Design optimization of a stand-alone green energy system of university campus based on Jaya-Harmony Search and Ant Colony Optimization algorithms approaches

• Published in: Energy (Oxford) Vol. 253; p. 124089
• Main Authors: Güven, Aykut Fatih, Yörükeren, Nuran, Samy, Mohamed Mahmoud
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.08.2022; Elsevier BV
• Subjects: Algorithms; Alternative energy sources; ant colonies; Ant colony optimization; Ant colony Optimizer algorithms; batteries; Clean energy; cost effectiveness; Design optimization; Diesel generators; Distributed generation; electric power; Electrical loads; energy; Energy demand; Energy management; Energy resources; Energy sources; generators (equipment); Green energy; Harmony Search algorithms; Hybrid systems; Installation costs; Jaya algorithms; Photovoltaic cells; Photovoltaics; Power; Power flow; Renewable energy; Renewable resources; Sizing; solar collectors; system optimization; Techno-economic optimization; Turbines; Wind power; Wind turbines; Ant colony Optimizer algorithms; Techno-economic optimization; Jaya algorithms; Energy management; Harmony Search algorithms
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2022.124089

The use of renewable energy resources in the production of electrical energy is becoming prevalent due to the decreasing installation costs of these resources and increasing environmental concerns. A Hybrid Renewable Energy System (HRES) is beneficial for meeting load demands, but optimal sizing is the main problem in the process of obtaining a cost-efficient system based on certain load demands and techno-economic parameters. In this article, the Harmony Search (HS) algorithm was used for the optimal sizing of components and compared to other methods. The HRESs consisted of photovoltaic (PV), wind turbine, battery, diesel generator and inverter components. A powerful rule-based energy management scheme was introduced to manage the power flow between system parts which constitute the microgrid that will minimize the annual system cost and reliably meet the energy demand. The decision variables for this optimization were the PV panel power, wind power, and the number of batteries. Simulation results revealed that HS provided the optimum sizing among the other methods including HOMER, Ant Colony Optimizer and Jaya. The time performances of the algorithms were also examined, and the HS algorithm had better performance and convergence properties. The optimization process was programmed using the MATLAB simulation package. [Display omitted] •The optimum hybrid system design for hourly varying load demands was examined.•Real time field meteorological data of solar, wind and temperature has been used.•Sustainable development and uninterrupted power supply assured from the analysis.•This article focuses on sizing, optimization, control, and energy management.