考虑多风电场出力相关性的电力系统随机优化调度

摘要

考虑多风电场出力之间的尾部相关性,借助Gumbel-Copula函数构建多风电场出力的联合概率分布,提出含多风电场的电力系统随机优化调度模型.通过抽样平均近似(SAA)法处理机会约束条件,将随机优化问题转换为可计算的确定性非线性规划问题,并采用粒子群优化(PSO)算法进行求解.通过算例分析联合概率分布、机会约束置信水平和抽样次数对优化调度结果的影响,结果验证了基于Gumbel-Copula联合概率分布的随机优化调度的合理性.%With the consideration of the tail-dependent correlation of multiple wind farm power outputs,their joint probability distribution is characterized by Gumbel-Copula function and a stochastic optimal dispatch model of power system with multiple wind farms is proposed. The chance constraint is managed by SAA (Sample Average Approximation) and the stochastic optimization is thus transformed to the computable and deterministic non-linear programming,which is then solved by PSO(Particle Swarm Optimization) algorithm. The influence of joint probability distribution,chance constraint credit level and sample times on the results of optimal dispatch is analyzed by cases,which verifies the rationality of stochastic optimal dispatch based on Gumbel-Copula joint probability distribution.