Research on the Deviation Analysis of Utilization Hours in Wind Power Plants Based on Regulatory Data Fusion and Feature Extraction & Processing Technologies

Abstract

Abstract The continuous elevation of wind power consumption pressure has proposed higher requirements for the technical means, which comprehensively support the wind power consumption. The power generation level of a wind power plant is measured through the utilization hours at present, but the factors influencing the utilization hours are scarcely analyzed and quantified. In order to accurately figure out the reasons for the different utilization hours of wind power plants located in the same area, the total power prediction, power plant data, standalone data, resources, etc. were summarized, and the contribution degrees of five dimensions—resources, equipment availability, AGC command balance degree, AGC command following performance, and power generation capacity—to the utilization hours were analyzed and quantified through the data fusion and feature extraction, in an effort to find the main factors influencing the utilization hours in different power plants. The customized measures were proposed according to the conclusions in order to increase the utilization hours for the power plants. The derived computing method was applied to the wind power plant data acquired by a company in a province, followed by the difference analysis of the utilization hours. It was found that in Mulan sectional area, the reason for partially low utilization hours in Jifeng and Xunfeng Wind Power Plants was resource factor, that for Daheishan and Songshan Wind Power Plants lied in equipment availability, and that for Jufeng Wind Power Plant was possibly equipment following performance or equipment power generation capacity. In addition, the AGC command balance degrees in all target power plants were at low levels.