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Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs

Author

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  • Viviani Caroline Onishi

    (Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, Campus de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
    INESC Coimbra, University of Coimbra, DEEC, Polo II, 3030-290 Coimbra, Portugal)

  • Carlos Henggeler Antunes

    (INESC Coimbra, University of Coimbra, DEEC, Polo II, 3030-290 Coimbra, Portugal
    Department of Electrical and Computer Engineering, University of Coimbra, Polo II, 3030-290 Coimbra, Portugal)

  • João Pedro Fernandes Trovão

    (INESC Coimbra, University of Coimbra, DEEC, Polo II, 3030-290 Coimbra, Portugal
    Department of Electrical & Computer Engineering, University of Sherbrooke, Sherbrooke, QC J1K 2R1, Canada)

Abstract

Vehicle-to-grid (V2G) technology heralds great promise as a demand-side resource to contribute to more efficient grid management and promote the use of decentralized renewable energy. In this light, we propose a new optimization model for the sustainable energy and reserve market management in renewable-driven microgrid (RMG) plug-in electric vehicles (PEVs) parking lot systems. The RMG is composed of a hybrid photovoltaic/wind/hydrogen energy and storage system, along with local dispatchable generation units and bidirectional grid connection. The RMG is coupled to a smart PEVs parking lot, which is equipped with grid-to-vehicle (G2V) and V2G technologies allowing for not only PEVs aggregation and control but also optimal allocation of energy resources. Time-of-use (TOU) prices are considered in a demand response program (DRP) to enhance both economic and environmental performances by encouraging end-users to shift their energy demands from peak to off-peak time periods. Additionally, the model accounts for an economic incentive to PEVs owners to compensate for battery degradation. The integrated system eco-efficiency is evaluated through the application of the novel life cycle assessment-based Eco-cost indicator. The resulting mixed-integer linear programming model to minimize sustainability costs is implemented in GAMS and solved to global optimality. Different case studies are performed to demonstrate the effectiveness of the proposed modelling approach. Energy analyses results reveal that the optimal G2V-V2G operation, allied to TOU prices in a DRP, and reserve market management can reduce around 42% the energy and environmental costs of the RMG-PEVs parking lot system.

Suggested Citation

  • Viviani Caroline Onishi & Carlos Henggeler Antunes & João Pedro Fernandes Trovão, 2020. "Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs," Energies, MDPI, vol. 13(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1884-:d:344839
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    References listed on IDEAS

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    1. Rishabh Ghotge & Yitzhak Snow & Samira Farahani & Zofia Lukszo & Ad van Wijk, 2020. "Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty," Energies, MDPI, vol. 13(5), pages 1-18, March.
    2. 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.
    3. Honarmand, Masoud & Zakariazadeh, Alireza & Jadid, Shahram, 2014. "Optimal scheduling of electric vehicles in an intelligent parking lot considering vehicle-to-grid concept and battery condition," Energy, Elsevier, vol. 65(C), pages 572-579.
    4. Shaukat, N. & Khan, B. & Ali, S.M. & Mehmood, C.A. & Khan, J. & Farid, U. & Majid, M. & Anwar, S.M. & Jawad, M. & Ullah, Z., 2018. "A survey on electric vehicle transportation within smart grid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1329-1349.
    5. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    6. Nikoobakht, Ahmad & Aghaei, Jamshid & Khatami, Roohallah & Mahboubi-Moghaddam, Esmaeel & Parvania, Masood, 2019. "Stochastic flexible transmission operation for coordinated integration of plug-in electric vehicles and renewable energy sources," Applied Energy, Elsevier, vol. 238(C), pages 225-238.
    7. Mohammadi Landi, Meysam & Mohammadi, Mohammad & Rastegar, Mohammad, 2018. "Simultaneous determination of optimal capacity and charging profile of plug-in electric vehicle parking lots in distribution systems," Energy, Elsevier, vol. 158(C), pages 504-511.
    8. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    9. Mortaz, Ebrahim & Vinel, Alexander & Dvorkin, Yury, 2019. "An optimization model for siting and sizing of vehicle-to-grid facilities in a microgrid," Applied Energy, Elsevier, vol. 242(C), pages 1649-1660.
    10. Zheng, Yanchong & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2019. "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 424-439.
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    Cited by:

    1. Sagar Hossain & Md. Rokonuzzaman & Kazi Sajedur Rahman & A. K. M. Ahasan Habib & Wen-Shan Tan & Md Mahmud & Shahariar Chowdhury & Sittiporn Channumsin, 2023. "Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    2. Sarah Ouédraogo & Ghjuvan Antone Faggianelli & Guillaume Pigelet & Jean Laurent Duchaud & Gilles Notton, 2020. "Application of Optimal Energy Management Strategies for a Building Powered by PV/Battery System in Corsica Island," Energies, MDPI, vol. 13(17), pages 1-20, September.
    3. Md. Rayid Hasan Mojumder & Fahmida Ahmed Antara & Md. Hasanuzzaman & Basem Alamri & Mohammad Alsharef, 2022. "Electric Vehicle-to-Grid (V2G) Technologies: Impact on the Power Grid and Battery," Sustainability, MDPI, vol. 14(21), pages 1-53, October.
    4. Sunoh Kim & Jin Hur, 2020. "A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis," Energies, MDPI, vol. 13(20), pages 1-13, October.
    5. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    6. Patrick Dossow & Maximilian Hampel, 2023. "Synergies of Electric Vehicle Multi-Use: Analyzing the Implementation Effort for Use Case Combinations in Smart E-Mobility," Energies, MDPI, vol. 16(5), pages 1-35, March.
    7. Roberta Olindo & Nathalie Schmitt & Joost Vogtländer, 2021. "Life Cycle Assessments on Battery Electric Vehicles and Electrolytic Hydrogen: The Need for Calculation Rules and Better Databases on Electricity," Sustainability, MDPI, vol. 13(9), pages 1-22, May.

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