Capacitated Location Allocation Problem of Solar Power Generation in Indonesia using Particle Swarm Optimization
Keywords:
Capacitated Location Allocation Problem, Solar energy, Simulated Annealing, Large Neighborhood Search, Particle Swarm OptimizationAbstract
Indonesia has abundant potential of solar energy. The decrease on cost of solar power generation components can bolster the development of solar power plants. Analysing the feasibility of using solar power plants as a primary source of renewable energy in Indonesia, especially in Sumatra Island, is important due to its geographical characteristics. One of important aspects in developing solar power plants is determining the suitable location of power plant and the allocation of the electricity generated to the regions. Therefore, this study considers the Capacitated Location Allocation Problem (CLAP) to determine the optimal placement of solar power plants in Sumatra Island, with the objective of minimizing investment and transmission costs. To address the problem, we explore three metaheuristics, namely Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Large Neighborhood Search (LNS). The results obtained by these metaheuristic methods show significant differences in cost, with SA providing the best solution with the lowest cost. By solving the CLAP to obtain optimal solar power plant placement, the investment and transmission cost can be minimized, while enhancing the region's resilience in the context of implementing distributed generation.
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Copyright (c) 2024 Arya Wijna Astungkatara, Hamzah Fath, Oktaviana Putri, Anak Agung Istri Anindita Nanda Yana, Nur Mayke Eka Normasari, Andiny Trie Oktavia, Achmad Pratama Rifai
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