基于粒子群算法的最接近稳态电压稳定分岔计算

Xiaoming Dong, Jun Liang, Xueqing Zhang, Hua Sun
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引用次数: 7

摘要

考虑稳态电压稳定性,连续潮流(CPF)工具计算的负荷裕度受到鞍节点分岔(SNB)和极限诱导分岔(LIB)两种约束。由于载荷边界是复杂的非凸边界,使得传统的最接近分岔方法更容易得到局部最接近解,而不是全局最接近解。本文提出了一种利用连续潮流和基于模拟退火的粒子群算法求解最接近分岔的新方法。组合方法可以在全局范围内搜索目标,并具有跳出局部极值的能力(概率)。通过对ieee5总线测试系统的实例分析表明,本文提出的方法对电力系统的稳态电压稳定性分析是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computation of closest steady state voltage stability bifurcation using PSO approach
Considering steady state voltage stability, load margin that calculated by continuation power flow (CPF) tool is limited by two constrains which are called saddle-node bifurcation (SNB) and limit induced bifurcation (LIB). The boundary of the load margin is complex and non-convex, so that the conventional approach for closest bifurcation is most likely to get a local closest solution instead of the global one. This paper presents a new approach, in which continuation power flow and particle swarm optimization (PSO) based on simulated annealing (SA) are both used to calculate the closest bifurcation. The combination approach can search the object in the global scope and have the ability (probability) to jump out of the local extreme value. Case study of IEEE 5 bus test system shows that, the approach presented in this paper is effective in analyzing steady state voltage stability of a power system.
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