of claim 14, wherein to identify the at least one rogue zone, the processing is resource to determine that the specified setpoint for a zone has exceeded the predefined value by the predetermined threshold for a predetermined period of time.

16. The non-transitory computer-readable medium of claim 14, wherein to regulate the VAV unit of the at least one rogue zone according to the new setpoint, the processing resource is to change the specified setpoint at a predefined maximum rate of change.

17. The non-transitory computer-readable medium of claim 16, wherein the maximum rate of change is predefined based on a rated capacity of the VAV unit of the at least one rogue zone.

18. The non-transitory computer-readable medium of claim 14, further comprising instructions executable by the processing resource to prioritize, based on the current physical conditions of the at least one rogue zone, maintaining the specified setpoint for the at least one rogue zone over regulating the VAV unit of the at least one rogue zone in accordance with the new setpoint.

19. The non-transitory computer-readable medium of claim 14, further comprising instructions executable by the processing resource to adjust specified setpoint of other zones of the plurality of zones in response to regulating the VAV unit of the at least one rogue zone, wherein a magnitude of adjustment in the specified setpoint for each of the other zones is inversely proportional to a distance of each respective zones from the AHU.

20. The non-transitory computer-readable medium of claim 14, further comprising instructions executable by the processing resource to:

monitor the specified setpoint of each zone over time; and

identify a zone as a rogue zone when the specified setpoint of the zone exceeds the predefined value by the predetermined threshold for a predetermined period of time.