Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study
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...
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MDPI AG
2025-06-01
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| author | Andrés Bernabeu-Santisteban Andres C. Henao-Muñoz Gerard Borrego-Orpinell Francisco Díaz-González Daniel Heredero-Peris Lluís Trilla |
| author_facet | Andrés Bernabeu-Santisteban Andres C. Henao-Muñoz Gerard Borrego-Orpinell Francisco Díaz-González Daniel Heredero-Peris Lluís Trilla |
| author_sort | Andrés Bernabeu-Santisteban |
| collection | DOAJ |
| description | 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 EUR 24.2 through the efficient scheduling of electric vehicle fleet charging. |
| format | Article |
| id | doaj-art-163e8b3d85f94e29b2d795690f03691e |
| institution | Matheson Library |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-163e8b3d85f94e29b2d795690f03691e2025-07-11T14:36:27ZengMDPI AGApplied Sciences2076-34172025-06-011513735110.3390/app15137351Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case StudyAndrés Bernabeu-Santisteban0Andres C. Henao-Muñoz1Gerard Borrego-Orpinell2Francisco Díaz-González3Daniel Heredero-Peris4Lluís Trilla5Catalonia Institute for Energy Research (IREC), 08930 Sant Adrià del Besos, SpainCatalonia Institute for Energy Research (IREC), 08930 Sant Adrià del Besos, SpainCentre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona (ETSEIB), Universitat Politècnica de Catalunya, 08028 Barcelona, SpainCentre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona (ETSEIB), Universitat Politècnica de Catalunya, 08028 Barcelona, SpainCentre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona (ETSEIB), Universitat Politècnica de Catalunya, 08028 Barcelona, SpainCatalonia Institute for Energy Research (IREC), 08930 Sant Adrià del Besos, SpainThe 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 EUR 24.2 through the efficient scheduling of electric vehicle fleet charging.https://www.mdpi.com/2076-3417/15/13/7351energy management systemelectric vehicleindustryoptimizationdigital twin |
| spellingShingle | Andrés Bernabeu-Santisteban Andres C. Henao-Muñoz Gerard Borrego-Orpinell Francisco Díaz-González Daniel Heredero-Peris Lluís Trilla Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study Applied Sciences energy management system electric vehicle industry optimization digital twin |
| title | Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study |
| title_full | Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study |
| title_fullStr | Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study |
| title_full_unstemmed | Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study |
| title_short | Energy Management System for Renewable Energy and Electric Vehicle-Based Industries Using Digital Twins: A Waste Management Industry Case Study |
| title_sort | energy management system for renewable energy and electric vehicle based industries using digital twins a waste management industry case study |
| topic | energy management system electric vehicle industry optimization digital twin |
| url | https://www.mdpi.com/2076-3417/15/13/7351 |
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