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Energy management system for renewable energy and electric vehicle-based industries using digital twins a waste management industry case study Bernabeu Santisteban, Andrés Henao Muñoz, Andrés Camilo Borrego Orpinell, Gerard Díaz González, Francisco Heredero Peris, Daniel Trilla Romero, Lluís Universitat Politècnica de Catalunya. Doctorat en Enginyeria Elèctrica Universitat Politècnica de Catalunya. Doctorat en Sistemes d'Energia Elèctrica Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica Universitat Politècnica de Catalunya. CITCEA-UPC - Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments Àrees temàtiques de la UPC::Enginyeria elèctrica Energy management system Electric vehicle Industry Optimization Digital twin The integration of renewable energy sources, battery energy storage, and electric vehicles into industrial systems unlocks new opportunities for reducing emissions and improving sustainability. However, the coordination and management of these new technologies also pose new challenges due to complex interactions. This paper proposes a methodology for designing a holistic energy management system, based on advanced digital twins and optimization techniques, to minimize the cost of supplying industry loads and electric vehicles using local renewable energy sources, second-life battery energy storage systems, and grid power. The digital twins represent and forecast the principal energy assets, providing variables necessary for optimizers, such as photovoltaic generation, the state of charge and state of health of electric vehicles and stationary batteries, and industry power demand. Furthermore, a two-layer optimization framework based on mixed-integer linear programming is proposed. The optimization aims to minimize the cost of purchased energy from the grid, local second-life battery operation, and electric vehicle fleet charging. The paper details the mathematical fundamentals behind digital twins and optimizers. Finally, a real-world case study is used to demonstrate the operation of the proposed approach within the context of the waste collection and management industry. The study confirms the effectiveness of digital twins for forecasting and performance analysis in complex energy systems. Furthermore, the optimization strategies reduce the operational costs by 1.3%, compared to the actual industry procedure, resulting in daily savings of €24.2 through the efficient scheduling of electric vehicle fleet charging. This research is part of Project PLEC2021-008152, funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR. Peer Reviewed Postprint (published version) 2025-06-30 Article Bernabeu Santisteban, A. [et al.]. Energy management system for renewable energy and electric vehicle-based industries using digital twins a waste management industry case study. «Applied sciences (Basel)», 30 Juny 2025, vol. 15, núm. 13, article 7351, p. 1-26. 2076-3417 https://hdl.handle.net/2117/439665 10.3390/app15137351 eng https://www.mdpi.com/2076-3417/15/13/7351 http://creativecommons.org/licenses/by/4.0/ Open Access Attribution 4.0 International 26 p. application/pdf Multidisciplinary Digital Publishing Institute