A method for feeding electrical power into an electrical supply network by means of at least one wind power installation having a power control and a generator, comprising the steps of: creating an electrical power gradient for an electrical power to be generated by the wind power installation wherein the power gradient at least: is limited by means of a stabilization operator or is created by means of a prediction operator in such a way that the electrical power gradient is unequal to a predicted wind power gradient, adjusting the created electrical power gradient in the power control of the wind power installation, generating an electrical power by means of the wind power installation depending on the created electrical power gradient for a feed-in time period with a feed-in time.

A power generation system (100, 200, 300, 400) is presented. The power generation system includes a prime mover (102), a doubly-fed induction generator (DFIG) (104) having a rotor winding (126) and a stator winding (122), a rotor-side converter (106), a line-side converter (108), and a secondary power source (110, 401) electrically coupled to a DC-link (128). Additionally, the power generation system includes a control sub-system (112, 212, 312) having a controller, and a plurality of switching elements (130, and 132 or 201). The controller is configured to selectively control switching of one or more switching elements (130, and 132 or 201) based on a value of an operating parameter corresponding to at least one of the prime mover, the DFIG, or the secondary power source to connect the rotor-side converter in parallel to the line-side converter to increase an electrical power production by the power generation system.

Systems and methods for controlling power flow to and from an energy storage system are provided. One implementation relates to an energy storage system comprising an energy storage device, an inverter configured to control a flow of power out of the energy storage device, a rectifier configured to control the flow of power into the energy storage device and one or more controllers. The one or more controllers may be configured to determine a schedule of a plurality of time periods based on historical price data. Each of the plurality of time periods may be associated with one of a state of charging, discharging, or idle. The one or more controllers may be configured to control the inverter and the rectifier based on the determined schedule.

A distributed energy conversion system is described. The illustrative distributed energy conversion system is described to include a first energy conversion entity and a second energy conversion entity being interconnected via an energy exchange network. The system is further disclosed to include an evaluation entity that is able to communicate with the energy conversion entities and create a roadmap for the consumption of energy by the first energy conversion entity and the second energy conversion entity.

The present disclosure relates to system, method and apparatuses for identifying load volatility of a power customary and a tangible computer readable medium therefor. In an embodiment of the present disclosure, the system comprises at least one processor; and at least one memory storing computer executable instructions. The at least one memory and the computer executable instructions are configured to, with the at least one processor, cause the system to determine boundary points for splitting a load curve of a power customer automatically, through performing density-based spatial clustering on data points of the load curve of the power customer; and detect tendency turning points of the load curve by means of the determined boundary points, so as to identify the load volatility of the power customer. With embodiments of the present disclosure, the boundary points for splitting the load curve may be determined automatically based on load data of each power customer instead of using a predetermined threshold and thus the load volatility of the load curve, which could provide a solution of self-adapted auto-identification for load volatility.

Systems and methods for probability forecasts and an energy transmission and/or energy distribution network are provided. Operational management may be carried out using a network control system with systematic consideration of forecast uncertainties. The probability of a distribution network being operable in a stable manner (e.g., with N-1 certainty) in a planning period is included. The system includes a forecaster for forecasts for a planning period, a forecast analyzer connected to the forecasts from the at least one forecaster, and elements for further information for outputting estimated forecast uncertainties. The system also includes a stability probability analyzer connected to the forecasts from the at least one forecaster, the estimated forecast uncertainties from the forecast analyzer, and elements for further information for outputting at least one item of information relating to an N-1 stability of the distribution network in the planning period.

Predictor variables that affect production or consumption of a resource are sampled at a plurality of times within a time period and aggregated to generate an aggregated value for each predictor variable over the time period. A model is generated which estimates the production or consumption in terms of the predictor variables. A regression process is performed to generate values for a plurality of regression coefficients in the model based on a cumulative production or consumption of the resource for the time period and the aggregated values. The sampled values of the predictor variables are then applied as inputs to the model to estimate productions or consumptions of the resource at each of the plurality of times. The estimated productions or consumptions may be used as inputs to a controller that operates equipment.

Systems and a method for forecasting data at noninstrumented substations from data collected at instrumented substations is provided. An example method includes determining a cluster id for a noninstrumented substation, creating a model from data for instrumented substations having the cluster id, and forecasting the data for the noninstrumented station from the model.

The invention includes systems and methods for power cogeneration. In certain embodiments the cogeneration systems include one or more units that are modularized; in some of these embodiments, the modules contain components that are integrated and ready for use with a control system that optimizes a result for the cogeneration plant. In some cases, the cogeneration system is part of a network of cogeneration systems.

The invention includes systems and methods for power cogeneration. In certain embodiments the cogeneration systems include one or more units that are modularized; in some of these embodiments, the modules contain components that are integrated and ready for use with a control system that optimizes a result for the cogeneration plant. In some cases, the cogeneration system is part of a network of cogeneration systems.