Provided are a load transfer method and system in thunder and lightning weather. The method includes: detecting lightning and predicting a position and time of a lightning strike to obtain a lightning prediction result; determining a transmission line possibly struck by lightning in a power grid according to the lightning prediction result; determining a load transfer scheme; and before the lightning occurs, transferring at least part of loads on the transmission line possibly struck by lightning according to the load transfer scheme.

Methods for implementing power delivery transactions between a buyer and a seller of electrical energy supplied to an electrical grid by an integrated renewable energy source (RES) and energy storage system (ESS) of a RES-ESS facility are provided. Estimated total potential output of the RES is compared to a point of grid interconnect (POGI) limit to identify potential RES overgeneration, and the buyer is charged if potential RES overgeneration is less than potential overgeneration during one or more retrospective time windows. The method provides a basis for the RES-ESS facility owner to be paid for an estimated amount of energy that did not get stored as a result of a grid operator not fully discharging an ESS prior to the start of a new day.

A method may include determining a position and movement of a shadow on a plurality of solar modules of a solar power plant using an analysis of irradiance data from sensors disposed proximate the plurality of solar modules. The method may include predicting future power output for the plurality of solar panels based on the movement of the shadow over the plurality of solar modules and modifying a power output of the solar power plant based on the predicted future power output.

A system and method that enables the ongoing communication, tracking, and management review of feedback among a population of workers and their management.

An energy saving support system according to an embodiment is configured to provide a consumer, who has an electric load to which electric energy is supplied from an electric power supply system within a house, with energy consumption-related information through a photo frame or the like. The information providing apparatus is configured to acquire an acceptability level, which stepwise indicates a degree of interest of the consumer in the energy consumption-related information, and to determine the energy consumption-related information to be newly provided to the consumer based on the acceptability level.

Provided is a source-load cooperation access method for a power distribution region. The method includes: establishing a timing feature model of a distributed generator and a timing feature model of a load respectively, acquiring a timing feature of the distributed generator in an access power distribution region by using maximum likelihood estimation and acquiring a timing feature of a user which accesses the power distribution region by using classification and regression trees; and inputting the timing feature of the distributed generator and the timing feature of the user which access the power distribution region into a combination optimization model, and determining a source-load access feeder through optimization.

A micro-power wireless access method and apparatus for the Internet of things for power transmission and transformation equipment involves a time synchronization process, a traffic channel access process, a control channel configuration information access process, and a control channel burst information access process. In the time synchronization process, an aggregation node determines a delay parameter and other parameters based on a timeslot in which traffic information randomly transmitted by a sensing terminal is located, and the sensing terminal adjusts transmission time of a corresponding frame based on the parameters. The traffic channel access process adopts a mode in which one-way reporting is mainly used, to minimize working time of a sensor. The present disclosure realizes limited two-way communication on a control channel, supports configuration of a sensor cycle, a threshold, and other parameters, and supports a retransmission mechanism on the control channel for important alarm information.

A method performed by a control node for a radio access network. The control node may select an energy source from a plurality of energy sources connected to a base station based on selecting an energy rate of one of the energy sources correlated in time with a radio traffic power usage of the base station. The selection may be made from a plurality of energy rates for the plurality of energy rates correlated in time for each energy source with a radio traffic power usage of the base station. The selected energy rate may improve at least one operating parameter of the selected energy source. The control node may activate the selected energy source for use by the base station. A further method performed by a global control node may be provided.

Disclosed is an optimal power flow acquiring method for regional distribution network of small hydropower groups based on deep learning, which specifically includes the following steps: generating required data sets by adopting continuous power flow and power flow equation calculation methods; the data set is randomly divided into training data (80 percent) and test data (20 percent); training the built convolutional neural network model with training data to learn the mapping relationship between load and generator output power; inputting test data, and directly obtaining P.sub.G and Q.sub.G from the trained convolutional neural network; and solving residual variables V.sub.i and θ.sub.i with traditional power flow solver. The application can accelerate the solving speed of the optimal power flow problem with higher prediction accuracy.

A computer-implemented method and system is provided. The system adaptively switches prediction strategies to optimize time-variant energy demand and consumption of built environments associated with renewable energy sources. The system analyzes a first, second, third, fourth and a fifth set of statistical data. The system derives of a set of prediction strategies for controlled and directional execution of analysis and evaluation of a set of predictions for optimum usage and operation of the plurality of energy consuming devices. The system monitors a set of factors corresponding to the set of prediction strategies and switches a prediction strategy from the set of derived prediction strategies. The system predicts a set of predictions for identification of a potential future time-variant energy demand and consumption and predicts a set of predictions. The system manipulates an operational state of the plurality of energy consuming devices and the plurality of energy storage and supply means.