中国电力 ›› 2014, Vol. 47 ›› Issue (3): 24-27.DOI: 10.11930/j.issn.1004-9649.2014.3.24.3

• 风光储专栏 • 上一篇    下一篇

一种混合储能光伏发电系统的功率预测算法

梁适春1, 张晓冬1, 林培峰2, 牛萌2   

  1. 1. 北京交通大学,北京 100080;
    2. 国网智能电网研究院中电普瑞科技有限公司,北京 102200
  • 收稿日期:2013-12-13 出版日期:2014-03-31 发布日期:2015-12-18
  • 作者简介:梁适春(1991-),男,硕士研究生,从事电力电子、新能源方向研究。E-mail: liangshichun0204@163.com

A Power Prediction Model of PV System With Hybrid Energy Storage

LIANG Shi-chun1, ZHANG Xiao-dong1, LIN Pei-feng2, NIU Meng2   

  1. 1. BeiJing JiaoTong University, Beijing 100080;
    2. China EPRI Science & Technology Co.,LTD,State Grid Smart Grid Research Institute,Beijing 102200
  • Received:2013-12-13 Online:2014-03-31 Published:2015-12-18

摘要: 对混合储能光伏发电系统进行了优化配置,加入完善的光伏功率预测算法,可以减少储能单元深度充放电的次数,延长储能单元的使用寿命,提高系统的能量利用率。提出了基于趋势移动平均法的超短期光伏功率预测数学模型,模型以部分历史数据为输入量,通过数据处理,得出预测量可提高和改进现有光伏功率预测算法的平滑效果。通过在多云天气环境下的实验,验证了该光伏功率预测算法可以达到及时跟踪并平滑光伏波动、减小储能单元容量的功能。

关键词: 光伏发电系统, 混合储能, 光伏波动, 光伏功率预测, 趋势移动平均法

Abstract: After adding prefect photovoltaic power prediction algorithm,the photovoltaic power generation system with hybrid energy storage,which is optimized,can let the photovoltaic power and invert power to keep balance in a short period of time.Then it can reduce the number of storage units frequently depth charging and discharging and prolong the service life of the storage unit and raise the utilization rate of the energy of the system.The existing prediction algorithm of photovoltaic power,which includes BP neural network,similar day typical of the trend and least squares support vector machine etc,has some shortcomings which the utility is not strong and smooth effect is not good.This paper proposes a pratical short-time photovoltaic power prediction mathematical model which is based on the trend of moving average model,the model is based on the historical datas as input,then manipulation datas to get the predicted value.Through the experiment under weather environment of the cloudy, the photovoltaic power prediction algorithm,which can timely tracking and smoothing PV fluctuation,also reduce the storage unit's capacity,is verified.

Key words: The Photovoltaic Power Generation System, Hybrid Storage, Photovoltaic fluctuation, The Photovoltaic Power Prediction, The Trend of Moving Average Method

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