用于弃风电量计算的样板风机选择方法  

Typical Wind Turbine Selection for Wind Power Curtailment Calculation

作　　者：王勃[1] 郑太一[2] 赵俊屹 冯双磊[1] 孙勇[2] 

机构地区：[1]中国电力科学研究院新能源研究所,北京100192 [2]国网吉林省电力有限公司电力调度通信中心,长春130021 [3]国网山西省电力有限公司电力调度通信中心,太原030001

出　　处：《电力系统及其自动化学报》2016年第3期71-76,共6页Proceedings of the CSU-EPSA

基　　金：国家重点基础研究发展计划(973计划)资助项目(2012CB215200)

摘　　要：为了保证弃风电量计算的准确性,必须合理选择样板风机.以风机实际运行数据为基础,定量分析了风电场内风机的出力特性;选择不同的样本风机,通过遍历法研究了不同样板风机组合对弃风电量估计的影响;以非限电时段的理论电量相对误差最小为优化目标,采用遗传算法实现对最优样板风机的选择.研究结果表明,不同样本风机组合对弃风电量计算的准确性影响显著,选择10％～30％的风机作为样板风机可达到最小电量相对误差.通过实际算例验证了样板风机选择方法的高效性及准确性.Typical wind turbines selection is the key to realize wind power curtailment estimation. The power characteristics of wind turbines and the effect of different wind turbine combination on wind power curtailment estimation are analyzed based on operating data of wind turbines, and then an optimal typical wind turbine selection method which based on genetic algorithms is proposed. Research results show that the random selection of typical wind turbines is obtained in a high uncertainty of the curtailment estimation, and also more likely to overestimate. In the case of optimization se- lection, 10%～30% typical turbines reach the minimum relative error. Genetic algorithm is used to capture the optimal combination of typical wind turbines, and the optimization efficiency is improved significantly.

关 键 词：风电场 弃风电量 样板风机 遗传算法 最优化 

分 类 号：TM743[电气工程—电力系统及自动化]