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A Comparative Study on Particle Swarm Optimization for Transmission Congestion Management

Patel Nilesh Kantilal, Bhavik N. Suthar


This research aims to propose solution to the issue of transmission congestion management based on optimal generation rescheduling using different variants of particle swarm optimization (PSO). In deregulated electricity market era, congestion management plays an essential role to accommodate all transactions within reliable system operations. Intending to reduce the congestion cost, optimum numbers of generators are selected based on generator sensitivity factor (GSF) to perform active power generation rescheduling. The capabilities of different variants of PSO viz. CPSO, TVIW-PSO, TVAC-TVIW PSO and RANDIW-PSO have been evaluated to deal with the challenge of transmission congestion management in pool electricity market model. The PSO variants have been tested on IEEE-39 bus and IEEE-118 bus test systems. The results demonstrate that RANDIW-PSO performs better in case of minimizing congestion cost along with satisfying system operational constraints. The work has also been extended for hybrid electricity market model with bilateral contracts. The scope of this research includes assistance to grid operator to manage transmission congestion in pool as well as hybrid electricity markets.


Keywords: Congestion management, generation rescheduling, generator sensitivity, particle swarm optimization, hybrid market

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Copyright (c) 2019 Journal of Power Electronics & Power Systems

eISSN: 2249–863X