Optimal sizing of PV/WT/CSP/TES/HFC-based hybrid renewable energy systems

Abstract

In recent times continuous increases in fuel prices and greenhouse gas emissions have demanded the transition to a 100% renewable energy system. However, with the increase of renewable sources requirement for battery storage systems also increases. Battery storage is making hybrid systems expensive and increasing their carbon footprint. One another hindrance to using solar power is their low reliability in large-scale use. This study aims to explore and analyze the optimal sizing techniques for a system consisting of photovoltaic (PV), wind turbines (WT), concentrated solar power (CSP), thermal energy storage (TES), and hydrogen fuel cells (HFC) in order to achieve efficient, reliable, and cost-effective designs of hybrid renewable energy systems. The primary objective of optimal sizing is to balance the energy supply and demand while considering the availability and intermittency of renewable energy resources. This involves a thorough analysis of the potential energy generation from PV, WT, and CSP systems. In this study, loss of power supply probability (LPSP) is used for ensuring power supply and a new index DLP is proposed to minimize the dump load requirement. To achieve optimal sizing, modeling and simulation techniques are employed in the MATLAB platform. This study uses one of the most popular metaheuristic optimization technique PSO (particle swarm optimization) and compares the result with two recently proposed optimization algorithm, Pelican optimization algorithm and the Dandelion optimization algorithm. The study shows Dandelion optimization algorithm gives the best result for PV/WT/CSP/TES/HFC configuration. In conclusion the integration of PV, WT, CSP, TES, and HFC technologies in hybrid systems presents a promising pathway toward achieving a cleaner, efficient and more sustainable energy future