SPATIAL MODELING OF MULTI-SCENARIO OPTIMAL SOLAR PV POWER PLANT DISTRIBUTION TO SUPPORT INDONESIA'S CLEAN ENERGY ACHIEVEMENT TARGETS

Abstract

The increasing population brings the increasing energy demand. The increasing production of fossil energy makes many gas emissions. This causes some effect like global warming. The production of clean energy concerns the world government. Solar energy has great attention from many countries worldwide, seeing the potential of the energy produced, the ease of installation process, and the small risk of damage. The potential of solar energy in Indonesia itself reaches 4.8 KWh/m2 or equivalent to 112,000 GWp. Currently, the Indonesian government has a target for constructing solar power plants in 2025 of 0.87 GW or around 50 MWp/year. The absence of research on determining the appropriate location based on multiple aspects is one of the obstacles in planning the construction of a solar PV power plant. Good planning is needed to determine the management and installation of an optimum and sustainable solar PV power plant. This research aims to develop an effective and efficient multi-scenario spatial model for the distribution of Solar PV (Photovoltaic) power plant development in Indonesia. The novelty in the study of the distribution of solar energy potential integrates meteorological and Geographic aspects and socio-economic aspects. The integration of dynamic multi-spatial data is used to determine the location of the development of solar power plants. Meteorological data is used to calculate potential energy, socio-economic data is used to determine the location for energy demand, and geographic aspect is used to know the suitable environment to install solar PV. The output of this research is the location of the priorities for the development of communal solar power plants in Indonesia. The distribution of effective Solar PV power plant development in Indonesia using a multi-scenario spatial model is divided into five suitability classes. The percentage of suitability class is 0.2% very low class, 3.5% low, 32.4% medium 56.9% high class, and very high 7%. The result is published in WebGIS that can access in link http://bit.ly/ModelPLTSIndonesia. It is hoped the results of this research can be used as material for consideration and one of the solutions for policymakers in making decisions regarding the development of communal solar power plants in Indonesia.