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All Journal Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Hadi, Husam Ali
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Journal : Journal of Robotics and Control (JRC)

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Using Grey Wolf Optimization Algorithm and Whale Optimization Algorithm for Optimal Sizing of Grid-Connected Bifacial PV Systems Hadi, Husam Ali; Kassem, Abdallah; Amoud, Hassan; Nadweh, Safwan; Ghazaly, Nouby M.
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21777

Abstract

The shift towards renewable energies is driven by the shortage of fossil fuels for electricity generation and the associated harmful impacts. Grid-connected PV systems are a reliable and effective choice for power production across different uses, making them a key player in the global renewable energy landscape. Consequently, the careful selection of components for these systems is a crucial and widely studied aspect in this area of research. This paper introduced using gray wolf optimization algorithm GWO whale optimization algorithm WOA for determining the optimal number of grid - connected bifacial photovoltaic PV systems in Babylon Hilla. The considered factors included available space, desired energy production, radiation, dihedral factor, budget constraints, and grid connectivity requirements. The mathematical formulation of the problem and implementation details of the algorithms are presented. In addition, two cases studied are performed one for a residential area, and the other for a single house. The results demonstrated the efficiency and effectiveness of both algorithms in identifying optimal solutions for determining the size of systems in the area under study. However, the WOA surpassed the GWO in meeting the optimization criteria. The proper selection of these systems resulted in higher power generation, lower costs, improved energy management, and the advancement of sustainable solar energy solutions.
Using Imperialist Competitive Algorithm Powered Optimization of Bifacial Solar Systems for Enhanced Energy Production and Storage Efficiency Hadi, Husam Ali; Kassem, Abdallah; Amoud, Hassan; Nadweh, Safwan; Ghazaly, Nouby M.; Abdulhasan, Mahmood Jamal
Journal of Robotics and Control (JRC) Vol 5, No 4 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i4.22100

Abstract

Interest in renewable energy has grown due to increased environmental awareness and concern about climate change. Among the various renewable energy technologies, grid-connected bifacial PV systems are particularly important due to their higher efficiency compared to conventional systems. However, maximizing energy harvesting and storage efficiency remains a challenge for these systems, requiring the use of an efficient charge controller and an appropriate battery. The process of setting charge controller parameters and selecting the best storage technology is complex and requires a thorough study of various operating conditions. The main research contribution of this paper is the development of an efficient optimization methodology to increase the energy production and storage efficiency of the studied systems using optimization algorithms. The imperialist competitive algorithm (ICA) is used in the system design to improve performance through optimal adjustment of charge controller parameters and selection of appropriate storage technology. This decision was based on factors such as energy production from PV panels, energy consumption from loads, and energy storage in batteries. Performance is also evaluated using both the flower pollination algorithm (FPA) and Gray Wolf optimization (GWO) algorithms. The study evaluated system performance by analyzing energy production, storage efficiency, and cost effectiveness. The results showed that the ICA algorithm is effective in improving energy production and storage, resulting in higher energy output, better battery efficiency, and lower system costs. In addition, lithium-ion batteries were identified as the best storage technology. This research demonstrates the potential of the ICA approach to increase efficiency and reduce costs in the PV systems.
Co-Authors Abdulhasan, Mahmood Jamal Amoud, Hassan Ghazaly, Nouby M. Kassem, Abdallah Moubayed, Nazih Nadweh, Safwan