Wind electricity power prediction error evaluation method in consideration of load level and wind speed segments

Abstract

The invention relates to a wind electricity power prediction error evaluation method in consideration of a load level and wind speed segments. The wind electricity power prediction error evaluation method in consideration of a load level and wind speed segments includes: performing data processing on a wind electricity power prediction result reported by a wind farm according to a set data processing method; calculating wind electricity power evaluation indexes according to the wind electricity power prediction result, wherein the wind electricity power evaluation indexes include an accuracy rate, a qualification rate, a reporting rate, a correlation coefficient, a load peak positive deviation rate, a load valley negative deviation rate, a high-speed segment prediction accuracy rate and low-speed segment prediction accuracy rate; according to the wind electricity power evaluation indexes and index weights corresponding to respective wind electricity power evaluation indexes, calculating a comprehensive evaluation parameter of the wind electricity power prediction result; and evaluating the wind electricity power prediction error of the wind farm according to the comprehensive evaluation parameter. The method can realize the comprehensive evaluation of the wind electricity power prediction result and improves corresponding evaluation accuracy.

Description

technical field [0001] The invention relates to the technical field of pre-control of electric power systems, in particular to a wind power prediction error evaluation method considering load level and wind speed segmentation. Background technique [0002] With the rapid development of the global economy, the demand for energy continues to grow. At present, energy is facing practical problems such as resource depletion and serious pollution emissions. Wind energy, because it does not pollute the environment in the process of converting it into electrical energy, has abundant reserves, and has the lowest power generation cost. The characteristics of being close to conventional energy make it develop most rapidly. However, wind energy has the characteristics of volatility, intermittency and uncontrollability, which lead to random fluctuations in wind power output power (wind power of wind farms). With the increasing proportion of wind power generated by wind farms in the grid...

AI Technical Summary

Problems solved by technology

[0005] Based on this, it is necessary to provide a wind power prediction error evaluation method that considers load levels and wind speed segments to address the technical problems that traditional schemes affect the accuracy of wind power prediction errors.

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