Multi-Objective Optimization of Smart Integrated Renewable Energy Systems (SIRES): A Web Tool Approach

Rural electrification initiatives often focus solely on providing electricity access, overlooking other essential needs such as water and cooking energy. This research introduces the Smart Integrated Renewable Energy System (SIRES), a comprehensive solution that addresses the diverse energy, water, and cooking requirements of rural areas. A comparative analysis between SIRES and conventional microgrids is conducted, considering social, economic, and environmental metrics such as Human Development Index (HDI) and carbon emissions. Using Multi-Objective Optimization (MOO) with the NSGA-II genetic algorithm, this study identifies the optimal system configuration based on cost, reliability, and environmental impact. To facilitate decision-making, a user-friendly, web-based optimization tool has been developed using the Python-Django framework, enabling users to input community-specific data for tailored recommendations. By optimizing renewable energy resources and providing a comparative analysis with traditional microgrids, this research outlines effective strategies for enhancing rural living standards while minimizing environmental impact and costs.