随着风电大规模并网,其不确定性给电力系统经济调度带来了新的挑战。文中利用通用分布模型拟合不同风电功率预测水平下的实际风电功率分布,并以此建立了考虑风电低估、高估成本的日前动态经济调度的随机优化模型。通过对目标函数和约束条件的转化与分析,将随机优化模型转化为一个非线性凸优化问题。结合二次规划算法和内点法,提出了一种两阶段优化算法用以求解对应的经济调度问题。最后,在含风电场的IEEE 30节点系统上,验证了所提基于通用分布的随机动态经济调度方法的有效性。
With large-scale wind power integrated into power systems,the uncertainty of wind power has brought new challenges to the economic dispatch of power systems.Versatile probability distribution is used to fit the distribution of actual wind power at different forecast levels.And based on it,a stochastic day-ahead dynamic economic dispatch model is developed considering both lower and higher evaluated penalty costs of wind power.By transformation and analysis of the objective function and the constraints,a stochastic optimization model is ultimately transformed into a nonlinear convex optimization problem.Combined with quadratic programming algorithm and interior point method,a two-stage optimization algorithm is proposed to solve the economic dispatch problem.Finally,simulation is implemented on the IEEE 30-bus system with a wind farm and the results verify the effectiveness of the proposed stochastic dynamic economic dispatch method.