Power grid demand side dispatchable capacity prediction method and power dispatching method

Abstract

The invention discloses a power grid demand side dispatchable capacity prediction method and belongs to the technical field of intelligent power grid and computer data mining intercrossing. According to the method, basic user information, user interruption capability and user interruption wishes influencing the demand side dispatchable capacity are fully considered, further the most important influence factor is selected from the basic user information, the user interruption capability and the user interruption wishes, the selected influence factor is quantized in a grading mode, and a demand side dispatchable capacity prediction model is constructed in combination with a neural network. The invention further discloses a power dispatching method adopting the prediction method. Compared to the prior art, the method has higher prediction precision and accuracy, and can provide powerful data support for applications of power grid dispatching, electricity price setting, power grid reliability analysis and the like.

Description

technical field [0001] The invention relates to a method for forecasting dispatchable capacity on the demand side of a power grid, and belongs to the technical field intersecting smart grids and computer data mining. Background technique [0002] Power grid dispatching refers to the organization, command, guidance and coordination of the power grid operation by the power grid dispatching organization to ensure the safe, high-quality and economical operation of the power grid. Its main tasks include: ①Forecast electricity load, ②Formulate power generation tasks, operation mode and operation plan, ③Carry out safety monitoring and safety analysis, ④Direct operation and deal with accidents. The traditional power system scheduling mainly relies on the combination of generators for energy scheduling. The present invention studies the impact of demand response on the safe and stable operation of the power grid from the perspective of demand-side scheduling. [0003] The proposal o...

AI Technical Summary

Problems solved by technology

[0007] (1) There are relatively few studies on the prediction of schedulable resource capacity, and most of the predictions are aimed at user load prediction, while user load and schedulable resource characteristics are completely different, and the prediction methods are also different

[0008] (2) The existing demand-side schedulable resource forecast is relatively rough, and the factors considered are relatively simple. The capacity forecast method is often only for a specific industry or user forecast, and has little applicability

[0009] (3) There are many factors affecting the schedulable resource capacity on the demand side, some of which are difficult to analyze quantitatively, and it is difficult to build a practical prediction model

[0010] (4) The capacity of schedulable resources on the demand side fluctuates greatly, and the existing technology is difficult to guarantee the prediction accuracy

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