Hybrid Renewable Energy Resources Utilizing Hybrid PSO and Cuckoo Search Algorithm

Abstract

Renewable Energy Sources (RES) are the catalysts for climate change for these environmental challenges. From the Philippine Development Plan from 2017-2022, sustainable development supports required massive investment and fast track to improve power generation using renewable energy sources. The system’s reliability is still a challenge due to its intermittent supply of energy dependence on nature. Hybrid Renewable Energy System (HRES) is widely known today to ease effect and balance energy supply. HRES requires a wide selection of techniques to be used to satisfy the demand of a given grid. A recent study was conducted calculating the values of Levelized Cost of Energy (LCOE) using optimization technique; result yields with LCOE and LPSP higher than the current values. This study developed software for Hybrid Renewable Energy Systems in Pamarawan Island that will reduce the Levelized Cost of Energy using Hybrid PSO and Cuckoo Search Algorithm. The result appears that the HPSOCS Algorithm gives an optimized solution that leads to a value of LCOE that is within the acceptable range of the current actual value. For the twenty independent runs of the program, the average value of LCOE is 0. 1508 ${\$}$/kWh, and LPSP is 0.1096 or 10.96%. The researcher assessed the level of significance of the hypothesis using a right-tailed test for the values of LCOE. In all instances, all the observed values of LCOE using Hybrid PSOCS are lower than those of LCOE using HPSOGSA. This means that the Hybrid PSOCS yields LCOE significantly better than HPSOGSA, with a 39% relative difference at a 5% significance level. Thus, the algorithm used has an excellent performance in the optimization method of HRES. Also, the HRES software calculator can be used in sizing HRES in different locations in need of sustainable energy sources.