Novel Approach for Energy Balancing With Intermittent Renewable Energy Source Using Multi-Objective Genetic Algorithm

Abstract

Integrating renewable energy into existing power grids is essential to maintaining a balance between supply and demand. They ensure a stable and reliable energy supply by seamlessly adjusting to the variations in energy production and consumption. This study introduces an innovative approach to achieving energy balance by integrating floating photovoltaic (FPV) systems with hydropower. This combination addresses not only environmental concerns but also the issue of underproduction in hydropower dams. The primary objective is to find the most economical combination of components for a 100% hybrid renewable energy system using a Multi-Objective Genetic Algorithm (MOGA). The integrated system is projected to add 988,508 MWh of electricity to the grid each year, surpassing the required amount needed to meet demand. Despite some energy losses, the contribution of each system is derived from the optimization process, where the FPV system contributes approximately 29% of the total energy produced, while the hydroelectric system provides the remaining 71%. These percentages are based on the modeled energy output of the combined system in the study. The study highlights the consistency and reliability of the FPV source, emphasizing its low cost of energy (COE) and net present cost (NPC). Moreover, implementing a 166.3 MW FPV system significantly reduces 238,739 tons of CO2 emissions. By exploring this approach, ongoing research and development in renewable energy technologies can enhance efficiency, cost-effectiveness, and overall performance, leading to a more robust and sustainable energy balance.

Keywords

• Cost of energy
• floating photovoltaic system
• hybrid energy system
• hydropower
• net present cost