Spatial Interpolation Long-Term Patterns Capacity of Renewable Energy in Sumatera

Abstract

Indonesia possesses considerable capacity for renewable energy as a result of its plentiful natural resources, including geothermal, solar, wind, hydro, and biomass. Nevertheless, the nation's existing energy composition is predominantly dependent on non-renewable resources, with fossil fuels constituting approximately 95% of its overall energy consumption. Nevertheless, Indonesia has made notable advancements in augmenting its renewable energy output in recent years. Nevertheless, there is still a lack of clarity about the identification of suitable regions for the installation of solar power plants (PLTS) in order to facilitate the development of solar energy. This study employed a methodology to investigate and forecast the solar energy potential in Sumatra, Indonesia. The data utilized consists of MERRA-2 reanalyzing information spanning from 1980 to 2019, collected on a daily basis. The data is analyzed and shown using IDW (Inverse Distance Weighting) and ARIMA techniques to visualize the spatial variation of solar energy potential in Sumatra. ARIMA is employed as a supplementary method to the interpolation technique in order to get long-term projections of solar energy potential for the period spanning from 2020 to 2029. The analysis of the best interpolation method for estimating solar energy potential reveals that the IDW approach with a power of 5 yields the most accurate findings, with an RMSE value of 28.33. For long-term prediction of solar potential in Aceh province, the ARIMA (1,0,0) method is recommended, which has a MAPE value of 0.0219. The findings indicated that Lampung and Bengkulu frequently experience the distribution of solar energy with an intensity ranging from 1400 to 1450 kWh. In addition, the forecast of the potential over Sumatera Island yielded encouraging results using the GAM model, with a root mean square error (RSME) rate of 0.05103.