含风储联合系统的输电系统恢复协同优化决策理论与方法

Collaborative optimization of transmission power system restoration with the implementation of a wind-storage system is not only beneficial for the secure and fast restoration for an area where there are no conventional black-start generators or there isn’t enough black-start capacity, but also expands the actual application of a wind-storage system. In view of the defects of the existing power system restoration scheme in the optimization models and solution methods as well as the urgent need to explore the positive role of the wind-storage combined generation power system in accelerating the power system restoration, the optimal strategy of unit restoration sequence taking the time-varying characteristics of unit restoration time and line restoration time into account is studied based on the bi-level programming theory in this project. A collaborative optimization strategy of the wind-storage system and the unit recovery sequence is proposed based on the robust optimization theory. A dynamic optimization strategy of restoration path is proposed based on the risk theory. A load restoration strategy is proposed, taking the time series characteristics of cold loads pickup and dynamic restoration risks of paths into account. A collaborative optimization strategy of the wind-storage system and load restoration is proposed based on scenario analysis and Benders decomposition. The research outputs of this project will provide theoretical analysis and technical support for the participation of the wind-storage combined system in the power system restoration process, and improve the theories and methods of power system restoration strategies. They will be beneficial for the secure, reliable, fast restoration of actual power systems after a blackout.

含风储联合系统的输电系统恢复协同优化决策不仅可以实现无常规黑启动机组区域或黑启动能力不足区域在停电后的安全、快速恢复，而且扩展了风储联合系统的应用范围。鉴于现有恢复策略在优化模型和求解方法的缺陷以及探索风储联合系统对加速电力系统恢复的积极作用的迫切需求，本课题拟研究基于双层规划理论计及机组恢复时间时变特性和线路恢复时间的机组恢复顺序优化策略；提出基于鲁棒优化理论的风储联合系统与机组恢复顺序的协同优化策略；提出基于风险理论的电力系统恢复路径动态优化策略；提出计及冷负荷时序特性和动态路径恢复风险的负荷恢复策略；提出基于场景分析法和Benders分解法的风储联合系统与负荷恢复的协同优化策略。本课题的研究成果将为风储联合系统参与电力系统恢复提供理论分析与技术支撑，完善电力系统恢复策略理论与方法的研究，有助于实现安全、可靠、快速地恢复电力系统。

针对大停电事故后的电力系统恢复问题开展全面、深入和系统的研究，对加快电力设备和电力用户的恢复速度、减少停电损失，具有十分重要的意义。在此背景下，本项目研究了含风储联合系统的输电系统恢复协同优化决策理论与方法，取得的成果如下：1）提出了基于置信间隙决策理论的含风光储系统的机组启动次序优化策略，实现机组启动次序与关键恢复路径的协同优化，有效避免了因两者解耦导致机组启动次序无效或机组延迟启动的情况，提高了机组恢复策略的准确性和实用性。2）提出了考虑运行风险的电力系统恢复路径两阶段鲁棒优化策略，构建了基于凸包理论的二阶锥潮流方程，提高了模型的求解效率。所提出的模型充分考虑机组调度、线路恢复和负荷恢复的协同优化，在确保系统安全性的同时加快大停电后电力系统的恢复速度。3）提出了考虑变时步步长的负荷恢复双层优化策略。通过迭代求解上下层模型，可得到当前时步最短负荷恢复持续时间的最优负荷恢复方案。提出了储能实时调度模型进而减少风储联合系统实际出力与调度出力之间的误差，有助于加快负荷恢复进程。4）提出了计及冷负荷效应时变特性的含风储联合系统负荷恢复策略，其中将冷负荷效应描述为关于停电时间的线性表达式。提出了基于Benders分解的求解框架，其中子问题为风储联合系统优化调度模型，实现风储联合系统跟踪调度指令。所提出的策略提高了电力系统恢复过程中机组出力和负荷恢复量，加快了含风储联合系统的输电系统恢复速度。