摘要
以大规模风电并网为背景,以实现有效接纳风电为目的,通过概率潮流计算,对地理位置不同的风电场之间风速的互补性进行分析。为模拟不同风电场之间风速的互补性,提出采用Frank Copula函数构建风电场之间风速的联合概率分布,选取Spearman秩相关系数作为风电场之间风速的互补性测度。采用云南电网实际数据作为算例,重点分析了风速的互补性对节点电压、支路潮流及线损的影响。研究结果表明,考虑风速的互补性可以更合理地评估风电场对系统的影响,有利于更好地进行风电场选址及电网规划。
With the penetration of large - scale wind power, in order to make a contribution to the consumption and utilization of wind power, the effect of wind speed complementation among different wind farms on the calculation results of probabilistic load flows is studied. In order to simulate the complementation of wind speed among different wind farms, a joint probability distribution model of wind speed based on Frank Copula is proposed and the Spearman rank correlation coefficient is selected to measure the complementation of wind speed among different wind farms. The case study on Yunnan Power Grid focuses on the effect of wind speed complementation on the node voltage, branch active power and line loss. The results demonstrate that it can help to assess the impact of wind farms on power system more reasonably and select better wind farm sites and make a better power grid planning when considering wind speed complementation
出处
《云南电力技术》
2013年第6期84-88,共5页
Yunnan Electric Power
关键词
COPULA理论
风电场
风速互补性
秩相关
概率潮流
Copula theory
wind farm
wind speed complementation
rank correlation
probabilistic load flow
