基于最大容量流和定向二元粒子群优化的复合电力系统可靠性评估

M. Benidris, J. Mitra
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引用次数: 17

摘要

本文介绍了一种减少电力系统可靠性指标评估中搜索空间的新方法。提出了一种新的输电线路最大容量流公式,并将其用于截断状态空间来识别确定成功子空间和确定失败子空间。提出了一种基于“定向”二元粒子群优化(BPSO)的新算法,在状态空间的剩余部分搜索指定的成功或失败状态。剩余的子空间是系统相关的,对于具有高容量和高可靠性传输线的系统,与发电和负载水平相比,该子空间对系统可靠性的影响可以忽略,不会造成任何显著误差。这种方法非常简单直接,但却大大减少了计算时间。该方法通过计算系统各状态下各母线和母线之间的总可用载功率来推进。采用关联矩阵技术建立线路容量矩阵(LCM)。从LCM和系统状态(发电-输电-负荷)出发,计算可靠性指标。将该方法应用于IEEE RTS和改进的IEEE RTS两个系统,取得了良好的效果。
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Composite power system reliability assessment using maximum capacity flow and directed Binary Particle Swarm Optimization
This work introduces a new technique to reduce the search space in evaluating reliability indices of power systems. A new formulation for maximum capacity flow of the transmission lines was developed and used in truncating the state space to identify the definite success and definite failure subspaces. A new algorithm based on “directed” Binary Particle Swarm Optimization (BPSO) was developed to search for the designated success or failure states in the remaining part of the state space. The remaining subspace is system dependent, and in case of systems with high capacity and reliability transmission lines in comparison with generation and loading levels, the effect of this subspace on system reliability can be ignored without causing any significant error. This method is very simple and straight forward, yet it reduces the computational time significantly. The method progresses by calculating the total available power carrying capability at every bus and between buses for every system state. Incidence matrix technique was used in building Line Capacity Matrix (LCM). From the LCM and system state (Generation-Transmission-Load), reliability indices can be calculated. This method was applied on two systems, the IEEE RTS and the modified IEEE RTS and it gave promising results.
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