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Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme

Author

Listed:
  • Jayalakshmi N. Sabhahit

    (Department of Electrical and Electronics, Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Sanjana Satish Solanke

    (Department of Electrical and Electronics, Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Vinay Kumar Jadoun

    (Department of Electrical and Electronics, Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Hasmat Malik

    (BEARS, University Town, NUS Campus, Singapore 138602, Singapore)

  • Fausto Pedro García Márquez

    (Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Jesús María Pinar-Pérez

    (Department of Quantitative Methods, CUNEF Universidad, 28040 Madrid, Spain)

Abstract

After over a century of internal combustion engines ruling the transport sector, electric vehicles appear to be on the verge of gaining traction due to a slew of advantages, including lower operating costs and lower CO 2 emissions. By using the Vehicle-to-Grid (or Grid-to-Vehicle if Electric vehicles (EVs) are utilized as load) approach, EVs can operate as both a load and a source. Primary frequency regulation and congestion management are two essential characteristics of this technology that are added to an industrial microgrid. Industrial Microgrids are made up of different energy sources such as wind farms and PV farms, storage systems, and loads. EVs have gained a lot of interest as a technique for frequency management because of their ability to regulate quickly. Grid reliability depends on this quick reaction. Different contingency, state of charge of the electric vehicles, and a varying number of EVs in an EV fleet are considered in this work, and a proposed control scheme for frequency management is presented. This control scheme enables bidirectional power flow, allowing for primary frequency regulation during the various scenarios that an industrial microgrid may encounter over the course of a 24-h period. The presented controller will provide dependable frequency regulation support to the industrial microgrid during contingencies, as will be demonstrated by simulation results, achieving a more reliable system. However, simulation results will show that by increasing a number of the EVs in a fleet for the Vehicle-to-Grid approach, an industrial microgrid’s frequency can be enhanced even further.

Suggested Citation

  • Jayalakshmi N. Sabhahit & Sanjana Satish Solanke & Vinay Kumar Jadoun & Hasmat Malik & Fausto Pedro García Márquez & Jesús María Pinar-Pérez, 2022. "Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme," Energies, MDPI, vol. 15(9), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3102-:d:800938
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    References listed on IDEAS

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    1. Zhu, Xianwen & Xia, Mingchao & Chiang, Hsiao-Dong, 2018. "Coordinated sectional droop charging control for EV aggregator enhancing frequency stability of microgrid with high penetration of renewable energy sources," Applied Energy, Elsevier, vol. 210(C), pages 936-943.
    2. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    3. Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Jiang, Di, 2020. "Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines," Renewable Energy, Elsevier, vol. 145(C), pages 981-996.
    4. Krzysztof Zagrajek & Józef Paska & Łukasz Sosnowski & Konrad Gobosz & Konrad Wróblewski, 2021. "Framework for the Introduction of Vehicle-to-Grid Technology into the Polish Electricity Market," Energies, MDPI, vol. 14(12), pages 1-30, June.
    5. Wang, Shuoqi & Lu, Languang & Han, Xuebing & Ouyang, Minggao & Feng, Xuning, 2020. "Virtual-battery based droop control and energy storage system size optimization of a DC microgrid for electric vehicle fast charging station," Applied Energy, Elsevier, vol. 259(C).
    6. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    7. Uddin, Kotub & Dubarry, Matthieu & Glick, Mark B., 2018. "The viability of vehicle-to-grid operations from a battery technology and policy perspective," Energy Policy, Elsevier, vol. 113(C), pages 342-347.
    8. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    9. LaMonaca, Sarah & Ryan, Lisa, 2022. "The state of play in electric vehicle charging services – A review of infrastructure provision, players, and policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    10. Peng, Chao & Zou, Jianxiao & Lian, Lian & Li, Liying, 2017. "An optimal dispatching strategy for V2G aggregator participating in supplementary frequency regulation considering EV driving demand and aggregator’s benefits," Applied Energy, Elsevier, vol. 190(C), pages 591-599.
    11. Wolbertus, Rick & van den Hoed, Robert & Kroesen, Maarten & Chorus, Caspar, 2021. "Charging infrastructure roll-out strategies for large scale introduction of electric vehicles in urban areas: An agent-based simulation study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 262-285.
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    Cited by:

    1. Bassam A. Hemad & Nader M. A. Ibrahim & Shereen A. Fayad & Hossam E. A. Talaat, 2022. "Hierarchical Clustering-Based Framework for Interconnected Power System Contingency Analysis," Energies, MDPI, vol. 15(15), pages 1-12, August.
    2. Efrain Mendez-Flores & Alexandro Ortiz & Israel Macias & Arturo Molina, 2022. "Experimental Validation of an Enhanced MPPT Algorithm and an Optimal DC–DC Converter Design Powered by Metaheuristic Optimization for PV Systems," Energies, MDPI, vol. 15(21), pages 1-35, October.
    3. Mohamed El-Hendawi & Zhanle Wang & Xiaoyue Liu, 2022. "Centralized and Distributed Optimization for Vehicle-to-Grid Applications in Frequency Regulation," Energies, MDPI, vol. 15(12), pages 1-22, June.

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