A method may include obtaining irradiance data at a first time and a second time from sensors, determining whether one or more solar modules of a plurality of networked power plants will be covered by a shadow or shade at a third time based on the irradiance data, and generating, based on the determination, a power output prediction for each power plant of the networked power plants at the third time. The method may further include receiving power delivery profiles for first and second loads, adjusting a power output of one or more power plants of the networked power plants based at least in part on the power output prediction and the power delivery profiles for the first and second loads, and allocating a combined power output of the power plants to the first and second loads based on first and second load reliability thresholds.

A method and apparatus for analyzing power devices in a circuit are disclosed. In one embodiment, a power analysis apparatus analyzes information on power supplied to the circuit and classifies the power patterns into groups of their own similar power patterns by making reference to the information on the power patterns, so as to acquire at least one piece of motif information which is information on at least one fingerprint. The apparatus further counts the frequency of occurrence of each motif and determines a pair of specific motifs having the difference between the counted frequencies of occurrence, which is within a predetermined value range, and average power variation values symmetrical to each other, whereby an accurate determination can be made as to the individual power devices in the circuit.

A power load data prediction method and device, and a storage medium are disclosed. In an embodiment, the he method comprises: acquiring historical power load data of a one-dimensional time sequence, the historical power load data including values of corresponding time points; mapping the values of corresponding time points to a coordinate system in which a horizontal axis is a set time period, and a vertical axis is time points within the time period, and performing marking at each mapping point by using predetermined pixel values corresponding to the values to obtain a mapping image, wherein different values correspond to different pixel values; and inputting the pixel values of the mapping image to a trained data prediction model, and acquiring a power load data prediction value output by the data prediction model. The method and device and the storage medium can improve the prediction accuracy of the power load data.

There is provided a method, a system, a storage medium and an orchestrator to enable a computer resource of a computing pool. In particular, the methods and apparatuses of the present disclosure are configured to enable a computing resource (16) of one or more computing pools (17), the computing resource (16) being in communication with a converter (13) of a renewable energy source (12). The methods and apparatuses may be configured to: tracking an electrical consumption of one or more electrical appliances (14) in communication with the converter; enabling the computing resource (16) in response to determining a surplus of renewable electrical energy provided by the renewable energy source (12); and to determining that there is computation demand from the one or more computing pools (17); and to determining that an estimated efficiency of use of the renewable energy is greater when responding to the demand of the one or more computing pools (17) than when injecting the renewable energy into an electrical grid (11) in communication with the converter (13).

An integrated energy optimizer having an edge side and a cloud side. The edge side may incorporate an energy optimizer, a building management system connected to the energy optimizer, a controller connected to the building management system, and equipment connected to the controller. The cloud side may have a cloud connected to the energy optimizer and to the building management system, and a user interface connected to the cloud. Data from the field sensor may go to the optimizer and the building management system. The data may be processed at the optimizer and the building management system for proper settings at the building management system.

The invention relates to an electrical power distribution system, including: an energy storage unit connectable to a power supply and configured to store electrical energy supplied by the power supply; a splitter connected to the energy storage unit and connectable to a grid and a micro-grid, the splitter being configured to split electrical energy supplied by the energy storage unit to allow electrical energy to be controllably supplied to the grid and/or the micro-grid; a splitter meter connected to the splitter, the splitter meter being configured to measure an amount of electrical energy supplied by the energy storage unit to the micro-grid; and electronic controlling devices coupled to the splitter, the one or more electronic controlling devices being configured to: determine a micro-grid load requirement; and control the splitter to cause electrical energy to be supplied to the micro-grid in accordance with the micro-grid load requirement.

A method of controlling a microgrid includes receiving, by a power management system, PMS, of the microgrid, operating point values for a plurality of controllable assets. The method includes determining, by the PMS, an asset headroom. The method includes determining, by the PMS, a modified operating point value that is dependent on the received operating point value of the controllable asset, the determined asset headroom of the controllable asset, and a total power offset of the microgrid. The method includes controlling, by the PMS, the controllable assets for which the modified operating point values have been determined in accordance with the modified operating point values.

A site management system has a site management device located on a fielded site, which has a controller unit integral with a power provision unit, and the power provision unit receives an input voltage via a conductor cable and delivers power to one or more receptacles. Additionally, the system has a plurality of remote devices communicatively coupled to the site management device over a wireless network and at least one off-site computing device communicatively coupled to the site management device. Further, the system has a processor on the controller unit that communicatively couples with at least one remote device, receives data indicative of a unique identifier from the wireless remote device, and determines whether the unique identifier correlates with a remote device of an individual who is permissively on the fielded site. In addition, the processor transits data indicative of the individual and data indicative of whether the individual is permissively on the fielded site to the off-site computing device or a site manager's remote device.

Embodiments of systems and methods for power demand management are described herein. More specifically, embodiments comprise systems and methods for powering, controlling, and/or operating various types of controllable load for integration with power fluctuations from intermittent power generation plants, such as photovoltaic arrays and wind turbine farms.

A method tests the configuration of an aggregated DERs system using distributed asset managers in a decentralized hardware-in-the-loop (“HIL”) scheme. The managers contain the model of the asset they are meant to control. The method programs an asset manager with a model of a DERs asset. A plurality of asset managers are connected to a central controller. The plurality of asset managers are also connected to a simplified hardware-in-the-loop platform. The simplified HIL platform is configured to solve a network model, a load model, a non-controllable asset model, and a grid model. The method tests the DERs system control structure by using: (a) the simplified HIL platform to solve the network model, the load model, the non-controllable asset model, and the grid model, and (b) the asset manager to solve the model of the DERs asset, without any simulation between the central controller and the distributed asset managers.