考虑大停电风险的输电网扩展规划模型和算法

A Model and Algorithm for Transmission Expansion Planning Considering the Blackout Risk

基于自组织临界理论提出了一种考虑大停电风险的电网规划模型及其求解算法。该模型在传统规划模型的基础上,增加了预期负荷损失和幂率尾风险(power-law tail risk,PTR)等风险指标,从多个角度分析规划方案的可靠性。求解算法分为2个阶段,首先利用改进的粒子群(multi-objective particle swarm optimization,MOPSO)算法初步筛选出待选方案集;然后计算待选方案的风险指标,综合所有评估指标利用帕累托最优原则排序。改进的MOPSO算法采用有限容量精英库和全局引导者概率选择机制,有效平衡解的多样性和全局收敛速度。算例分析表明:所提方法可行有效;PTR是其他风险指标的有效补充,在电网规划中考虑PTR有利于降低规划方案的大停电风险;大停电风险并不总是随投资费用的增加而降低,利用优化算法可实现用少量增加的投资费用有效降低大停电风险。

According to self-organized criticality （SOC） theory, a model and its solving algorithm for transmission expansion planning （TEP） considering the blackout risk was proposed. Based on traditional TEP model, the proposed algorithm added the risk indices of expected load loss （ELL） and power-law tail risk （PTR） to analyze the reliability of TEP plans from multiple perspectives. The solving algorithm includes two stages, the first one employed the improved multi-objective particle swarm optimization （MOPSO） algorithm to select the candidate plans; the second one calculated the risk indices of these plans and sorted them by Pareto optimality based Oil all the assessment indices. The improved MOPSO algorithm, adopting the strategies of limited-capacity elite archive and probability selection of global guiders, effectively traded off the solutions diversity and the global convergence speed. Example analyses indicate that the proposed method is feasible and effective; PTR is an effective supplement to other risk indices, considering PTR in TEP helps to reduce the plans＇ blackout risk; the blackout risk does not always decrease with investment increasing, but it can be achieved by the optimization algorithm that a small amount of increasing investment can efficiently decrease the blackout risk.