储能科学与技术 ›› 2015, Vol. 4 ›› Issue (4): 388-393.doi: 10.3969/j.issn.2095-4239.2015.04.007

• 研究及进展 • 上一篇    下一篇

基于风电功率预测误差区间的储能系统控制策略

严干贵1, 冯凯翔1, 刘嘉2, 李军徽1, 王月1, 孙兆键3, 李鸿博4   

  1. 1 东北电力大学,吉林 吉林 132012;
    2 广西电网有限责任公司,广西 南宁 530029;
    3 国网烟台供电公司,山东 烟台 264000;
    4 国网吉林省电力有限公司培训中心,吉林 长春 130022
  • 收稿日期:2014-10-25 出版日期:2015-08-19 发布日期:2015-08-19
  • 通讯作者: 严干贵（1971—）,男,博士,教授,主要研究方向为风力发电联网运行分析与控制和柔性直流输电等,E-mail：yangg@mail.nedu.edu.cn。
  • 作者简介:严干贵（1971—）,男,博士,教授,主要研究方向为风力发电联网运行分析与控制和柔性直流输电等,E-mail：yangg@mail.nedu.edu.cn。
  • 基金资助:
    国家重点基础研究发展计划（973计划）（2013CB228201）,吉林市科技发展计划（201464038）及国家电网公司2015年科技项目（522201150038）

A control strategy for energy storage system based on wind power prediction error interval

YAN Gangui1, FENG Kaixiang1, LIU Jia2, LI Junhui1, WANG Yue1, SUN Zhaojian3, LI Hongbo4   

  1. 1 College of Electrical Engineering, Northeast Dianli University, Jilin 132012, Jilin, China;
    2 Guangxi Province Electric Grid Company, Nanning 530029, Guangxi, China;
    3 State Grid Company of Yantai, Yantai 264000, Shandong, China;
    4 State Grid Jilin Electric Power Training Center, Changchun 130022, Jilin, China
  • Received:2014-10-25 Online:2015-08-19 Published:2015-08-19

PDF

456

被引次数

3

摘要： 由于风能的间歇性和随机性,风电功率预测的精度依然较低。随着大规模风电的集中接入,不确定性风电功率并网运行会加重电力系统的调控负担,同时会对日前调度计划安排带来不利影响。储能系统具有对功率和能量的时间迁移能力,被认为是平抑风电功率波动性、提高风电功率确定性的有效手段。本文从电力系统安全角度分析了制约风电上网规模的原因,使用基于时间序列的自回归模型预测风电功率,提出利用储能平抑风电功率预测误差区间的方法,对比考虑最大预测误差的传统调度方法,采用风电平均入网容量、风电发电量、电网空间利用率等评价指标评估所提出方法的有效性。

关键词: 风电调度, 预测误差区间, 储能系统, 评价指标

Abstract: Due to intermittency and randomness of wind, the accuracy of wind power prediction is still low. With access of large-scale wind power to centralized grid systems, significant increase is expected in the burden of power system scheduling, leading to adverse effects to power control. This can be alleviated by using energy storage systems (ESS), which is able to time shift energy and power. This paper first describes the impact of uncertainty of wind power on the scale of wind power dispatching in terms of power system security. Then a time series regression model is proposed to predict wind power. A control strategy is put forward for ESS based on wind power prediction error interval. Finally, an assessment is made on the effectiveness of the strategy.

Key words: wind power schedule, prediction error interval, energy storage system, evaluation

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