Genetic algorithm based optimal sizing of PV-Diesel-Battery system considering CO₂ emission and reliability

The reliability system concern and CO₂ emission reduction are still the main targets of optimization problem in the hybrid generation system components. This paper utilizes Genetic Algorithm (GA) method to determine the optimal capacities of PV system, battery bank and diesel generator (DG) unit according to the minimum cost objective functions that relate to these two factors. In this study, the cost objective function includes the annual capital cost (ACC), annual operation maintenance cost (AOM), annual replacement cost (ARC), annual fuel cost (AFC), annual emission cost (AEC) and annual customer damage cost (ADC). The proposed method has been tested in the hybrid power generation system located in East Nusa Tenggara, Indonesia (latitude 09.30S and longitude 122.0E). To show the effectiveness of this method, three different crystalline Silicon PV module technologies: ASE-300 (mc-Si based EFG), Kyocera KC-120 (mc-Si based wafer) and AstroPower AP-120 (thin-film Si) were used. Simulation results show that the optimum configuration can be achieved using thin-film Si technology of PV modules, battery banks and diesel generator unit with capacities of 139,250× 120W, 5× 5MWh and 12MW, respectively. This study also reveals the importance of PV and battery systems in the hybrid generation system from economical, reliability and environmental point of views.