摘要
为了解决配电网中可再生能源消纳的问题,并平抑其并网引起的有功功率波动,提出一种基于深度学习的算法对负荷进行预测的方法,来对混合储能系统的清洁能源消纳效果进行研究,建立可再生能源接入的配电网模型,最后通过某工业园区风光储示范项目中配电网实际数据对提出的调度方法进行验证。试验结果表明,所提出的负荷预测方法能达到理想预测效果,混合储能系统能平抑功率波动。
In order to solve the problem of renewable energy consumption in the distribution network,and to smooth the problem of active power fluctuations caused by its grid connection,a method for load forecasting based on deep learning algorithms is proposed and the clean energy consumption effect of hybrid energy storage systems is studied.A distribution network model is established for renewable energy access.Finally,the proposed dispatching method is verified through the actual data of the distribution network in a wind-solar storage demonstration project in an industrial park.The test results show that the proposed load forecasting method can achieve the ideal forecasting effect,and the hybrid energy storage system can smooth out power fluctuations.
作者
李红
朱立位
伏祥运
许志鹏
LI Hong;ZHU Liwei;FU Xiangyun;XU Zhipeng(Lianyungang Power Supply Branch,State Grid Jiangsu Electric Power Co.,Ltd.,Lianyungang 222004,China;School of Electric Power Engineering,Nanjing Institute of Technology,Nanjing 211167,China)
出处
《电工技术》
2022年第2期35-38,共4页
Electric Engineering
基金
国网江苏省电力有限公司科技项目(编号J2019112)。
关键词
负荷预测
混合储能
功率波动
深度学习
清洁能源消纳
load forecast
hybrid energy storage
power fluctuation
deep learning
clean energy consumption
