可再生能源2018，Vol.36Issue(2)：215-222,8.
能源互联网下基于HS-Elman的光伏出力预测研究
The research on PV power prediction based on HS-Elman under Energy Internet
摘要
Abstract
Based on elabrating the concept of energy internet, this paper puts forward an improved Elman neural network (HS-Elman) forecasting model for photovoltaic power, considering different weather types, aiming to the photovoltaic output prediction problem. This paper analyzes the impacts of weather types, ambient temperature, air humidity, wind speed and irradiance on photovoltaic output prediction, and optimizes the model parameters, such as weights and thresholds, using harmony search algorithm. The prediction model is trained and tested based on photovoltaic historical data from a university in Shanghai Energy Internet platform.The results show that the model based on the HS-Elman intelligent algorithm can meet the standard of the photovoltaic output forecast, and the advanced model has a faster speed and better prediction precision under the different types of weather,compared with the traditional Elman neural network. Effectiveness and practicability can be improved and tested by the results.关键词
能源互联网/能效管控/光伏出力预测/Elman神经网络/和声搜索算法Key words
Energy Internet/effective energy control/PV power prediction/elman neural network/harmony search algorithm分类
能源科技引用本文复制引用
彭道刚,张宇,张浩,姚峻,艾春美..能源互联网下基于HS-Elman的光伏出力预测研究[J].可再生能源,2018,36(2):215-222,8.基金项目
上海市"科技创新行动计划"社会发展领域项目(16DZ1202500) （16DZ1202500）
上海市科委工程技术研究中心项目(14DZ2251100). （14DZ2251100）
