可再生能源2017，Vol.35Issue(12)：1841-1846,6.
基于优化聚类的组合风速短期预测
Short-term wind speed forecasting of combined ELM based on optimal clustering
摘要
Abstract
Accurate wind speed prediction is the key to wind power forecastingand very important to the safe and stable operation of power system. This paper presents a method of combined short-term wind speed forecasting based on optimal fuzzy C means (OFCM)clustering.First of all,the initial clustering center of fuzzy C means clustering algorithm is optimizedby using simulated annealing genetic algorithm. Then,the initial wind speed attribute data is classified. According to the differentwind speed samples,combined wind speed forecasting model is builtby using extreme learning machine (ELM).Finally,the feasibility of the method is verified by comparing the measured data with predicted value.关键词
风速预测/模拟退化遗传算法/FCM聚类/极限学习机Key words
wind speed forecasting/genetic simulated annealing algorithm/FCM clustering/extreme learning machine分类
能源科技引用本文复制引用
陈记牢,栗惠惠,李富强,郝飞,张圆美..基于优化聚类的组合风速短期预测[J].可再生能源,2017,35(12):1841-1846,6.基金项目
国家高技术研究发展计划"863"资助项目(SS2014AA052502). （SS2014AA052502）
