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Supply Side Management vs. Demand Side Management of a Residential Microgrid Equipped with an Electric Vehicle in a Dual Tariff Scheme

Author

Listed:
  • Alain Aoun

    (Department of Mathematics, Computer Science and Engineering, Université du Québec à Rimouski (UQAR), Rimouski, QC G5L 3A1, Canada)

  • Hussein Ibrahim

    (Institut Technologique de Maintenance Industrielle (ITMI), Cegep de Sept-Iles, Sept-Iles, QC G4R 5B7, Canada)

  • Mazen Ghandour

    (Faculty of Engineering, Lebanese University, Beirut 6573/14, Lebanon)

  • Adrian Ilinca

    (Department of Mathematics, Computer Science and Engineering, Université du Québec à Rimouski (UQAR), Rimouski, QC G5L 3A1, Canada)

Abstract

Fundamentally, two main methodologies are used to reduce the electric energy bill in residential, commercial, and even industrial applications. The first method is to act on the supply side by integrating alternative means of power generation, such as renewable energy generators, having a relatively low levelized cost of energy. Whereas, the second methodology focuses on the management of the load to minimize the overall paid cost for energy. Thus, this article highlights the importance of demand side management by comparing it to the supply side management having, as criteria, the total achieved savings on the overall annual energy bill of a residential microgrid supplied by two power sources and equipped with an electric vehicle. The optimization takes into consideration the cost of kWh that is paid by the prosumer based on an economical model having as inputs the outcomes of the energy model. The adopted energy model integrates, on the demand side, an intelligent energy management system acting on secondary loads, and on the supply side, a photovoltaic (PV) system with and without battery energy storage system (BESS). The outcome of this work shows that, under the right circumstances, demand side management can be as valuable as supply side control.

Suggested Citation

  • Alain Aoun & Hussein Ibrahim & Mazen Ghandour & Adrian Ilinca, 2019. "Supply Side Management vs. Demand Side Management of a Residential Microgrid Equipped with an Electric Vehicle in a Dual Tariff Scheme," Energies, MDPI, vol. 12(22), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4351-:d:287221
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    References listed on IDEAS

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    Cited by:

    1. Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    2. Yeongenn Kwon & Taeyoung Kim & Keon Baek & Jinho Kim, 2020. "Multi-Objective Optimization of Home Appliances and Electric Vehicle Considering Customer’s Benefits and Offsite Shared Photovoltaic Curtailment," Energies, MDPI, vol. 13(11), pages 1-16, June.
    3. Yong, Jin Yi & Tan, Wen Shan & Khorasany, Mohsen & Razzaghi, Reza, 2023. "Electric vehicles destination charging: An overview of charging tariffs, business models and coordination strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    4. Alain Aoun & Hussein Ibrahim & Mazen Ghandour & Adrian Ilinca, 2021. "Blockchain-Enabled Energy Demand Side Management Cap and Trade Model," Energies, MDPI, vol. 14(24), pages 1-26, December.
    5. Larry Erickson & Stephanie Ma, 2021. "Solar-Powered Charging Networks for Electric Vehicles," Energies, MDPI, vol. 14(4), pages 1-10, February.
    6. Chitchai Srithapon & Prasanta Ghosh & Apirat Siritaratiwat & Rongrit Chatthaworn, 2020. "Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost," Energies, MDPI, vol. 13(2), pages 1-20, January.
    7. Muñoz-Rodríguez, Francisco José & Jiménez-Castillo, Gabino & de la Casa Hernández, Jesús & Aguilar Peña, Juan Domingo, 2021. "A new tool to analysing photovoltaic self-consumption systems with batteries," Renewable Energy, Elsevier, vol. 168(C), pages 1327-1343.
    8. Upasana Lakhina & Irraivan Elamvazuthi & Nasreen Badruddin & Ajay Jangra & Bao-Huy Truong & Joseph M. Guerrero, 2023. "A Cost-Effective Multi-Verse Optimization Algorithm for Efficient Power Generation in a Microgrid," Sustainability, MDPI, vol. 15(8), pages 1-25, April.

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