Optimal planning of solar energy using a sensitivity factor for rural electricity needs in an off-grid system (case study: Sebesi Island, South Lampung, Indonesia)

Small islands in Indonesia usually have a million beauty and extraordinary natural wealth. However, the development of remote islands is prolonged due to the limited electricity supply on these islands. This limitation occurs because the island is far from the primary power grid or uses a diesel generator (DG). Using the DG will increase the cost of shipping fuel oil through limited sea transportation. Therefore, this study aims to conduct a feasibility study of a solar power plant to meet the electricity needs of Sebesi Island, South Lampung, Indonesia. The availability of solar Energy and limited battery life are the main challenges in providing solar Energy today. Therefore, this study also considers the uncertainty of resources by using the sensitivity factor. This research uses HOMER software. This study assumes operating reserve peak, operating reserve, solar reserve, and lifetime battery life to account for resource uncertainty. This method is very effective in overcoming operational limitations and problems. The research results show that the optimal peak operating reserve, operating reserve, solar reserve, and lifetime battery are 10%, 10%, 10–30%, and 5 years, respectively. To meet the daily electrical energy needs of 505. 1 kWh, the minimum net current cost (NPC) and energy cost (COE) are 1. 26 million and 0. 346 /kWh, respectively. Therefore, this research succeeded in finding a scenario that takes into account sensitivity factors that are more economical. Compared with a diesel generator (DG) with a capacity of 100 kW, the NPC and COE values are 1. 29 million and 0. 397 /kWh. Meanwhile, in terms of technology, solar power systems produce much more energy than DG. This system has an energy of 583, 316 kWh/year, while the DG system can produce an energy of 268, 469 kWh/year. As a result, this system can also reduce CO2 emissions by 241, 812 kg/year.