计及风电备用容量与需求响应的多备用资源鲁棒优化

Robust Optimization of Multiple Reserve Resources Considering Reserve Capacity of Wind Power and Demand Response

为缓解多重不确定性因素造成的系统运行与备用压力,提出了一种计及风电备用容量与需求侧响应的日前-日内两阶段多备用资源鲁棒优化模型。一方面,为充分发挥风电场与需求侧的备用容量,提高系统运行与备用的灵活性,分别对风电场备用与需求侧备用进行建模;另一方面,基于鲁棒优化模型对系统多种备用资源进行优化,保障电网在最恶劣运行工况下的安全可靠运行,提升了系统的鲁棒性。采用列和约束生成算法对两阶段鲁棒优化问题进行了求解。修改的IEEE RTS-79测试系统算例验证了所提模型与算法的有效性。结果表明,协同优化多种备用资源可以提升电力系统的运行灵活性,促进风电的消纳;同时,通过调节鲁棒模型中不确定性限值的大小,可以实现系统运行鲁棒性与经济性的平衡。

To alleviate the system operation and reserve scheduling pressures caused by multiple levels of uncertainty,a two-stage robust optimization model of multiple reserve resources is proposed,which considers the reserve capacity of wind power and demand response.On one hand,to make full use of the wind farm and demand reserve capacity and improve the flexibility of system operation,the reserve capacity provided by wind farm and demand side is modeled,respectively.On the other hand,based on the robust optimization model,multiple reserve resources are co-optimized to ensure the safe and reliable operation of power grid in the worst operation conditions,thus improving the robustness of power system.The two-stage robust optimization problem is solved by the column and constraint generation(C&CG)algorithm.Simulation results on the modified IEEE RTS-79 test system verify the effectiveness of the proposed model and algorithm.The results show that the co-optimization of multiple reserve resources can improve the operation flexibility of power system and promote wind power consumption.At the same time,by adjusting the uncertainty set of the robust model,the balance between the robustness and economic efficiency of the system can be achieved.