Volume 18: Sustainable Energy Solutions for a Post-COVID Recovery towards a Better Future: Part I

Optimisation of a Grid-Connected Hybrid Renewable System at Peak Load Bader Alqahtani, Manosh C Paul, Jin Yang, Xiaolei Liu



In this study, a hybrid renewable energy system consisting of photovoltaics (PVs), wind turbines, bioenergy, and pumped hydropower energy storage (PHES) is proposed. This study aims to optimise the size of the hybrid system components based on peak periods to increase the reliability of the overall system performance. The non-dominated sorting genetic algorithm (NSGA2) optimization model is developed to minimise two main objectives: loss of power supply (LPSP) and loss of renewable energy (LORE). The input variables are the number of wind turbines, the number of solar modules, the number of pumps/generators, and the capacity of the upper reservoir of PHES. The novelty of this study is to develop a multi objectives optimisation model focusing on peak load period for long time assessment taking advantage of hybridisation dispatchable and non-dispatchable renewable sources to size renewable energy components accurately. The results reveal that increasing the number of PV modules and wind turbines improves the LORE while reducing the LPSP, as it covers more demand at a given period. The best solutions obtained for the LPSP and LORE are 5% and 5%, respectively. The entire system dispatchability might be improved by increasing bioenergy power plant and PHES capacity.

Keywords renewable/green energy resources, pumped hydropower energy storage (PHES), PV system

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