Algorithms (Jun 2024)
Multi-Criteria Decision Support System for Automatically Selecting Photovoltaic Sets to Maximise Micro Solar Generation
Abstract
Technological advancements have improved solar energy generation and reduced the cost of installing photovoltaic (PV) systems. However, challenges such as low energy-conversion efficiency and the unpredictability of electricity generation due to shading or climate conditions persist. Despite decreasing costs, access to solar energy generation technologies remains limited. This paper proposes a multi-criteria decision support system (MCDSS) for selecting the most suitable PV set (comprising PV modules, inverters, and batteries) for microgrid installations. The MCDSS employs two multi-criteria decision-making methods (MCDM) for analysis and decision-making: AHP and TOPSIS. The system was tested in two case studies: Barreiras, with a global efficiency of 14.4% and an internal rate of return (IRR) of 56.0%, and Curitiba, with a worldwide efficiency of 14.8% and an IRR of 52.0%. The research provided a framework for assessing and selecting PV sets based on efficiency, cost, and return on investment. Methodologically, it integrates multiple MCDM techniques, demonstrating their applicability in renewable energy. Managerially, it offers a practical tool for decision-makers in the energy sector to enhance the feasibility and attractiveness of microgeneration projects. This research highlights the potential of MCDSS to improve the efficiency and accessibility of solar energy generation.
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