Size optimization of standalone wind-photovoltaics-diesel-battery systems by Harris hawks optimization (HHO): Case study of a wharf located in Bushehr, Iran

Abstract

The global increase in energy demand has led to a growing focus on renewable energy sources as a potential solution. This study examines the annual total cost of optimized off-grid hybrid multi-resource systems, considering various configurations of Wind Turbines (WT), Photovoltaics (PV), Diesel Generators (DG), and Batteries (Bat). The research focuses on an oil dock in Bushehr, Iran, as a case study. The optimization process employs the Harris Hawk Optimization (HHO) algorithm – which is used for the first time for hybrid configuration and optimal sizing in this paper-, a nature-inspired, population-based optimization technique. This algorithm’s performance is compared to conventional optimization methods to assess its efficiency. The study’s methodology involves: (1) Explaining the economic relationships for each energy source, (2) Formulating a cost function, (3) Using the HHO algorithm to minimize the total cost of the renewable energy-based hybrid systems. The HHO algorithm is inspired by the hunting behavior of Harris hawks, specifically their “wonder attack” strategy. This novel approach to optimization aims to find the most cost-effective configuration of energy sources for the given scenario. Key findings of the study include the HHO algorithm demonstrated superior efficiency compared to Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) across all configurations tested. The most cost-effective configuration was found to be a combination of photovoltaics, batteries, and diesel generators. This setup had the lowest total annual cost among all configurations examined. The optimal system consisted of 450 photovoltaic units, 9 battery units, and 2 diesel generator units, with a minimum annual cost of approximately $355,525. These results highlight the potential of the HHO algorithm in optimizing renewable energy systems and demonstrate the complex trade-offs between cost and environmental impact in hybrid energy configurations. The study contributes valuable insights to the field of renewable energy system design and optimization, particularly for off-grid applications in industrial settings.