Abstract: A design optimization system (100) and a method for achieving design optimization for cooling are described herein. According to an implementation, the method includes obtaining an inlet value of at least one flow parameter at a small geometric length scale and determining an outlet value of the at least one flow parameter at the small geometric length scale based on the inlet value. Further, a flow behavior is modeled based on the inlet and outlet values of the at least one flow parameter, and based on the modeled flow behavior an optimized design for cooling is ascertained.

Abstract: Disclosed is a system and method for facilitating optimizing cooling efficiency of a data center. The method may comprise receiving a layout of the data center. The method may comprise computing co-ordinates of each equipment of a plurality of equipments associated with the data center. Further, the method may comprise segregating the layout into a plurality of cells. The method may comprise capturing preliminary data associated with the data center. Further, the method may comprise determining a state value of the data center based upon the preliminary data. The method may comprise capturing CFD data and, selectively, thermal assessment data. Further, the method may comprise facilitating the optimization of the cooling efficiency of the data center by using an external analysis tool capable of performing Computational Fluid Dynamics (CFD) analysis or thermal assessment followed by the Computational Fluid Dynamics (CFD) analysis using the CFD data and the thermal assessment data.

Abstract: A system and method for optimizing energy consumption in a plurality of air handling units (AHUs) in a zone is provided. The system comprising a zone thermal unit that is configured to obtain a first set of input parameters including an internal heat gains, a surface convective loads, an intra-zone mixing, a supply air temperature, a second set of input parameters including internal moisture gains, a supply humidity ratio, and a third set of input parameters including an air contaminant concentration and an ambient contaminant concentration of the AHUs and generates a first set of output parameters including a zone temperature, a humidity ratio and an air concentration. The system further includes an optimizer that is configured to generate a second set of output parameters including an optimum combination of AHU flow rates for the AHUs based on at least one of the first set of output parameters.

Abstract: A technique for energy sample forecasting of heating, venting and air conditioning-refrigeration (HVAC-R) systems is disclosed. In an example, a first expected energy sample of a HVAC-R system at a first time period is forecasted by modelling actual energy samples of the HVAC-R system at previous time periods using a statistically-based seasonal-autoregressive integrated moving average (SARIMA) model. Further, an anomaly is detected at the first time period when deviation between the first expected energy sample and an actual energy sample at the first time period is greater than a dynamic context sensitive threshold. Also, an expected energy sample at next time period is forecasted by modelling a second expected energy sample of the HVAC-R system at the first time period using the statistically-based SARIMA model upon detecting anomaly. The second expected energy sample is forecasted by modelling the actual energy samples at the previous time periods using a physical model.

Abstract: Disclosed is a method for real-time prediction of thermal-insights for a heat dissipating device in a data center cooled by one or more cooling units. The method uses a concept of influence mass fractions in conjunction with proper orthogonal decomposition (POD) based reduced order model. It may be understood that, the influence mass fractions may be computed by performing a fixed number of CFD simulations based on mass flow rates of the one or more cooling units. The method further facilitates to identify a set of reference scenarios for a given range of operational parameters of the one or more cooling units impacting the heat dissipating device. The set of reference scenarios may then be provided to the POD in order to predict the thermal-insights of the data center such as a temperature, mass flow rate, and insights into thermal influence of air sources on the heat dissipating device.

Abstract: Described herein, are methods and systems for locating a leak in a water distribution network. According to an implementation, a leak situation in the water distribution network is detected based on a flow difference value between an actual flow value and a predicted flow value of an inlet flow meter of the water distribution network at at least one time interval. Leak signature values of demand nodes in the water distribution network at the at least one time interval are determined. A leak signature value of a respective demand node at a respective time interval is determined based on centrality metrics, the predicted flow value at the respective time interval, and static physical properties related to the water distribution network. At least one possible leak node is identified based on the flow difference value and the leak signature values of the demand nodes at the at least one time interval.

Abstract: Disclosed is a system and method for optimizing cooling efficiency of a data center is disclosed. The system may comprise an importing module, a Computational fluid dynamics (CFD) modeling module, a scope determination module, a metrics computation module, an identification module and a recommendation module. The importing module may be configured to import data associated to the data center. The CFD modeling module may be configured to leverage an external CFD Analysis tool in order to develop a CFD model of the data center. The scope determination module may be configured to determine a scope for optimizing the cooling efficiency of the data center. The metrics computation module may be configured to compute metrics based upon the data. The identification module may be configured to identify inefficiency and a cause producing the inefficiency. The recommendation module may be configured to facilitate optimizing cooling efficiency of the data center.

Abstract: Disclosed is a system for facilitating homogenized distribution of airflow, generated from one or more cooling units, in a data center. The virtual data center creation module for creating a virtual environment of the data center. The airflow channel determination module for dividing the architectural layout into one or more partitions to determine one or more airflow channels corresponding to each of the one or more partitions. The CRAC placement module for positioning the at least one cooling unit in an airflow channel, of the one or more airflow channels, in a manner such that the airflow moves in a streamline manner within the airflow channel. The vein determination module for determining position of each of a plurality of veins inside the airflow channel. The vein shape determination module for determining shape of each vein that facilitates the homogenized distribution of the airflow.

Abstract: The application provides a method and system for real time monitoring and prediction of temperatures in a data center for effective thermal management. Further, the invention provides a method and system for analyzing and display of monitored and predicted temperatures for obtaining complete temperature profile of the data center.

Abstract: A method and system are provided for determining at least one combined forecast value of non-conventional energy resources. An Input/output Interface receives an adaptively selected historical dataset and a current dataset from one or more predictive forecast models and/or measurements. An adaptive forecast module generates one or more variants of machine learning models to model the performance of the one or more predictive forecast models by training the one or more variants of machine learning models on the historical dataset. The adaptive forecast module correlates the current dataset with the historical dataset to adaptively obtain a filtered historical dataset. The adaptive forecast module evaluates the one or more variants of machine learning models on the filtered historical dataset. The adaptive forecast module derives a statistical model to determine the at least one combined forecast value by combining outputs obtained based on the evaluation.

Abstract: A method and system is disclosed for maintaining Power Usage Effectiveness (PUE) of a new data center constant or within narrow range around efficient level during ramping up stage of the data center. The method comprises of capturing a plurality of design and operational parameters of the data center, computing an efficient design for the data center at full occupancy, and maintaining the Power Usage Effectiveness constant or within narrow range around efficient level at a current occupancy during a ramp up period of the data center.

Abstract: The subject matter described herein relates to a system and a method for generation of energy consumption profiles corresponding to a plurality of computing systems. For each of the plurality of the computing systems, a plurality of consumption parameters from at least one measurement device is received. The consumption parameters include a processor utilization parameter and an energy consumption parameter. Further, a normalization factor corresponding to each of the plurality of the computing systems is identified. Based on the normalization factor, the processor utilization parameter is normalized. Based on the normalized processor utilization parameter and the energy consumption parameter, the energy consumption profile is generated. The energy consumption profile is indicative of energy efficiency of the plurality of the computing systems.

Abstract: A method and system is provided for determining a viable containment design of a data center and systematic implementation of the determined containment design in the data center. Particularly, disclosed is a method and system for collecting data pertaining to the design and operational parameters of the data center; enabling various containment design options using CFD based methodology; and providing recommendations for a viable containment design and assisting systematic implementation of the recommendations of in the data center following an iterative procedure.

Abstract: The invention provides a method and system for quantitative determination of cooling characteristics of a data center by calculating thermal influence indices. The invention further provides a method and system for providing effective thermal management in a data center using quantitative determination of cooling characteristics of a data center.

Abstract: A design optimization system (100) and a method for achieving design optimization for cooling are described herein. According to an implementation, the method includes obtaining an inlet value of at least one flow parameter at a small geometric length scale and determining an outlet value of the at least one flow parameter at the small geometric length scale based on the inlet value. Further, a flow behaviour is modeled based on the inlet and outlet values of the at least one flow parameter, and based on the modeled flow behaviour an optimized design for cooling is ascertained.

Abstract: The subject matter described herein is directed to a power monitoring system for managing power in a data center. In one embodiment, the power monitoring system includes: at least one processor, a memory coupled to the at least one processor, wherein the memory includes, a computation module configured to compute at least one of peak power consumption and current power consumption of each power distribution point of a power distribution unit and an analysis module configured to identify the power distribution points which are overloaded or are underutilized based on a policy data.

Abstract: A method and system are provided for determining at least one combined forecast value of non-conventional energy resources. An Input/output Interface receives an adaptively selected historical dataset and a current dataset from one or more predictive forecast models and/or measurements. An adaptive forecast module generates one or more variants of machine learning models to model the performance of the one or more predictive forecast models by training the one or more variants of machine learning models on the historical dataset. The adaptive forecast module correlates the current dataset with the historical dataset to adaptively obtain a filtered historical dataset. The adaptive forecast module evaluates the one or more variants of machine learning models on the filtered historical dataset. The adaptive forecast module derives a statistical model to determine the at least one combined forecast value by combining outputs obtained based on the evaluation.

Abstract: The subject matter described herein relates to a system and a method for generation of energy consumption profiles corresponding to a plurality of computing systems. For each of the plurality of the computing systems, a plurality of consumption parameters from at least one measurement device is received. The consumption parameters include a processor utilization parameter and an energy consumption parameter. Further, a normalization factor corresponding to each of the plurality of the computing systems is identified. Based on the normalization factor, the processor utilization parameter is normalized. Based on the normalized processor utilization parameter and the energy consumption parameter, the energy consumption profile is generated. The energy consumption profile is indicative of energy efficiency of the plurality of the computing systems.

Abstract: The application provides a method and system for real time monitoring and prediction of temperatures in a data center for effective thermal management. Further, the invention provides a method and system for analyzing and display of monitored and predicted temperatures for obtaining complete temperature profile of the data center.

Abstract: The invention provides a method and system for quantitative determination of cooling characteristics of a data center by calculating thermal influence indices. The invention further provides a method and system for providing effective thermal management in a data center using quantitative determination of cooling characteristics of a data center.