Techno economic assessment and ANFIS driven optimization for solar PV-biomass hybrid energy system

Abstract

This research project aims to design and evaluate a solar PV-biomass hybrid energy system for rural electrification in the Ugandan district of Kebisoni Rukungiri. The study uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) method to improve precision and modeling accuracy. Solar radiation levels and biomass sources are sourced from NASA's website and the Uganda Meteorological Center. MATLAB/Simulink tools are used to model and simulate various hybrid system setups. Results show trade-offs between cost of energy and net present value, with significant NPV reductions ranging from 68.75% to 77.95%. Comparisons with existing systems reveal substantial cost savings and potential financial gains. This cost-effective and sustainable approach to rural electrification offers a viable solution for meeting electricity demands in remote areas, fostering economic development and enhancing living standards.