The present invention relates to system and method for providing near real-time DR events and price signals to the customer end-points to optimally manage the available DR resources. The system utilizes bottom up load forecasting for accurate individualized forecasts for customer loads in the presence of dynamic pricing signals. For better efficiency and reliability of grid operation the system utilizes advanced machine learning and robust optimization techniques for real-time and “personalized” DR-offer dispatch.

A method includes selectably controlling a power supply from a renewable energy source based power system and an energy storage device charged thereby and/or an Alternating Current (AC) power system to a computing system including one or more data processing device(s) using an electronic control system, and continuously updating, through a computing power management system associated with the electronic control system, a parameter of operation of the energy storage device in response to analyzing data pertinent to prior energy usage/production and/or predicted energy usage/production relevant to execution of a high computational workload through the one or more data processing device(s). The method also includes optimizing the power supply from the energy storage device to the one or more data processing device(s) using the computing power management system based on the continuously updated parameter of operation of the energy storage device.

This invention provides a system and process to optimize photovoltaic (PV), grid, and other electricity in powering an electric water heater. The system comprises a photovoltaic (PV) controller coupled to a plurality of power input sources and heating elements wherein the heating elements immersed in an electric immersion heater water tank. The PV controller is further configured with control circuitry having an operating efficiency routine calculating optimal use cases from a variety of installation parameters and learned parameters to determine the appropriate power input source and switch between sources accordingly.

A method, apparatus and system are provided to coordinate, manage, and optimize the electrical loads across all subsystems behind a given meter. In this approach, which is sometimes referred to herein as intelligent demand optimization, the optimized capacity needs of each subsystem are assessed in real-time, along with the available capacity of the meter and the current billing period peak. Power is then distributed dynamically to each subsystem to reduce the overall peak.

A voltage stability monitoring device and a method capable of obtaining information of voltage stability that can be served to practical use within a range of assumed conditions during a predetermined monitoring period are provided. The present invention provides a voltage stability monitoring device for estimating a voltage stability by using a voltage stability curve representing the voltage stability in an electric power system, including a voltage stability limit prediction unit for predicting a voltage stability limit, a voltage stability calculation condition determination unit for determining voltage stability calculation conditions by using a prediction result of voltage stability limit, a voltage stability curve calculation unit for calculating the voltage stability curve using a result of the voltage stability calculation condition determination, and a voltage stability margin calculation unit for calculating a voltage stability margin using a calculation result of the voltage stability curve.

A reduction instruction receiver receives a reduction instruction for energy from a server. An energy setter sets, when the reduction instruction receiver receives the reduction instruction, individual target energies for the respective subsystems, the individual target energies each being a target value of a consumption energy for a corresponding subsystem such that (i) a total of individual target energies that are target values of consumption energies for the respective subsystems is smaller than a total target energy that is a target value of a consumption energy of an entirety of the subsystems, and (ii) a higher correlation among consumption energies of the respective subsystems provides an increase in a total margin energy, the total margin energy being a difference between the total target energy and the sum of the individual target energies. The control-instruction transmitter transmits control-instruction information for control of the facility device based on the set individual target energies.

A computing device for distributed power system model calibration is provided. The computing device is programmed to receive event data and model response data associated with a model to simulate, wherein the model includes a plurality of parameters, divide the event data into a plurality of sets, wherein each set includes associated parameters, and transmit the plurality of sets of event data to a plurality of client nodes. Each client node of the plurality of client nodes is programmed to analyze a corresponding set of event data to determine updated parameters for the model. The computing device is further programmed to receive a plurality of updated parameters for the model from the plurality of client nodes and analyze the received plurality of updated parameters to determine at least one adjusted parameter.

A versatile intelligent fault diagnosis (IFD) method for a distribution grid integrating renewable energy resources is described. Advanced signal processing techniques extract useful features from recorded three-phase current signals, which are input to a multilayer perceptron neural networks (MLP-NN) to diagnose i.e., to detect, classify, identify the feeder branch, and locate the faults. Once a fault is detected, classified and located, a grid operator may adjust grid parameters or dispatch a technician to correct the fault. The IFD method is independent of load demand, renewable energy generation, and fault information (resistance and inception angle) uncertainties, as well as measurement noise.

A utility management system and method including a water collection apparatus; a water storage apparatus in fluid communication with the water collection apparatus; a water storage quantity sensor; one or more water usage sensors; an energy generation apparatus; an energy storage apparatus coupled to the energy generation apparatus; an energy storage quantity sensor; one or more energy usage sensors; a processor with one or more channels to receive at least weather forecast data, water usage data, and energy usage data, and one or more channels to send at least a request for weather forecast data, wherein the processor is coupled to the one or more water usage sensors and energy usage sensors, and wherein the processor is programmed to use the received data to project water collection, water storage, energy generation, and energy storage and to formulate recommendations for water and energy usage; a control interface; and a data display.

A power management system, which manages a transaction of power generated based on renewable energy, includes: a power supply system capable of supplying power generated based on the renewable energy to a power demand system; and a power demand-supply management apparatus that manages demand and supply of the power. The power demand-supply management apparatus requests the power supply system to supply the power to the power demand system in a power generation time zone of the power, and issues, to the power demand system, a certificate that an amount of supplied power has been consumed in accordance with generation of the power.