A method of trading electrical energy is provided. The method comprises a smart agent receiving state data affecting electricity usage within an electrical power grid over a specified time period and forecasting, with a supply/demand model, supply and demand for electricity within the power grid according to the state data. The smart agent uses a reinforced learning neural network to calculate a price for electricity according the state data and forecasted supply and demand. The smart agent submits an order to a matching engine to buy or sell electricity on the power grid at the calculated price according to specified market rules. The smart engine receives an acknowledgment from the matching engine if the order is matched to another agent on the power grid or a rejection from the matching engine if the order is not matched to another agent.

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 supply system contains a plurality of power generating devices, a plurality of power consuming devices, and a controller. The controller controls the power supply system based on a rated consumption value indicating an anticipated power consumption of the power supply system and also based on a standby value indicating a standby power. The standby value indicates the standby power made available by the power supply system at which emergency measures can be avoided if the actual power consumption deviates from the rated consumption. The power supply system further has a preprocessing device for calculating a rated consumption value and a standby value at which an emergency measure-free operation can be attained with the required probability, based on consumption values recorded in the past and using a probability value defined on the user side which defines the probability of the emergency measure-free operation of the power supply system.

Disclosed is state trajectory prediction in an electric power delivery system. Electric power delivery system information is calculated from measurements by intelligent electronic devices (IEDs), and communicated to a state trajectory prediction system. The state trajectory prediction system may be configured to generate a load prediction profile. The load prediction profile may provide a predicted response of a load at a future time. Further, the state trajectory prediction system may be configured to generate a generator prediction profile that provides a predicted response of a generator at a future time. The state trajectory prediction system may generate a state trajectory prediction based, at least in part, on the load prediction profile and the generator prediction profile. The state trajectory prediction may represent a future state of the electric power delivery system.

A system, apparatus, and method for distributed control of thermostatic electric loads (TELs) including receiving at an energy gateway, a demand response event signal and receiving real-time measurements of a temperature value and a power consumption value corresponding to a temperature setting of a plurality of TELs. The method retrieving historical data from pre-determined load profiles for the TELs and comparing load profiles and real-time measurements to determine a first consumption trajectory. Further, coordinating temperature settings of at least two TELs to generate a second consumption trajectory corresponding to the demand response event signal.

A method and apparatus for optimally allocating resources of a provider according to a contribution margin ratio of a resource consumer in a distributed energy resource environment are described. An embodiment is a method for distributing energy resources in a distributed energy resource system. The method may include receiving information about the amount of available energy resources from each of one or more providers, receiving information about the amount of required energy resources from each of one or more consumers, assessing a contribution margin ratio for each of the one or more consumers, calculating an energy resource allocation amount for each of the one or more consumers based on the assessed contribution margin ratio, and distributing energy resources to each of the one or more consumers based on the calculated energy resource allocation amount.

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 the load adjustment and an overlimit line capacity on the transmission line, and controlling the power generating facility, using the mitigation plan, to achieve the load modification and mitigate the probability of congestion predicted in the transmission line.

A microgrid system includes one or more power generators configured to provide electrical energy. The microgrid system also includes a localized distribution network coupled to the one or more power generators, coupled to the one or more loads, and coupled to an external grid. The microgrid system further includes a microgrid controller configured to predict microgrid demand for the one or more loads for a predetermined period of time. The microgrid controller is also configured to receive demand information for the external grid for the predetermined period of time. The microgrid controller is further configured to determine an operation plan for the one or more power generators based on the predicted microgrid demand and the received demand information. Moreover, the microgrid controller is configured to determine a schedule to transmit electrical energy to the external grid based on the operation plan.

A system and method for calculating energy to be preceded or delayed through a deactivation of appliance on a power network to reduce a highest threshold of power production required to meet power demand. Predictions of power demand by appliances and the possibility of preceding or delaying such demand away from a time of high power usage allow power use to be shifted away from periods of peak production. Further, such predictions allow more complete use of power once a power generator has been activated.

A system and method for distributed intelligence of power tracking and power allocation may include: receiving data by at least one computer from a plurality of identified charging stations and vehicles of customers at distributed locations throughout a power grid; analyzing, with at least one processor of the at least one computer, the data with respect to available power for those locations and customer historical usage and profiles; and sending commands, with the at least one processor, to reallocate power to assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on the analysis. Customer preferences may also be considered in predicting power demand issues and need for demand response. Economic rules may be executed to incentivize the customers to comply with demand response requirements where demand is greater than power supply.