基于可信性理论的含直流落点系统风电与负荷协调恢复优化

在高风电占比的交直流混联电力系统中,大停电后快速恢复负荷需要风电与常规电源、直流输电系统共同支撑,但风电的不确定性阻碍了其在恢复中应用。考虑风电与负荷的不确定性,引入风电场出力和负荷恢复量的模糊模型,基于可信性理论,建立风电与负荷协调恢复的模糊机会约束规划模型,在控制频率与备用风险水平基础上,优化风电与负荷接入效益。采用模糊机会约束的清晰等价类方法,将模糊模型转化为确定性的混合整数线性规划模型,保证了求解效率,满足在线快速决策的要求。算例表明该方法能够平衡风电、负荷与常规电源在多阶段恢复过程中的效益与安全,对风电接入具有更好的适应性。

Wind Power-load Coordinated Restoration Optimization of Power System With DC Terminal Location Based on Credibility Theory

In an AC/DC hybrid power system with high proportion of wind power, rapid load restoration after blackout requires participation of both wind power, conventional generators and DC system. But uncertainty of wind power hinders its application in this restoration. This paper proposed a fuzzy chance constrained programming model for wind power-load coordinated restoration optimization, in which the load and wind power were expressed as fuzzy parameters for taking uncertainty of wind farms and load into account according to credibility theory. In this model, the objective function was to optimize the benefits of load restoration with the constraints of frequency security and reserve risk level. Furthermore, the fuzzy chance constraints including fuzzy parameters were turned into their clear equivalent forms. In this way, the load restoration model could be transformed to a mixed integer linear programming model, which would be solved with deterministic solution and dramatically improve computation efficiency. Case studies show that the proposed model can balance the benefit and security of wind power, load and conventional sources in multi-stage load restoration, and the decision results are more suitable for load restoration optimization for power system with high wind power penetration.