基于Copula理论考虑风电相关性的源网协调规划

相邻风电场处于相似气象条件下,功率相关性较强。目前源网规划方法假设风电场功率间相互独立,忽略风电相关性对规划的影响,不适用于未来高比例可再生能源电力系统。文中主要提出了考虑风电相关性的源网规划方法,并探讨风电相关性对规划方案的影响。首先,基于Copula理论描述风电功率相关性,通过模糊C均值聚类法考虑风电不确定性,建立了概率风电功率模型。继而,提出考虑风电相关性的经济源网协调规划模型,采用遗传算法求解。通过Garver 6节点系统和巴西南部46节点系统算例分析不同系统规模下风电相关性对规划的影响。算例分析结果表明:风电相关性对局部规划方案影响显著,对全局影响较小,应避免建设连接有相关性较强的风电场接入点的输电线路,减少风电功率趋同变化的不利影响;经济性方面,投资费用增加,运行费用降低,对总费用影响不明显。

Copula Theory Based Generation and Transmission Co-planning Considering Wind Power Correlation

Since the neighboring wind farms are under similar weather conditions, their outputs are strongly correlated. Referring to conventional planning methods, wind farm outputs are supposed to be mutually independent without considering the influence of wind power correlation. Such methods are not suitable for future power system with high proportion of renewable energy. This paper proposes a generation and transmission co-planning method considering wind power correlation and discusses its influence. First, the Copula theory is applied to describe the correlation of wind power outputs. Then, a wind power probability model is developed based on the fuzzy C-means clustering model of correlated wind power. Further, the economical co-planning model is developed, which is further solved by the generic algorithm. Finally, the influence of wind power correlation in different system scales is analyzed via numerical results from the Garver 6-bus and South Brazil 46-bus systems. The results show that the wind power correlation has strong influence on the local generation and transmission expansion planning, while weak on the global planning. In order to reduce the adverse impact of wind power convergence, the transmission line connecting integration points with strongly correlated wind farms should be avoided. With increased transmission investment cost and the reduced operation cost, the influence of wind power correlation on the total cost is not obvious.