Optimization of a Hybrid Renewable Energy System Based on Meta-Heuristic Optimization Algorithms

Islands represent strategic platforms for exploring and exploiting marine resources. This article presents a hybrid renewable electric system (HRES) designed to power the island communities of Djerba in Tunisia. The system integrates photovoltaic panels, wind turbines, tidal turbines, hydraulic systems, biomass, and batteries, taking into account available climatic and land resources. A multi-objective optimization method is proposed for sizing this system to minimize power loss and energy costs. Two optimization algorithms, MOPSO (Multi-Objective Particle Swarm Optimization) and SSO (Social Spider Optimization) have been used to solve this problem. MATLAB simulations show that MOPSO offers better convergence and coverage than SSO. The results confirm the viability of the proposed algorithm and method for optimal sizing. In addition, they enable an in-depth analysis of the electrical production and economic benefits associated with the various system components.

@article{Ouederni2024,
  title     = {Optimization of a Hybrid Renewable Energy System Based on Meta-Heuristic Optimization Algorithms},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {7},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Ramia Ouederni and Bechir Bouaziz and Faouzi Bacha},
  doi       = {10.14569/IJACSA.2024.0150779},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150779}
}