Wind electricity maximum installed capacity prediction method which uses maximum entropy principle

Abstract

The invention relates to a wind electricity maximum installed capacity prediction method which uses a maximum entropy principle. The wind electricity maximum installed capacity prediction method which uses the maximum entropy principle mainly achieves the purposes of achieving rapid and exact prediction for the wind electricity maximum installed capacity, and laying a foundation for reasonable planning of a power grid. The technical scheme is that the wind electricity maximum installed capacity prediction method which uses the maximum entropy principle includes steps: 1) building a chance constraint planning model of the wind electricity maximum installed capacity; 2) using a pattern search method combined with a maximum entropy method to solve the chance constraint planning model, and then obtaining prediction value of the wind electricity maximum installed capacity of a system. The electricity maximum installed capacity prediction method which uses the maximum entropy principle is mainly used in the wind electricity technology field.

Description

technical field [0001] The invention relates to a method for predicting the maximum installed capacity of wind power, in particular to a method for predicting the maximum installed capacity of wind power using the principle of maximum entropy, which is mainly applicable to the technical field of wind power. Background technique [0002] In recent years, with the attention to environmental issues and sustainable development, the construction of new energy sources including wind power has been greatly developed, and wind power has become an important part of the power system. On the one hand, wind power has the advantages of being clean, economical and renewable, and its development scale is constantly expanding. On the other hand, wind power is random, intermittent, unschedulable, and partially predictable, which makes large-scale wind power grid integration pose severe challenges to grid planning and operation. The existence of wind power uncertainty has a great impact on t...

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Problems solved by technology

[0003] Although wind power prediction technology is developing rapidly, in actual operation, it is still difficult to obtain a complete and accurate description of the uncertainty of wind power, and only part of the information about the probability distribution of wind power can be obtained

For example, in some existing methods (such as Monte Carlo method, Gram-Charlier method, etc.), the prediction of wind power is affected by the prediction time scale, and the prediction error comes from wind speed prediction error, power output model, prediction method, etc., and the accuracy is relatively low. Low

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