This invention provides an energy storage device manager, a system comprising the energy storage device manager, computer-readable media configured for providing the energy storage device manager, and methods of using the energy storage device manager. The energy storage device manager can optionally control charge buses and/or load buses to modulate the state of charge of an energy storage device. The energy storage device manager can optionally be configured with a plurality of modes that target different states of charge. The plurality of modes can optionally comprise a maintain mode which targets a nominal (e.g. 50%) charge state and a high-charge mode that targets a state of charge greater than the maintain mode. The plurality of modes can optionally further include an in-use mode which targets a state of charge greater than the maintain mode, and turns on a load bus that is turned off in the preparation mode. The energy storage device manager can optionally be configured to determine a charge start time to execute the preparation mode. The energy storage device manager can optionally be configured to determine the charge start time based on forecast data (e.g. power prediction forecast determined based on weather forecast).

A method for operating a power generating facility connected to a power distribution grid having an uncertain power generation condition includes predicting a probabilistic power flow forecast in a transmission line of the power distribution grid for a period of time, wherein the transmission line is electrically coupled to the power generating facility, predicting, using the probabilistic power flow forecast, a probability of congestion over the transmission line of the power distribution grid during the period of time, generating a mitigation plan, including a load adjustment on the transmission line, using the probability of congestion predicted over the transmission line and a thermal limit constraint of the transmission line, wherein the mitigation plan balances load adjustment and an overlimit line capacity on the transmission line, and controlling the power generating facility, using the mitigation plan, to achieve load modification and mitigate the probability of congestion predicted in the transmission line.

Embodiments of the disclosure provide a method for operating a combined cycle power plant (CCPP). The method may include creating a variant control profile for the CCPP for a power plant model of the CCPP. The method may include modifying the variant control profile in response to the variant control profile not reducing the fuel consumption or meeting the quality threshold. The method may also include adjusting the CCPP to use the variant control profile in response to the variant control profile reducing the fuel consumption and meeting the quality threshold. Using the variant control profile adjusts a turbine section inlet temperature schedule or an exhaust temperature schedule for the CCPP.

A method of controlling a microgrid comprises receiving, by a power management system, PMS, of the microgrid, operating point values for a plurality of controllable assets. The method comprises determining, by the PMS, an asset headroom. The method comprises 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 comprises 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 of controlling a wind power plant including an energy storage device, the wind power plant being connected to a power grid and comprising one or more wind turbine generators that produce electrical power for delivery to the power grid, the method comprising: processing input data related to one or more inputs to the wind power plant to determine a probability forecast for each input; and controlling charging and discharging of the energy storage device in accordance with each probability forecast and a prescribed probability of violating one or more grid requirements.

According to embodiments described herein control of the auxiliary power system in a hybrid power plant is provided by determining a grid-draw threshold from an external power grid; monitoring power consumption for powered systems of the hybrid power plant; monitoring power generation of the hybrid power plant; discharging an alternative power source of one or more of an Energy Storage System (ESS) and an auxiliary generator in response to the power consumption exceeding the grid-draw threshold; and implementing prediction algorithms for power generation of the hybrid power plant and the power consumption. Accordingly, a source of power is managed between several alternative sources and the external power grid to meet plant operator defined criteria when maintaining power in various wind speed conditions.

A calculation device 20 is linked with an electric power system 1 and optimizes energy utilization efficiency of a grid S1 including a power storage device 15. The calculation device 20 determines the range of a final charge state of a prediction target section of the power storage device 15 on the basis of power demand prediction for the next and following sections, and assesses, through the optimization calculation for the prediction target section, whether or not the final charge state of the section falls within the range.

In an energy system in a community provided with a plurality of unit grids, each of which is an energy transfer network of a single-unit facility including a power load, the unit grids each include a photovoltaic generator, supply power generated by the photovoltaic generator thereof to the power load thereof, and, as an electric vehicle moves, form a cooperative grid that transfers power stored in a mobile storage battery mounted on the electric vehicle to and from another of the unit grids, and some of the unit grids whose geographical positional relationship is not fixed form a virtual grid for transferring power as a combination of the unit grids that form the cooperative grids changes in accordance with a destination of the electric vehicle.

A method and a system for energy scheduling of shared energy storage considering degradation cost of energy storage. Provided herein relates to energy scheduling for multiple microgrids. The method includes: acquiring energy data of each of microgrids in a multi-microgrid system of shared energy storage; establishing a peer-to-peer trading model between each of the microgrids; establishing a shared energy storage trading model between the multi-microgrid system and the shared energy storage device thereof; establishing a utility grid trading model between the multi-microgrid system and the utility grid thereof; and based on the peer-to-peer trading model, the shared energy storage trading model and the utility grid trading model, setting an objective of minimizing a total operating cost of the multi-microgrid system, and solving an objective function corresponding to the objective to acquire power data of each of the microgrids at each stage.

One embodiment provides a system and method for predicting network power usage associated with workloads. During operation, the system configures a simulator to simulate operations of a plurality of network components, which comprises embedding one or more event counters in each simulated network component. A respective event counter is configured to count a number of network-power-related events. The system collects, based on values of the event counters, network-power-related performance data associated with one or more sample workloads applied to the simulator; and trains a machine-learning model with the collected network-power-related performance data and characteristics of the sample workloads as training data 1, thereby facilitating prediction of network-power-related performance associated with a to-be-evaluated workload.