Particle Swarm Optimization with Time Varying Acceleration Coefficients for Congestion Management

E. Muneender, D. Vinodkumar
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引用次数: 4

Abstract

This paper presents an application of Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) algorithm for Congestion Management (CM) using optimal re-scheduling of real power generation. The optimal rescheduling of powers in a pool model is formulated as a constrained nonlinear optimization problem. The PSO-TVAC algorithm is proposed to assess the generation re-schedule to relieve the congestion optimally. The generators participating in the congestion management are selected based on real power transmission congestion distribution factors (PTCDFs). The effectiveness of the proposed method has been tested on 39-bus New England Test system. The simulation experiments reveal that the proposed method performs better than conventional PSO.
时变加速系数粒子群算法在拥塞管理中的应用
提出了时变加速系数粒子群优化算法(PSO-TVAC)在实际发电最优调度的拥塞管理中的应用。将池模型中功率最优重调度问题表述为一个约束非线性优化问题。提出了PSO-TVAC算法来评估代重调度,以最优缓解拥塞。根据实际输电拥塞分配系数(PTCDFs)选择参与拥塞管理的发电机。该方法的有效性已在39总线新英格兰测试系统上进行了测试。仿真实验表明,该方法的性能优于传统的粒子群算法。
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