Generation expansion planning incorporating the recuperation of older power plants for economic advantage

Abstract

As power plants age, they will gradually lose their reliability, economic viability, and productivity. They will also emit more carbon dioxide when producing electricity. This study has addressed the retirement and recuperation of the power plants in order to tackle the generation expansion planning (GEP) problem. Recuperation is a factor that benefits the power generating company both environmentally and economically. These requirements have increased the complexity of the GEP issue. Therefore, the utilization of optimization techniques is necessary to address these intricate, limited, and extensive issues. The GEP problem for the Tamil Nadu power system was solved in this study by using one of the most successful optimization techniques, namely particle swarm optimization (PSO), and its variations, such as cooperative coevolving particle swarm optimization (CCPSO) and opposition-based learning competitive particle swarm optimization (OBLCPSO). The real-world GEP problem has been resolved for planning horizons of seven years (2020–2027) and fourteen years (2020–2034). The outcomes showed that the CCPSO algorithm outperformed the competition. The most favorable results have been attained in scenario 4. Compared to the GEP problem without retirement and recuperation, the total cost has dropped by 11.07% and CO₂ emissions by 9.48% once retirement and recuperation are considered. According to the simulation results, retirement and recovery are taken into account in GEP, which considerably lowers overall costs and polluting emissions.

Graphical abstract