电力系统保护与控制Issue(2)：26-32,7.
基于模糊信息粒化和最小二乘支持向量机的风电功率联合预测建模
A combined forecasting model for wind power predication based on fuzzy information granulation and least squares support vector machine
王恺 1关少卿 1汪令祥 2王鼎奕 2崔垚1
作者信息
- 1. 国网安徽省电力公司合肥供电公司，安徽 合肥 230022
- 2. 阳光电源股份有限公司，安徽 合肥 230088
- 折叠
摘要
Abstract
A combination prediction model modeling method for wind power average value prediction and wind power fluctuation range prediction is proposed, which is based on the fuzzy information granulation and least squares support vector machine (LSSVM). Firstly, fuzzy information granulation of the training samples is made, and effective component information of each window is extracted according to the need, namely the minimum, average and maximum value of each window. Secondly, LSSVM of the prediction models are established for each component, and then the adaptive particle swarm algorithm is used to optimize each component model. Finally, the optimized LSSVM model is used for combined forecast in terms of wind power average value and wind power fluctuation range. The case study shows that the combined prediction model can effectviely predict wind power average value prediction and wind power fluctuation range, and accurately track the wind electric power change.关键词
风力发电/功率预测/模糊信息粒化/最小二乘支持向量机/联合预测Key words
wind power/power predication/fuzzy information granulation/least squares support vector machine/combined forecast分类
信息技术与安全科学引用本文复制引用
王恺,关少卿,汪令祥,王鼎奕,崔垚..基于模糊信息粒化和最小二乘支持向量机的风电功率联合预测建模[J].电力系统保护与控制,2015,(2):26-32,7.
