改进粒子群优化算法的概率可用输电能力研究

研究了基于改进粒子群优化算法的概率可用输电能力的计算问题。建立了基于最优潮流的区域间可用输电能力模型；构造了适合可用输电能力研究的改进粒子群算法，并提出了自适应调整惯性权重的策略，该策略有效改善了算法的适应性和收敛速度；针对改进粒子群算法的搜索特点，动态调节罚函数。在此基础上对经模态分析方法选出的系统严重故障进行可用输电能力计算，并对各种故障出现概率和相应的可用输电能力进行概率统计分析，得到具有概率性质的可用输电能力。对IEEE-30节点系统的仿真计算验证了文中所提方法的合理性和有效性。

Study of Probabilistic Available Transfer Capability by Improved Particle Swarm Optimization

This paper carries out the comprehensive studies, which concerning the problem of probabilistic Available Transfer Capability (abr. ATC) computation based on the improved particle swarm optimization (abr. IPSO). Firstly, the mathematic model of ATC based on optimal power flow is constructed and a new method of improved particle swarm optimization which is adaptive for the model of ATC is presented. A new self-adaptive adjustment inertia-weighted strategy factor, which elevates the adaptability of PSO and accelerates convergence-speed of PSO, is proposed. On consideration of the search characteristics of particle swarm optimization (abr. PSO), penalty function is assigned dynamically. Secondly, ATC can be computed by IPSO after selection of critical contingencies by modal analysis method. Finally, through the probabilistic analysis based on the probability of each contingency and the value of ATC corresponding to each contingency, the probabilistic ATC can be computed. A case study of IEEE-30 bus system demonstrates the rationality and validity of strategies proposed in this paper.