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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ44813

Application of Cognitive Optimization Algorithms to Solve Generation Expansion Planning Problem by Considering the Recuperation for Aged Thermal Plants

A.Arun Kumar, B.V. Manikandan, S. Kannan, A. Bhuvanesh


Power plant recuperation is conventionally designed for old units that can be upgraded to yield additional capacity, and intends to extend their life. Recuperation procedure depends on many physical factors such as generating unit types, locations, finance etc. In this study, Generation Expansion Planning (GEP) problem has been solved by considering the retirement and recuperation of thermal power plants. Particle Swarm Optimization (PSO) and Local Stochastic Search Particle Swarm Optimization (LSSPSO) algorithms have been applied to solve the GEP problem by considering the objective functions such as minimization of cost, minimization of emission and maximization of reliability. The real-world power system of Tamil Nadu, an Indian state has been considered for investigation. The problem has been solved for 7-year (till 2027) and 14-year (till 2034) planning horizons for four different scenarios. The results show that the combined consideration of recuperation and retirement of thermal power plants considerably reduces the cost of planning and the emission.


Thermal Units, Recuperation, Generation Expansion Planning, Least Cost, Minimum CO2Emission, Tamil Nadu

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