考虑风速相关性的电力系统动态经济调度

随着并网风电场数量的增多和规模的扩大,风电功率的随机性以及各风电场之间的风速相关性对电网调度的影响不容忽视。针对多风电场的风速联合概率分布函数不易构造的问题,通过Nataf逆变换,获取具有相关性的多维风速样本。基于机会约束规划理论,建立了一定风险阈值下考虑风电成本和运行风险约束的多变量、非线性随机优化调度模型,有效地协调了系统经济性和安全性之间的矛盾。提出基于场景化理论的改进粒子群爬山混合算法用于模型求解,提高了模型求解速度并直观地反映出系统的最佳风险水平。以含风电场的IEEE 30节点系统为算例验证了所提方法的可行性和有效性。

Dynamic Economic Dispatch of Power System Considering the Correlation of the Wind Speed

With the increasing number and scale of wind farms, the impacts arising from the uncertainty of wind power are significant. According to the difficulty in constructing the probability distribution function of multi-wind speed, the sample space of correlative wind speed is generated by Nataf inverse transformation. A nonlinear multivariable optimization model under a certain risk threshold is established, based on the theory of chance-constrained programming. The scene theory and improved particle swarm optimization algorithm are integrated to solve the model fast, saving computational time and reflecting the best risk level directly. The simulation results of IEEE 30 bus system with two wind farms indicate the feasibility and efficiency of the proposed method.