基于优化聚类的组合风速短期预测

发布时间：2018-05-28 07:48

本文选题：风速预测 + 模拟退化遗传算法　；参考：《可再生能源》2017年12期

【摘要】：准确的风功率预测对电力系统安全、稳定运行具有重要意义,而风速预测是风功率预测的关键。文章提出一种基于优化模糊C均值(Optimal Fuzzy C means,OFCM)聚类的组合风速短期预测方法。首先,采用模拟退火遗传算法优化模糊C均值聚类算法的初始聚类中心;其次,基于优化模糊C均值聚类算法将初始风速属性样本数据进行分组;再根据不同风速样本组,运用极限学习机(Extremely Learning Machine,ELM)构建组合风速预测模型;最后,通过风速实测值与预测值的对比,验证了该方法的可行性。
[Abstract]:Accurate wind power prediction is of great significance to the safe and stable operation of power system, and wind speed prediction is the key to wind power prediction. This paper presents a short-term forecasting method for combined wind speed based on optimal Fuzzy Fuzzy OFCM clustering. First, the simulated annealing genetic algorithm is used to optimize the initial clustering center of fuzzy C-means clustering algorithm; secondly, the initial wind speed attribute sample data are grouped based on the optimized fuzzy C-means clustering algorithm; then according to different wind speed sample groups, The combined wind speed prediction model is constructed by using extreme learning machine Extremely Learning Machine (ELM). Finally, the feasibility of this method is verified by comparing the measured wind speed values with the predicted ones.
【作者单位】：呼和浩特职业学院机电学院;国网吉林省电力有限公司经济技术研究院;
【基金】：国家高技术研究发展计划“863”资助项目(SS2014AA052502)
【分类号】：TM614

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