摘要
为最大程度地提高风电跟踪计划出力能力,基于超短期风电预测功率建立了包含5个控制系数的储能系统充放电控制策略,并提出了利用粒子群优化算法实时优化储能系统充放电控制系数的方法,以减少日前短期风电预测误差。以典型风电场出力为例进行仿真分析,对固定系数方法及滚动优化系数方法进行了比较,并分析了影响预测精度的因素,结果验证了所提方法的可行性。
In order to maximize the ability to improve the tracking wind power schedule output, based on the ultra-short term forecasting of wind power, a charge and discharge power control method of energy storage system containing five control coefficients is proposed, and using the particle swarm optimization algorithm, a method to optimize the charge and discharge control coefficients for real time is put forward to reduce wind power short-term prediction error. Finally, taking the typical wind farm output for example, simulation verifications have been performed, the fixed coefficients and moving optimization coefficients methods were compared, and the factor affecting the accuracy of prediction is analyzed, the results show that the proposed control method is effective.
出处
《电网技术》
EI
CSCD
北大核心
2015年第2期432-439,共8页
Power System Technology
基金
国家自然科学基金项目(51107126)
国家电网公司科技项目(DG71-14-032)~~
关键词
超短期风电预测功率
风电计划出力
储能系统充
放电控制策略
滚动优化
荷电状态
ultra-short term wind power prediction
windpower schedule output
charge and discharge power controlstrategy
moving optimization
state of charge