Smart feasibility optimization of hybrid renewable water supply systems by digital twin technologies: A multicriteria approach applied to isolated cities
Miguel Tavares, Modesto Pérez‐Sánchez, Armando Carravetta, Óscar E. Coronado-Hernández, Petra Amparo López Jiménez, Helena M. Ramos
Abstract
• Smart optimization to manage the energy production in Madeira Island • Machine learning applications for hybrid water-energy systems • Pumped-storage hydropower systems manage 130,000 m 3 each day, storing 25 MWh • Non annual emission of 18000 tonnes CO2 This research presents a multicriteria approach for the best hybrid water supply solution of a multipurpose Pumped-Storage Hydropower (PSH) system, using the Generalized Reduced Gradient (GRG) method in Solver, with the optimization process considering key factors, such as Net Present Value (NPV), the number of energy conversion devices, renewable energy production, source availability, reservoir capacities, topographic constraints, and energy tariffs. The methodology combines a literature review, methodological development, and machine learning applications for hybrid water-energy systems. Results indicate that solar-only solutions are insufficient in high hydropower potential scenarios while integrating wind turbines significantly enhances energy production and profitability by generating surplus energy for grid sales. The timing of energy sales and the incorporation of battery storage also impact NPV, which can exceed 180 million euros. Wind energy contributes to continuous profitability and optimized system performance, particularly in isolated regions. The PSH system can manage 130,000 cubic meters of water daily, storing 25 MWh of energy, and reducing CO 2 emissions by over 18,000 tonnes per year. These findings highlight the importance of renewables, such as wind energy, and effective operational management. It enhances the economic viability and environmental sustainability of hybrid water-energy systems.