Provided are an operation limit value management unit managing an operation limit value related to the power flow power of system equipment and a determination unit calculating the power flow state for each set time of the future of a power system based on load dispatching information including a power generation plan value, a predicted output value, and a predicted value of power demand and determining whether or not stable is each power flow state by comparison with the operation limit value. The determination unit sequentially changes the first output power of a first power source defined by the power generation plan value of the first power source and calculates each power flow state based on power including the changed first output power and a predicted value of the output of a second power source.

A solar energy system includes a photovoltaic (PV) assembly and a drive system. The PV assembly comprises a support subassembly and an array of PV panels pivotable therewith about a longitudinal axis of the PV assembly. The drive system comprises a motor assembly comprising an electric motor and a gearing arrangement, and a pivot wheel comprising a hoop-portion and joined to the PV assembly. The hoop portion includes an outer circumferential channel, and two opposing catches defining a maximum pivot range. A chain resides partly within the circumferential channel, is engaged with the two opposing catches, and is also in geared communication with the motor assembly such that the motor is operable to rotate the pivot wheel. In some embodiments, the opposing catches define a maximum pivot range through an arc of more than π radians and less than 2π radians.

A system and method for performing novel wind forecasting that is particularly accurate for forecasting over short-term time periods, e.g., over the next 1-5 hours. Such wind forecasting is particularly advantageous in wind energy applications. The disclosed method is anchored in a robust physical model of the wind variability in the atmospheric boundary layer (ABL). The disclosed method approach leverages a physical framework based on the unsteady dynamics of earth's atmosphere, and drives forecasting as a function of previously-observed atmospheric condition data observed at the same location for which a wind forecast is desired.

Systems and methods are directed to controlling components of a utility grid. The system can receive data samples including signals detected at one or more portions of a utility grid. The system can construct a matrix having a first dimension and a second dimension. The system can train a machine learning model based on the matrix to predict values for signals of the utility grid not provided in the matrix. The system can receive bounds for one or more input variables, constraints on one or more output variables, and a performance objective for the utility grid. The system can determine, based on the machine learning model and via an optimization technique, an adjustment to a component of the utility grid that satisfies the performance objective. The system can provide the adjustment to the component of the utility grid to satisfy the performance objective.

Techniques for managing an off-grid power system include executing update requests for an off-grid power system that is communicably coupled to an energy management system by determining an amount of stored energy in energy storage devices in response to at least one update request, determining an amount of electrical power generatable by renewable energy power systems in response to another update request, determining a predicted reliability of at least a portion of the energy storage devices and the renewable energy power systems in response to another update request, and determining an amount of electrical power for a remote facility that is electrically coupled to the off-grid power system in response to another update request. The techniques further include determining a control command for the off-grid power system based on the responses to the update requests; and providing the control command to the off-grid power system to adjust an operation of at least one of the energy storage devices or the renewable energy power systems.

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.

Aspects of the present invention relate to a method for controlling a renewable power plant connected to a power network to reduce deviation of a measured frequency of the power network from a target frequency. The method comprises determining a forecasted power gradient over a forecast interval defined between a first time point and a second time point, and, at a third time point during the forecast interval, controlling the power plant to output active power according to a minimum active power level if the measured frequency at the third time point is below the target frequency, controlling the power plant to output active power according to a maximum active power level if the measured frequency at the third time point is above the target frequency. The maximum and minimum active power levels are based on the forecasted power gradient.

Apparatus and associated methods relate to automatically load matching, in time, energy physically generated and transmitted to a consumption location across at least one tracking and processing infrastructure. In an illustrative example, a load pool (LP) may be created based on energy consumed at a physical location at one or more selected time periods. A generation pool (GP) may, for example, be created based on energy generated and physically available for consumption at the physical location during the time periods. Associations may be created, for example, between measurements in the GP of energy generated and transmitted and measurements in the LP of energy consumed. The associations may be created as a function of predetermined privileges associated with the consumption location and generation locations and/or physical transmission links corresponding to the GP during the time periods. Various embodiments may advantageously determine environmental impact based on location and time-based load matching.

A method includes collecting energy resource data for the specific geographic location over a predetermined time period, calculating power curves and matrices for at least two energy technologies based on the collected energy resource data, estimating the potential of generated electric power over time of the at least two energy technologies based on the calculated power curves and matrices, the time period, and the characteristic parameters of each of the at least two energy technologies, simulating different base load and power variations based on the estimation of the potential generated electric power and different distribution of the electric power generation of the at least two energy technologies, identifying an optimal distribution of the at least two energy technologies by analyzing the base load and power variations for each simulation, and choosing the distribution of the electric power generation with the highest base load and lowest power variation.

A micro utility system. The micro utility system may include a portable container configured to house an energy storage system (ESS) and solar panel storage structures; a portable solar panel structure having two or more solar panels coupled to each other at one end, wherein the two or more solar panels are coupled to at least two wheels at a distal end of the portable solar panel structure; and circuitry configured to receive electrical power from the portable solar panel structure, wherein the circuitry includes a processor configured by machine-readable instructions to direct electrical energy from the portable solar panel structure or the ESS to a load.