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Optimal electrification of off-grid smart homes considering flexible demand and vehicle-to-home capabilities

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  • Tostado-Véliz, Marcos
  • León-Japa, Rogelio S.
  • Jurado, Francisco

Abstract

The emergence of novel demand-side management strategies is provoking that residential consumers cannot be longer categorized as inflexible loads. In that sense, new paradigms such as flexible demand and vehicle-to-home capabilities have appeared on pursuing a more efficient management of the different domestic assets such as smart appliances, small renewable generators and storage facilities. Consideration of such kind of management strategies plays a vital role on designing stages of electrifications systems for isolated homes. In this regard, a proper evaluation of possible demand-side capabilities enables a more accurate evaluation of the electrification project. This paper tackles this issue by developing a Mixed Integer Linear Programming formulation for optimal planning of electrification systems for off-grid dwellings. The developed framework allows to incorporate and analyse advanced demand-side strategies such as deferrable loads and vehicle-to-home processes by evaluating different project costs over various time horizons. The proposed approach is applied to a benchmark off-grid residential case study and various results are provided and analysed. As the most relevant result, it is worth remarking that total project cost can be reduced by ~21.2% and ~25.73% by considering flexible demand and vehicle-to-home capabilities, respectively. Nevertheless, the highest monetary savings were achieved when both strategies are jointly adopted, reducing the total project cost up to ~41.5%. The reported results demonstrate the importance of considering the different demand-side strategies on planning stages of electrification systems for off-grid dwellings.

Suggested Citation

  • Tostado-Véliz, Marcos & León-Japa, Rogelio S. & Jurado, Francisco, 2021. "Optimal electrification of off-grid smart homes considering flexible demand and vehicle-to-home capabilities," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921006127
    DOI: 10.1016/j.apenergy.2021.117184
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    Cited by:

    1. Virginia Casella & Daniel Fernandez Valderrama & Giulio Ferro & Riccardo Minciardi & Massimo Paolucci & Luca Parodi & Michela Robba, 2022. "Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management," Energies, MDPI, vol. 15(11), pages 1-23, May.
    2. Dongsu Kim & Yeobeom Yoon & Jongman Lee & Pedro J. Mago & Kwangho Lee & Heejin Cho, 2022. "Design and Implementation of Smart Buildings: A Review of Current Research Trend," Energies, MDPI, vol. 15(12), pages 1-17, June.
    3. Aws Khalil & Ahmed Abdelhamed & Girma Tewolde & Jaerock Kwon, 2021. "Ridon Vehicle: Drive-by-Wire System for Scaled Vehicle Platform and Its Application on Behavior Cloning," Energies, MDPI, vol. 14(23), pages 1-25, December.
    4. Hessam Golmohamadi, 2022. "Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    5. Tostado-Véliz, Marcos & Kamel, Salah & Hasanien, Hany M. & Arévalo, Paul & Turky, Rania A. & Jurado, Francisco, 2022. "A stochastic-interval model for optimal scheduling of PV-assisted multi-mode charging stations," Energy, Elsevier, vol. 253(C).
    6. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Dongsu Kim & Jongman Lee & Sunglok Do & Pedro J. Mago & Kwang Ho Lee & Heejin Cho, 2022. "Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends," Energies, MDPI, vol. 15(19), pages 1-30, October.
    8. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    9. Tostado-Véliz, Marcos & Kamel, Salah & Hasanien, Hany M. & Turky, Rania A. & Jurado, Francisco, 2022. "Uncertainty-aware day-ahead scheduling of microgrids considering response fatigue: An IGDT approach," Applied Energy, Elsevier, vol. 310(C).
    10. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Jurado, Francisco, 2022. "A novel hybrid lexicographic-IGDT methodology for robust multi-objective solution of home energy management systems," Energy, Elsevier, vol. 253(C).
    11. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
    12. Krzysztof Zagrajek & Mariusz Kłos & Desire D. Rasolomampionona & Mirosław Lewandowski & Karol Pawlak, 2023. "The Novel Approach of Using Electric Vehicles as a Resource to Mitigate the Negative Effects of Power Rationing on Non-Residential Buildings," Energies, MDPI, vol. 17(1), pages 1-36, December.
    13. Zhou, Yuekuan, 2022. "Energy sharing and trading on a novel spatiotemporal energy network in Guangdong-Hong Kong-Macao Greater Bay Area," Applied Energy, Elsevier, vol. 318(C).
    14. Wang, Guotao & Zhou, Yifan & Lin, Zhenjia & Zhu, Shibo & Qiu, Rui & Chen, Yuntian & Yan, Jinyue, 2024. "Robust energy management through aggregation of flexible resources in multi-home micro energy hub," Applied Energy, Elsevier, vol. 357(C).

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