Abstract: Embodiments relate to a method for predicting power generation and remaining useful life to predict operational soundness of a power plant and a system for performing the same, the method including acquiring sensing data from each of a plurality of sensors included in a plurality of systems in the power plant, outputting each of a predicted power generation and a predicted remaining useful life from a measurement value in sensing data of an input sensor through a pre-trained prediction model, assessing the operational soundness in aspect of the power generation and the remaining useful life using a prediction result and a current result in each aspect, and determining the operational soundness of the system based on prediction uncertainty and an assessment result in aspect of the power generation and the remaining useful life.

Abstract: A method for controlling power consumption includes receiving a flexibility request from an electrical utility and discovering energy relevant devices in a building. The energy relevant devices include electrical loads and alternative energy sources. Power requirements are predicted from an electrical utility for the loads, the prediction takes into account available power from the alternative power sources. Power set points are determined for the energy relevant devices based on the prediction. The power set points meet the flexibility request. The energy relevant devices are directed to operate at the power set points. A building energy management system is also disclosed.

Abstract: A method for handling surplus or deficit of energy in local energy systems (30) is presented. The method comprising; determining an accumulator status based on data pertaining to an accumulator (20) of a moveable device (10); determining energy status of each of a plurality of local energy systems (30) based on data pertaining to the respective local energy system 30; scoring, based on the determined accumulator status and the determined energy statuses, each of the local energy systems (30); determining, based on the respective scores of each of the plurality of local energy systems (30), a local energy system (30), among the plurality of local energy systems (30), to which the moveable device (10) is to be directed. Also a server (40) configured to handling surplus or deficit of energy in local energy systems is presented.

Abstract: An embodiment establishes a knowledge base based at least in part on sensor data received from a network. The embodiment generates a predicted performance parameter for a designated entity of the network using a first machine learning algorithm. The embodiment compares the predicted performance parameter to an actual performance parameter and determines whether the actual performance parameter exceeds a threshold difference from the predicted performance parameter. The embodiment generates, responsive to determining that the threshold difference is exceeded, incentive data using a second machine learning algorithm, where the incentive data is representative of an action selected by the second machine learning algorithm using an iterative optimization process, and where the iterative optimization process comprises performing the action and determining that the actual performance parameter approaches the threshold value in response to the action.

Abstract: The actual performance information classify part derives a classification result of an actual performance information on electric power demand, by a classification setting information, from an environment information and a date attribute information which is correlated with each of the electric power demands which is included in an actual performance information on electric power demand. The prediction information calculate part derives a classification result of a prediction target day, using the date attribute information of the prediction target day, which is a day to conduct a prediction, and the environment information which is measured before a start of the prediction of a prediction target day, and in addition, predicts an electric power demand of a prediction target day, based on the electric power demand of the actual performance information on electric power demand, which corresponds to the classification result of the prediction target day.

Abstract: Systems and methods may coordinate and provide bidirectional energy transfer events between electrified vehicles and households or other structures, such as for supporting transient loads associated with the households/structures, for example. Vehicle information, driving habit information, and household information may be leveraged for providing enhanced transient load capability controls that permit increased appliance usage without increasing energy costs. The proposed systems/methods may particularly allow for bidirectional energy transfer support of high load appliances for increasing a user's comfort, pleasure, and convenience.

Abstract: The disclosure provides a distributed dispatch method for ubiquitous power Internet of Things based on a transition matrix. The ubiquitous power Internet of Things includes generators. The method includes: S1, setting a marginal cost function of each of the generators, and extracting key cost parameters in the marginal cost function; S2, establishing an optimization model based on the key cost parameters of each of the generators and a communication topology of the ubiquitous power Internet of Things, and solving the optimization model to obtain an optimized transition matrix; and S3, generating a plan of a power output of each of the generators based on the optimized transition matrix and a distributed dispatch protocol to perform a distributed dispatch.

Abstract: Provided is a power supply system configured to supply AC power to a building. The power supply system includes a discharge assembly which is connectable to a discharge port provided in a vehicle. The discharge assembly includes a first end which receives electric power from the discharge port connected thereto, and a second end which outputs AC power. The second end of the discharge assembly is connected to the building by a single-phase three-line wiring.

