中文摘要：

随着大规模风电并网,构建一个能准确描述风电场出力随机性和彼此间相关性的模型,对电网安全有效地利用风能意义重大。构建了基于Copula理论的多风电场出力联合分布函数模型,并引入相关性和拟合性指标,提出了基于熵权属性识别理论的最优模型选取方法。然后,给出了基于蒙特卡洛抽样和Copula联合分布的风电场出力相关性场景在电力系统经济调度中的应用。最后,以美国加州沿海风电场出力历史同步数据为样本验证Copula建模的有效性,结果表明,t-Copula不仅能很好地刻画原变量之间的相关性,而且能精准地拟合原样本经验分布函数。通过含多风电场的IEEE 118节点系统的动态经济调度算例,说明了考虑多风电场间相关性的建模对制定合理调度计划是必要且有效的。

英文摘要：

With increasing grid integration of large scale wind power, accurately constructing model to describe randomness and correlation of multi wind plants is of significance for safe and effective utilization of wind energy. A new method to model joint distribution function of multi wind plant output with Copula theory is proposed. Based on entropy weighted attribute recognition theory, optimal model selection method is developed by introducing correlation and fitting coefficient. It shows successful application in power system economic dispatch by constructing multi wind farm output correlation scenario based on Monte Carlo sampling and Copula distribution. Lastly, validity of Copula modeling is verified with historical data of a coastal wind farm in California. Results show that t-Copula can not only well describe correlation of original variables but also fit empirical distribution function accurately. Example of dynamic economic dispatch on IEEE-118 system with multi wind plant integrated proves that accurate correlation modeling between multi wind farms is necessary and effective to make a reasonable dispatch plan.