Least Cost Vehicle Charging in a Smart Neighborhood Considering Uncertainty and Battery Degradation
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| Publicado en: | Batteries vol. 11, no. 3 (2025), p. 104 |
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| Otros Autores: | , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 024 | 7 | |a 10.3390/batteries11030104 |2 doi | |
| 035 | |a 3181371213 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Schade, Curd |u Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Alfred Getz Veg 3, 7491 Trondheim, Norway<email>parinaz.aliasghari@ntnu.no</email> (P.A.); ; Workgroup for Infrastructure Policy (WIP), Straße des 17. Juni 135, 10623 Berlin, Germany | |
| 245 | 1 | |a Least Cost Vehicle Charging in a Smart Neighborhood Considering Uncertainty and Battery Degradation | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The electricity landscape is constantly evolving, with intermittent and distributed electricity supply causing increased variability and uncertainty. The growth in electric vehicles, and electrification on the demand side, further intensifies this issue. Managing the increasing volatility and uncertainty is of critical importance to secure and minimize costs for the energy supply. Smart neighborhoods offer a promising solution to locally manage the supply and demand of energy, which can ultimately lead to cost savings while addressing intermittency features. This study assesses the impact of different electric vehicle charging strategies on smart grid energy costs, specifically accounting for battery degradation due to cycle depths, state of charge, and uncertainties in charging demand and electricity prices. Employing a comprehensive evaluation framework, the research assesses the impacts of different charging strategies on operational costs and battery degradation. Multi-stage stochastic programming is applied to account for uncertainties in electricity prices and electric vehicle charging demand. The findings demonstrate that smart charging can significantly reduce expected energy costs, achieving a 10% cost decrease and reducing battery degradation by up to 30%. We observe that the additional cost reductions from allowing Vehicle-to-Grid supply compared to smart charging are small. Using the additional flexibility aggravates degradation, which reduces the total cost benefits. This means that most benefits are obtainable just by optimized the timing of the charging itself. | |
| 653 | |a Arbitrage | ||
| 653 | |a Electricity | ||
| 653 | |a Energy costs | ||
| 653 | |a Costs | ||
| 653 | |a Market prices | ||
| 653 | |a Buildings | ||
| 653 | |a Aging | ||
| 653 | |a Electric vehicles | ||
| 653 | |a Vehicle-to-grid | ||
| 653 | |a Renewable resources | ||
| 653 | |a Electricity pricing | ||
| 653 | |a Stochastic models | ||
| 653 | |a Electric power demand | ||
| 653 | |a Energy storage | ||
| 653 | |a Smart grid | ||
| 653 | |a Operating costs | ||
| 653 | |a Alternative energy sources | ||
| 653 | |a Degradation | ||
| 653 | |a Neighborhoods | ||
| 653 | |a Uncertainty | ||
| 653 | |a Electric vehicle charging | ||
| 653 | |a Battery cycles | ||
| 653 | |a Stochastic programming | ||
| 653 | |a Electric power distribution | ||
| 700 | 1 | |a Aliasghari, Parinaz |u Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Alfred Getz Veg 3, 7491 Trondheim, Norway<email>parinaz.aliasghari@ntnu.no</email> (P.A.); ; Workgroup for Infrastructure Policy (WIP), Straße des 17. Juni 135, 10623 Berlin, Germany | |
| 700 | 1 | |a Ruud Egging-Bratseth |u SINTEF Industry, Sustainable Energy Technology, Richard Birkelands vei 2B, 7034 Trondheim, Norway | |
| 700 | 1 | |a Pfister, Clara |u Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Alfred Getz Veg 3, 7491 Trondheim, Norway<email>parinaz.aliasghari@ntnu.no</email> (P.A.); ; Workgroup for Infrastructure Policy (WIP), Straße des 17. Juni 135, 10623 Berlin, Germany | |
| 773 | 0 | |t Batteries |g vol. 11, no. 3 (2025), p. 104 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3181371213/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3181371213/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3181371213/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |