A power system comprising one or more power generators and a combiner. The system may be electrically connected to or include one or more loads. The combiner may have input terminals that are coupled to outputs of the power generators. The combiner may also have output terminals that are coupled to input(s) of the one or more loads. The power generators may be configured to transfer harvested power to the combiner, and the combiner may be configured to transfer the harvested power to the one or more loads.

A power system comprising one or more power generators and a combiner. The system may be electrically connected to or include one or more loads. The combiner may have input terminals that are coupled to outputs of the power generators. The combiner may also have output terminals that are coupled to input(s) of the one or more loads. The power generators may be configured to transfer harvested power to the combiner, and the combiner may be configured to transfer the harvested power to the one or more loads.

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 method for controlling an inverter-based resource (IBR) having a power converter connected to an electrical grid includes receiving a first power limit signal for the IBR from an external controller, receiving a second power limit signal for the IBR, and determining a constrained power limit signal based on the first and second power limit signals. The method also includes applying a first frequency droop function to the constrained power limit signal and determining at least one of a power reference signal or a pitch reference signal for the IBR as a function of an output of the first frequency droop function and the constrained power limit signal. Further, the method includes determining one or more control commands for the IBR based on at least one of the power reference signal or the pitch reference signal and controlling the IBR based on the control command(s) so as to support a grid frequency of the electrical grid within power available at the IBR.

A method for controlling an inverter-based resource (IBR) having a power converter connected to an electrical grid includes receiving a first power limit signal for the IBR from an external controller, receiving a second power limit signal for the IBR, and determining a constrained power limit signal based on the first and second power limit signals. The method also includes applying a first frequency droop function to the constrained power limit signal and determining at least one of a power reference signal or a pitch reference signal for the IBR as a function of an output of the first frequency droop function and the constrained power limit signal. Further, the method includes determining one or more control commands for the IBR based on at least one of the power reference signal or the pitch reference signal and controlling the IBR based on the control command(s) so as to support a grid frequency of the electrical grid within power available at the IBR.

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 system includes: an edge computing device disposed in an indoor facility having at least one light source; an energy storage subsystem configured to generate electrical power from light emitted by the at least one light source, and to supply the electrical power to the edge computing device, the energy storage subsystem including: a collector; an auxiliary energy storage device configured to receive energy collected by the collector, the auxiliary energy storage device having a first storage capacity; a main energy storage device having a second storage capacity greater than the first storage capacity; a controller configured to supply energy from the main energy storage device to the edge computing device; and a selector configured to selectively discharge energy from the auxiliary energy storage device to the main energy storage device.

A system includes: an edge computing device disposed in an indoor facility having at least one light source; an energy storage subsystem configured to generate electrical power from light emitted by the at least one light source, and to supply the electrical power to the edge computing device, the energy storage subsystem including: a collector; an auxiliary energy storage device configured to receive energy collected by the collector, the auxiliary energy storage device having a first storage capacity; a main energy storage device having a second storage capacity greater than the first storage capacity; a controller configured to supply energy from the main energy storage device to the edge computing device; and a selector configured to selectively discharge energy from the auxiliary energy storage device to the main energy storage device.

The disclosure provides a method for calculating a parameter changing domain of loads under a case that guarantees a constant locational marginal price in an electricity market, which relates to the electricity market field of the power system. With the method in the disclosure, the clearing model on the locational marginal price in the general form is established, and the safe changing domain of the locational marginal price with respect to the loads may be derived and calculated based on the first-order KKT condition expansion of the clearing model on the locational marginal price in the general form. When the increment of the nodal loads is subordinate to the changing domain, the locational marginal price may remain unchanged. The parameter changing domain of loads in the power system may be used for the comprehensive evaluation of power market clearing results and assisting the operation of the power market.

The present invention belongs to the technical field of information, particularly relates to the theories such as time series interval prediction, extreme learning machine modeling and Gaussian approximation solution, and is a wind power output interval prediction method. First, interval prediction of wind power output influencing factors is realized by time series analysis and normal exponential smoothing so as to consider an input noise factor. Then an extreme learning machine prediction model is established with an interval result as an input, output distribution is calculated based on iterative expectation and a conditional variance law, and thus an interval prediction result of wind power output is obtained. The method has advantages in interval prediction performance and calculation efficiency and can provide guidance for production, scheduling and safe operation of a power system.