A method is proposed for real-time economic dispatch in power system operation, especially in systems that include renewable power sources that may cause heavy deviations from a generation schedule due to their uncertain outputs. According to the method an optimal generation schedule is obtained based on forecasted load data. This schedule has to be adjusted if the actual load and renewable energy source outputs unexpectedly deviate from the forecasted value. An algorithm employed in the method is capable of dictating generation adjustments which minimize total generation costs. The algorithm is a modification of the base point and participation factor method. It differs from existing methods in that a precise model of transmission losses is adopted in the algorithm to achieve higher accuracy in optimization. The proposed method also has significant advantage in execution speed so that it is suitable for real-time operation.

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.

The present disclosure is directed to systems and methods for controlling an electrical system using simulation-based setpoints. Some embodiments include control methods that enable recalculation of the optimal setpoints during demand windows. Some embodiments include a multi-mode controller to control an electrical system in a charge mode and a demand mode. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

A system includes a database storing demand response data, the demand response data including demand response agreement parameters, demand response load and energy demand characteristics of one or more demand response customers, the demand response load characteristics including power consumption capacity of each of one or more demand response loads, an aggregator to aggregate the demand response loads based on the demand response data and forecast data into a demand response portfolio, a monitor to monitor power demand of one or more demand response customers and one or more power grids, and a dispatcher to notify the one or more demand response customers of the demand response portfolio and to notify a utility of a response from the one or more demand response customers whether to control the demand response load to return the power consumption capacity of the demand response load back to the one or more power grids.

A computing device translates each of a group of structured language graphical process flow element representations, that each represents within a structured language one node of a captured graphical process flow diagram of a first business process, into one of a group of numerical strings that each represents within a set of data fields the respective node and connections to and from the respective node. The group of numerical strings is sequenced in accordance with values of the respective data fields within each numerical string that represents the respective node and the connections to and from each represented node of the captured graphical process flow diagram of the first business process.

Transaction-enabling systems including a controller are disclosed. The controller can access a distributed ledger including an instruction set, tokenize the instruction set, interpret an instruction set access request, and, in response to the instruction set access request, provide a provable access to the instruction set.

An information processing (1) includes: input means (2) for inputting a predicted value of an amount of demand at each of a plurality of times; and output means (3) for outputting a production plan that satisfies the predicted value based on an optimum solution of an optimization model in which at consecutive times, a constraint is given to an amount of production of each of at least one production facility and a data range indicating a range of uncertainty is set in the amount of demand, the optimization model determining the production plan including a planned value of the amount of production of each of the at least one production facility at each of the times up to a predetermined time for the amount of demand at each of the times up to the predetermined time.

Provided is an abnormality determination apparatus. The abnormality determination apparatus, comprises: a storage unit; and a processor in communication with the storage unit. The processor configured to: accept a first signal output from a first sensor related to operation of a power transmission device and a second signal output from a second sensor attached to the power transmission device; determinate an operating condition based on the first signal; predict feature value of the second signal concerning the power transmission device in a normal state depending on the determined operation condition; and determine a presence or absence of an abnormality based on the predicted feature value of the second signal depending on the determined operating condition of the power transmission device and based on an actual feature value of the second signal

A power generation planning apparatus that calculates a generation plan which is a plan of starting and stopping and output power of electric generators. The apparatus includes an information calculation unit that calculates demand and supply of electric power, a plan calculation unit that calculates the generation plan of the starting and stopping and the output power of the electric generators by using, as an input, the generation information calculated by the information calculation unit, and an adjustment unit that calculates a generation plan with a time interval shorter than the generation plan by adjusting a starting initiation time and/or a stopping initiation time of the electric generator in the generation plan such that total power generation cost is reduced by using, as inputs, the generation plan calculated by the plan calculation unit and generation information with a time interval shorter than the generation plan.

A power generation facility operation device includes an opportunity loss calculator for calculating a power generation opportunity loss value, (a loss value resulting from losing the power generation opportunity when output of the power generated from a power generation facility is reduced according to a request for provision of reserve power desired by an electric power provider), a reserve power incentive calculator for calculating a reserve power incentive value, (a value equivalent to an incentive obtained by the electric power producer from the electric power provider by output control being performed in the power generation facility and the reserve power being supplied to the electric power provider, and a reserve power plan calculator for calculating a plan of the reserve power that the power generation facility is to secure in order to keep the power generation opportunity loss value below the reserve power incentive value.