Wind power probability forecasting method based on numerical weather forecasting ensemble forecasting results

Abstract

The invention provides a wind power probability forecasting method based on numerical weather forecasting ensemble forecasting results. Numerical weather forecasting serves as the foundation, basic input data are provided for short-period wind power forecasting through a numerical weather forecasting ensemble forecasting technology, and a short-period forecasting model is established for each ensemble member to obtain a plurality of groups of forecasting results. For the obtained plurality of groups of forecasting results, and different characteristic forecast errors are classified through an ensemble forecasting configuration characteristic classification method and a forecasting power level classification method to obtain future forecast error bands under certain confidence level. According to the wind power probability forecasting method, under the same confidence level, the error band section is narrower, and for power grids containing large-scale wind power integration, under the condition of the same safety margin, the power grid operation cost can be effectively reduced, and the power grid operation economical property can be improved.

Description

technical field [0001] The invention relates to the field of wind power prediction, in particular to a wind power probability prediction method based on numerical weather forecast ensemble prediction results. Background technique [0002] Wind energy is an important part of renewable energy, and wind power is currently one of the most mature, large-scale development and commercial development prospects of renewable energy power generation. However, wind power is different from conventional energy in that it is highly random, intermittent, and uncontrollable. Large-scale wind power is integrated into the power grid, which will have certain impact on the planning and construction, operation scheduling, analysis and control, economic operation and power quality of the power grid. influences. Predicting the output power of wind farms is one of the important measures to deal with large-scale wind power access to the grid. Wind power prediction can provide technical support for t...

AI Technical Summary

Problems solved by technology

However, wind power has strong random fluctuations, and the law of wind generation is difficult to grasp, resulting in large wind power prediction errors, and the prediction results are difficult to provide an effective basis for the formulation of grid dispatching plans. The research on probabilistic prediction technology of power has obtained the error band interval of prediction results under a certain degree of confidence, which can provide basic technical support for the optimal scheduling of large-scale wind farm grid connection, so it has important practical application value

[0003] The current error band probability prediction of wind power mainly adopts certain parameter distribution models, such as Gaussian distribution, hyperbolic distribution, and beta distribution, etc., to fit the historical prediction error distribution of wind power, without identifying the prediction errors of different characteristics, the obtained probability The prediction error band has the same bandwidth for all prediction results, and the width is relatively large under the same confidence level, which is not conducive to the economic dispatch operation of wind power

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