考虑多风电场相关性的电网动态经济调度二阶段带补偿算法

大规模多风电场的并网给电网经济调度带来了巨大挑战,文中对含多风电场的电网日前动态经济调度问题进行研究。首先,引入Copula理论构建了多风电场间输出功率的联合分布。随后,建立了电网日前24h动态经济调度随机优化模型。针对约束中风电输出功率的随机性,引入二阶段带补偿算法求解,将原调度模型转化为二阶段模型:第一阶段为仅含常规变量约束,而在目标函数中增加补偿量期望值的优化模型;第二阶段为含随机变量约束,并以补偿量惩罚期望值最小为目标的优化模型;通过二阶段模型间的交替迭代求得最优解。基于IEEE 118节点系统和某省级大电网的算例对该方法的有效性进行了验证。

Two-stage Compensation Algorithm for Dynamic Economic Dispatch of Power Grid Considering Correlation of Multiple Wind Farms

The large-scale grid-connection of multiple wind farms has brought a great challenge to the economic dispatch of power grid. This paper focuses on the dynamic economic dispatch of power grid with multiple wind farms. First, the Copula theory is introduced to develop the model of joint distribution for the output power of multiple wind farms. Secondly, a stochastic optimization model of the 24 hour dynamic economic dispatch is established. In order to deal with the stochastic characteristics of wind output power, a two-stage compensation algorithm is applied and the original model is transformed into a two-stage model. The first-stage model is of constraints about conventional variables, and the expected compensation value is added to the objective function. The second-stage model is constrained by random variables, and its objective function is to minimize the expected compensation value. The optimal solution is obtained by the alternating iteration of the two models. The proposed model is finally verified by the IEEE 118-bus system and an actual provincial power grid.