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Self-sufficiency and charger constraints of prosumer households with vehicle-to-home strategies

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  • Rücker, Fabian
  • Schoeneberger, Ilka
  • Wilmschen, Till
  • Sperling, Dustin
  • Haberschusz, David
  • Figgener, Jan
  • Sauer, Dirk Uwe

Abstract

In recent years, the market of electric vehicles has been growing strongly. This growth is accompanied by discussions on vehicle-to-home strategies that allow households with a photovoltaic system and an electric vehicle both to charge the vehicle with solar energy and to supply energy from the vehicle to the household. However, vehicle-to-home technology is still not yet widely implemented in prosumer households and there is still little literature about the impact of technological constraints given by the hardware and charging protocols on prosumer energy consumption. To close this research gap, we develop heuristic vehicle-to-home charging strategies that aim to increase self-sufficiency, vehicle availability and traction battery lifetime. We discuss charging power constraints due to technical limitations measured in the laboratory and communication protocols. We investigate the impact of charging power constraints, bidirectional charger capability and forecasting algorithms on the self-sufficiency of the prosumer household. The simulation model integrates a comprehensive electric vehicle model, photovoltaic system model and historic measurement data of prosumer and driving profiles. We propose and simulate three different exemplary mobility profile scenarios. The mobility scenarios differ in their departure and arrival time distributions and are named Worker, Half-time Worker and Late Worker. The developed smart charging strategies can increase the self-sufficiency of the household by up to 16.9 percentage points in comparison to charging the vehicle with maximum power upon plug-in. Decreasing the minimum charging power constraint from 4.1kW to 1.8kW can increase self-sufficiency by up to 10.5 percentage points. Smart charging strategies, the use of a bidirectional charger, relaxation of charging power constraints and the use of forecasting algorithms increase the self-sufficiency of a prosumer household with a photovoltaic system and an electric vehicle.

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  • Rücker, Fabian & Schoeneberger, Ilka & Wilmschen, Till & Sperling, Dustin & Haberschusz, David & Figgener, Jan & Sauer, Dirk Uwe, 2022. "Self-sufficiency and charger constraints of prosumer households with vehicle-to-home strategies," Applied Energy, Elsevier, vol. 317(C).
    • Handle: RePEc:eee:appene:v:317:y:2022:i:c:s0306261922004561
    DOI: 10.1016/j.apenergy.2022.119060
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    1. Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying, 2016. "Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 720-732.
    2. Angenendt, Georg & Zurmühlen, Sebastian & Axelsen, Hendrik & Sauer, Dirk Uwe, 2018. "Comparison of different operation strategies for PV battery home storage systems including forecast-based operation strategies," Applied Energy, Elsevier, vol. 229(C), pages 884-899.
    3. Kim, Tae Hyun & Shin, Hansol & Kwag, Kyuhyeong & Kim, Wook, 2020. "A parallel multi-period optimal scheduling algorithm in microgrids with energy storage systems using decomposed inter-temporal constraints," Energy, Elsevier, vol. 202(C).
    4. Stefan Englberger & Holger Hesse & Daniel Kucevic & Andreas Jossen, 2019. "A Techno-Economic Analysis of Vehicle-to-Building: Battery Degradation and Efficiency Analysis in the Context of Coordinated Electric Vehicle Charging," Energies, MDPI, vol. 12(5), pages 1-17, March.
    5. Karan, Ebrahim & Asadi, Somayeh & Ntaimo, Lewis, 2016. "A stochastic optimization approach to reduce greenhouse gas emissions from buildings and transportation," Energy, Elsevier, vol. 106(C), pages 367-377.
    6. Buonomano, Annamaria, 2020. "Building to Vehicle to Building concept: A comprehensive parametric and sensitivity analysis for decision making aims," Applied Energy, Elsevier, vol. 261(C).
    7. Hoarau, Quentin & Perez, Yannick, 2019. "Network tariff design with prosumers and electromobility: Who wins, who loses?," Energy Economics, Elsevier, vol. 83(C), pages 26-39.
    8. Zhang, Qi & Tezuka, Tetsuo & Ishihara, Keiichi N. & Mclellan, Benjamin C., 2012. "Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan," Renewable Energy, Elsevier, vol. 44(C), pages 99-108.
    9. van der Kam, Mart & van Sark, Wilfried, 2015. "Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study," Applied Energy, Elsevier, vol. 152(C), pages 20-30.
    10. Bhatti, Abdul Rauf & Salam, Zainal, 2018. "A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system," Renewable Energy, Elsevier, vol. 125(C), pages 384-400.
    11. Kotowicz, Janusz & Uchman, Wojciech, 2021. "Analysis of the integrated energy system in residential scale: Photovoltaics, micro-cogeneration and electrical energy storage," Energy, Elsevier, vol. 227(C).
    12. van Leeuwen, Gijs & AlSkaif, Tarek & Gibescu, Madeleine & van Sark, Wilfried, 2020. "An integrated blockchain-based energy management platform with bilateral trading for microgrid communities," Applied Energy, Elsevier, vol. 263(C).
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    3. Alaa Al Zetawi & Marcos Tostado-Véliz & Hany M. Hasanien & Francisco Jurado, 2024. "A Robust-Based Home Energy Management Model for Optimal Participation of Prosumers in Competitive P2P Platforms," Energies, MDPI, vol. 17(22), pages 1-22, November.
    4. Matteo Fresia & Stefano Bracco, 2023. "Electric Vehicle Fleet Management for a Prosumer Building with Renewable Generation," Energies, MDPI, vol. 16(20), pages 1-16, October.
    5. Hildenbrand, Felix & Ditscheid, Dominik & Barbers, Elias & Sauer, Dirk Uwe, 2023. "Influence of the anode overhang on the open-circuit voltage and the ageing of lithium-ion batteries—A model based study," Applied Energy, Elsevier, vol. 332(C).

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