Abstract: Disclosed is a centralized cloud energy storage system for massive and distributed users and a transaction settlement method thereof, a storage medium, and a terminal. The system includes: a centralized energy storage facility invested and operated by a cloud energy storage service provider; the massive and distributed users; and a power network and a user energy management system connecting the centralized energy storage facility with the massive and distributed users. A user sends a charging and discharging request to the cloud energy storage service provider through the user energy management system, and the cloud energy storage service provider issues a charging and discharging instruction to the centralized cloud energy storage system.

Abstract: A system and method for managing and distributing an electrical power system is provided. In one embodiment, the system and method comprise at least one powered device that receives electrical power from an electrical power system utilizing multiple energy sources. Structure and devices are provided within the system to command, regulate, monitor, and transmit power to a device or devices in an efficient, reliable manner based on resource availability, energy cost, and environmental factors. The system selects and manages the resources to optimize the energy output to the device(s) to achieve the specific requirements in resiliency, cost, and the environmental impact of the application.

Abstract: Provided are a method and apparatus for evaluating a degree of frequency regulation urgency of a generator set, a power system and a storage medium.

Abstract: A method for tracking non-homogeneous products on a shelf comprises monitoring weight measurement data points corresponding to the weight of the shelf and the products arranged thereupon, determining a set of weight-event parameters of a weight event, such as product identification and an action taken with respect to the product, and at least one of recording information about the results and displaying information about the results. A system for tracking non-homogeneous products on a shelf comprises processors for carrying out stored program instructions for carrying out the steps of the method.

Abstract: Systems, methods, and related technologies for self-training classification are described. In certain aspects, a plurality of device classification methods with associated models are accessed. Each of the classification methods have an associated reliability level. The models of classification methods with a higher reliability level than other classifications methods are used to train the models associated with lower reliability level. The trained models and associated classification methods are thus improved.

Abstract: The disclosed method reconstructs a topology of an electrical distribution network. An ohmic matrix model is generated as a function of consumption measurements provided by smart meters in the network. A tree table of nodes to which the smart meters are connected is defined. A branch in exploration is defined in the table and the nodes of the branch meeting preestablished relations are entered in the table as a function of connection values derived from resistive quantities in the matrix model. One of the relations determines a junction of the branch in exploration with a branch already explored connectable to a root to which a distribution transformer of the distribution network is connected. The topology is reconstructed by iteratively proceeding with sequences of decreasing values derived from the resistive quantities.

Abstract: A liquefaction apparatus that automatically adjusts the load on the liquefaction apparatus correspondingly with an upper limit value of contracted power in different time slots, and which is capable of maximizing the amount of liquefied product produced and of achieving optimum operating efficiency is provided.

Abstract: Provided are an apparatus and a method for generating an alternative routine, the method comprising monitoring a first routine comprising at least one activity representing at least one interaction of a user with one or more IoT devices, determining semantic information associated with the at least one activity, and generating at least one second routine comprising one or more activities corresponding to the at least one activity based on the semantic information associated with the at least one activity.

Abstract: This disclosure describes techniques that enable a supplemental voltage to be delivered to a Remote Radio Unit (RRU) to compensate for a voltage loss that occurs between a primary Direct Current (DC) power source and the RRU. A supplemental voltage controller is described that captures current environmental metadata associated with an operation of the RRU and calculates an RRU voltage at the RRU. In doing so, the supplemental voltage controller may generate a supplemental voltage control signal that supplements the RRU with a supplemental DC voltage.

Abstract: A power grid control device of the present invention may comprise: a grid input interface for receiving an input of information on an operation state of a power grid; a grid output interface for outputting a signal for operating the power grid; a communication interface for performing data communication with a remote device; a component unit in which a plurality of software components for performing individual functions required for operating the power grid are stored; and a processing module for executing the components to process a work required for the operation of the power grid.

Abstract: The embodiments of the present disclosure provide methods and systems for natural gas data computation outside a gas IoT based on energy measuring, including establishing the gas IoT. The object platform obtains consumed gas volume data and location data of the smart gas meter as first data and second data, and sending them to the management platform through the sensor network platform. The management platform generates consumed gas preprocessing data based on the first data and the second data, and generates energy measurement data after performing the computation outside the gas IoT on the consumed gas preprocessing data by the cloud platform outside the gas IoT. The management platform sends the energy measurement data to the user platform configured in a regional pipeline network center through the service platform. The user platform performs gas energy measurement of the smart gas meter based on the energy measurement data.

Abstract: A power calculation apparatus calculates an amount of power suppliable and demandable between a battery and a power grid. The power calculation apparatus includes a microprocessor and a memory connected to the microprocessor. The microprocessor is configured to perform: predicting the amount of power suppliable and demandable between the battery and the power grid at a predetermined point in time to calculate a prediction value of the amount of power suppliable and demandable; and switching a calculation logic to be applied to a calculation of the prediction value, based on a length of duration from a present point in time to the predetermined point in time.

Abstract: Embodiments generate machine learning predictions to discover target device energy usage. One or more trained machine learning models configured to discover target device energy usage from source location energy usage can be stored. Multiple instances of source location energy usage over a period of time can be received for a given source location. Using the trained machine learning model, multiple discovery predictions for the received instances of source location energy usage can be generated, the discovery predictions comprising a prediction about a presence of target device energy usage within the instances of source location energy usage. And based on the multiple discovery predictions, an overall prediction about a presence of target device energy usage within the given source location's energy usage over the period of time can be generated.

Abstract: AI-assisted Connected Home systems for improving power efficiency at homes and offices are described. The system may perform operations including: receiving, from each of a plurality of power receptacles, power usage information of an electrical device attached to the power receptacle; determining, for each of the plurality of power receptacles, a plurality of power usage metrics of the power receptacle based on the power usage information; feeding the plurality of power usage metrics into a machine learning model to obtain a priority of the electrical device attached to the power receptacle, wherein the priority is one of a plurality of pre-configured priorities; obtaining a power management signal; and transmitting a plurality of control signals to the plurality of power receptacles based on the power management signal and respective priorities of the plurality of electrical devices attached to the plurality of power receptacles.

Abstract: Techniques are described for implementing an automated control system to control operations of a target physical system, such as production of electrical power in an electrical grid. The techniques may include determining how much electrical power for each of multiple producers to supply for each of a series of time periods, such as to satisfy projected demand for that time period while maximizing one or more indicated goals, and initiating corresponding control actions. The techniques may further include repeatedly performing automated modifications to the control system's ongoing operations to improve the target system's functionality, by using reinforcement learning to iteratively optimize particles generated for a time period that represent different state information within the target system, to learn one or more possible solutions for satisfying projected electrical power load during that time period while best meeting the one or more defined goals.

Abstract: A total energy management system for high energy efficiency of a logistics center includes: an energy management system (EMS) server for collecting real-time data associated with the logistics center, wherein the EMS server processes the real-time data and generates at least one of real-time temperature data, real-time humidity data, renewable energy data, and electric power data of the logistics center; and an artificial intelligence (AI) server for outputting at least one of temperature mapping data, defrosting time determination data, and an energy operation guide in the logistics center based on at least one of the real-time temperature data, the real-time humidity data, the renewable energy data, and the electric power data received from the EMS server, wherein the EMS server switches between a plurality of management modes having different operating conditions for the logistics center based on at least one of the temperature mapping data, the defrosting time determination data, and the energy operation

Abstract: The present disclosure provides methods, systems, and devices for controlling electric vehicle charging across multiple customers and multiple fleets of electric vehicles. These methods, systems, and devices may implement machine learning to determine distinct charging strategies for a plurality of charging depots. Scheduling methods systems, and devices disclosed herein do not require fixed electric vehicle arrival times but may instead update charging strategies in real time based on changes in a state of a system.

Abstract: Disclosed is a service operation method for managing energy data for each tenant. More particularly, the service operation method monitors energy consumption consumed in a specific space that a tenant manager desires to manage using an individualized energy management service user interface (UI) according to a service development/production environment set by a manager terminal and visualizes a status of use of energy for each specific space from a monitoring result.

Abstract: Architectures, apparatuses, methods, systems, and techniques for controlling electrical power distribution network are disclosed. Embodiment distributed, hierarchical controls including layered locational energy service control variables may be utilized to determine and control the provision of energy services, including real power, reactive power (VAR), and capacity reserves, by DERs in a distribution network. In a first ex-ante iteration a simulation may be performed to calculate a set of subnetwork-specific control variables based on subnetwork locational energy service prices and a plurality of sets of DER-specific control variables based on DER locational energy service prices. A second ex-ante iteration calculates a set of actual subnetwork-specific control variables based on subnetwork locational energy service prices and a plurality of sets of actual DER specific control variables based on DER locational energy service prices.

