基于信息间隙决策理论的电网负荷恢复鲁棒优化

停电电网的恢复过程中,负荷恢复的不确定性可能影响电网恢复过程的安全,需要在负荷恢复中考虑负荷的不确定性。考虑到准确的负荷不确定性分布模型难以获取,文中提出了基于信息间隙决策理论(IGDT)的电网负荷恢复鲁棒优化方法,使负荷恢复方案在负荷波动范围内均能满足要求,而无需已知负荷的不确定性分布。首先,基于IGDT,将确定性负荷恢复优化模型转变为在负荷波动范围内均能达到最低恢复要求的鲁棒优化模型,同时综合考虑负荷恢复过程中的负荷最大恢复量、单次最大投入量、电网潮流等约束条件,再利用人工蜂群算法对优化模型进行求解,最后以新英格兰系统和江苏系统为例验证了所提方法的有效性。

Robust Restoration Method for Power System Load Based on Information Gap Decision Theory

Owing to the effect of uncertainties of load restoration on the power system security in the restoration process, it is necessary to consider the uncertainties during restoration. Afraid it''s hardly practical to obtain an accurate model of load uncertainty distribution, a network load restoring robust optimization method based on the information gap decision theory(IGDT)is proposed. This will enable the load restoring scheme to always meet the requirements within the range of fluctuation without prior knowledge of load uncertainty distribution. According to IGDT, the deterministic optimization model is reformed to a robust model, which can always achieve the minimum restoration object in the range of load fluctuation. Meanwhile, the maximum capacity of load restoration constraints, the maximum capacity of load restoration at each time step, power flow constraint and other constraints are taken into account comprehensively. The artificial bee colony(ABC)algorithm is also used to solve the optimization problem. Finally, numerical tests on a New England system and on Jiangsu power grid are used to demonstrate the effectiveness of the proposed method.