Abstract: Disclosed are systems and methods for utilizing a unique elastic command and control architecture to incorporate certain resiliency qualities in power grid management and outage mitigation.

Abstract: Provided are techniques for predictively generating demand response (DR) events based on grid operations and faults, based on optimization and self-learning routines. The techniques include obtaining grid status information, and determining a fault condition based at least in part on the grid status information. The techniques also include generating a DR event based at least in part on the fault condition, and responsive to generating the DR event, transmitting a notification of the DR event.

Abstract: A system for completing a well, including a generator, and a plurality of electric load components, each electric load component powered by the generator. The system further includes a load shedding control panel that monitors the generator and, if the generator loses functionality, is capable of deactivating one or more of the plurality of electric load components to reduce the electric load.

Abstract: The present disclosure provides an adaptive energy storage operating system that is programmed or otherwise configured to operate and optimize various types of energy storage devices.

Abstract: In some embodiments, devices, systems, and methods herein may be used to operate an environmental control system in order to improve environmental satisfaction and/or cognitive function for one or more occupants or groups of occupants of an indoor environment. By some approaches, the devices, systems, and methods described herein may be employed by occupants, managers or owners of indoor environments to improve satisfaction with lighting and/or improve the performance of various executive functions for one or more occupants of an indoor environment. In some embodiments, the devices, systems, and methods described herein may be used to adjust various lighting parameters in an indoor environment, for example, lighting parameters that are indicative of access to natural light in the indoor environment.

Abstract: An EMS includes a control unit that controls a power generation facility and a power adjustment unit that adjusts an amount of supply of supply power. The control unit includes: a reverse power flow suppression process determination unit; a priority decision unit that decides a priority for adjusting an amount of power generated for the two power generation devices of the power generation facility on the basis of a predicted degree of fluctuation in load power; and a device control unit that controls the power generation facility such that the amount of power generated is adjusted in descending order of the priority decided by the priority decision unit when the reverse power flow suppression process determination unit determines to reduce the amount of power generated by the power generation facility.

Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

Abstract: A hierarchical control method for an island power grid energy storage system for increasing new energy generation fluctuation is disclosed. The method includes implementing a rolling dispatch method based on an idea of model predictive control; comprehensively considering a response capability of the energy storage system to grid-wide economic dispatch instructions and life loss of energy storage lithium batteries, and constructing an objective function of an intraday control model of the energy storage system with economic optimization; and constructing, on a basis of satisfying the objective function of the intraday control model, a real-time control model of the energy storage system and solving the model, and determining charge and discharge plans of a lithium battery energy storage system and a supercapacitor energy storage system.

Abstract: A system for controlling air flow in an air handling unit having an air mover is provided. The system includes a first and a second sensing device, each receiving a first input indicative of electric power and a second input indicative of properties of air, respectively. The system further includes a processing unit to determine heat generated from a motor of the air mover based on the first input, determine density of air based on the heat generated from the motor based on the second input, and determine an actual air flow rate based on the density of the air, a speed of the motor, and dimensional characteristics of the air handling unit. Further, the speed of the motor is controlled when the actual air flow rate is different from a target air flow rate.

Abstract: The present disclosure relates to an apparatus for diagnosing a state of a photovoltaic device, a building Integrated Photovoltaics (BIPV) device, etc., and more particularly to an apparatus for diagnosing photovoltaic power generation, which diagnoses a state of the specific photovoltaic device by comparing the difference in power generation between grouped photovoltaic devices through analysis of power generation for the same period in the past through machine learning, etc., wherein the apparatus processes power generation information, which is collected from the photovoltaic devices, based on failure history and maintenance and repair information of each photovoltaic device and performs precise grouping by minimizing error information regarding a power generation trend based on information such as regional weather information and environment information for a region where each photovoltaic device is located, so that a power generation trend can be analyzed with improved accuracy of analysis of state.

Abstract: A power regulation and control method, apparatus and device, and a readable storage medium.

Abstract: A power management apparatus and a housing complex combination method for trading surplus power for a housing are provided. Influencing factors in analyzing a consumption pattern of an individual housing and various correlations between the influencing factors are analyzed, and an optimal sustainable housing complex through supply of new renewable energy is formed.

Abstract: A smart meter system is described for managing demand side electrical transactions with shifted demand in a smart grid. The smart meter controller uses non-cooperative game theoretic analysis for managing multi-periodic smart grid shifted demand. The problems of user based electricity demand, production, storage, and sales of energy to providers are addressed. The smart meter system described is used in the control of Home-Area-Network (HAN) or Wide-Area-Network (WAN) demand response management (DRM).

Abstract: Techniques are provided for improving the environmental sustainability of a networking device and/or a networking system. In one example, a sustainability server obtains power consumption data of a networking device on a per-plane basis. Based on the power consumption data, the sustainability server computes an individual sustainability score that indicates a level of environmental sustainability of the networking device. The sustainability server further analyzes the power consumption data on the per-plane basis. In response to analyzing the power consumption data on the per-plane basis, the sustainability server provides a recommendation to implement a change to a configuration or operating parameter of the networking device, or to a networking system that includes the networking device, to improve the individual sustainability score.

Abstract: The embodiments disclosed in this document are directed to an AI-enabled microgrid and DER planning platform that uses AI methods and takes into account cost calculations, emission calculations, technology investments and operation. In an embodiment, the computing platform is deployed on a network (cloud computing platform) that can be accessed by a variety of stakeholders (e.g., investors, technology vendors, energy providers, regulatory authorities). In an embodiment, the planning platform implements machine learning (e.g., neural networks) to estimate various planning parameters, where the neural networks are trained on observed data from real-world microgrid/minigrid and DER projects.

Abstract: Provided is a highly reliable technology for optimizing an action for controlling an environment in a target space.

Abstract: Systems and methods for improving load energy forecasting in the presence of distributed energy resources in which a revised load forecast is calculated based on forecasted meteorological conditions data, forecasted wind and solar energy, forecasted load data, time data and time-series variables determined based on an analysis of the historical data. In exemplary embodiments, the revised load forecast is provided to energy management computer systems to enable appropriate levels of generation of conventional and renewable energy generation within the electric power grid.

Abstract: Systems and methods for coordinating distributed energy storage in accordance with embodiments of the invention are illustrated. One embodiment includes a power distribution network, including a set of nodes, wherein a node includes a controllable load, an uncontrollable load, and a local controller, a substation connected to each node in the set of nodes by a set of distribution lines, and a global controller including a processor, a memory, and a communications device, wherein the global controller obtains load parameters from at least one node, calculates coordination parameters for each node based on the obtained load parameters, and asynchronously provides the coordination parameters to each of the nodes in the set of nodes, and wherein each node independently obtains coordination parameters, and controls the operation of its controllable load using the local controller based on the coordination parameters and a local load profile describing at least the uncontrollable load.

Abstract: The present invention provides a system of providing a control service for a TVWS-based hybrid energy storage apparatus in which DC power generated based on solar power is charged into a hybrid solar energy storage device including a plurality of supercapacitors, batteries, supercapacitor modules and battery modules, and the power is supplied to a plurality of loads using the charged power.

Abstract: Examples disclosed herein relate to an energy device including a memory, one or more processors, a transceiver, a display, and a dashboard. The memory includes one or more energy modules. The one or more processors are configured to communicate via the transceiver with one or more energy devices. The display is configured to display a dashboard of energy options based on one or more signals received from the one or more processors.

Abstract: A supply and demand adjustment monitoring device of a power grid includes an output actual power value database that stores an output actual power value of at least one generator, an output power command value database that stores an output power command value issued to the generator, a planned adjustment capacity value database that stores a planned adjustment capacity value for the generator, and an adjustment capacity evaluation unit that evaluates an adjustment capacity based on the output actual power value, the output power command value, and the planned adjustment capacity value.

Abstract: A method for managing energy in a controllable device includes determining a plurality of future energy prices, where each of the future energy prices represents a price of a unit of energy over a predetermined time period, determining a duration to charge a controllable device, correlating the duration to charge the controllable device with at least one predetermined time period based at least in part on the price per unit energy over the at least one predetermined time period, and directing a utility to charge the controllable device at the at least one predetermined time period.

Abstract: A controller for equipment that operate to provide heating or cooling to a building or campus includes a processing circuit configured to obtain utility rate data indicating a price of resources consumed by the equipment to serve energy loads of the building or campus, obtain an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the resources consumed by the equipment, determine a relationship between resource consumption and load production of the equipment, optimize the objective function over the optimization subject to a constraint based on the relationship between the resource consumption and the load production of the equipment to determine a distribution of the load production across the equipment, and operate the equipment to achieve the distribution.