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Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement

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  • Liu, Hui
  • Huang, Kai
  • Wang, Ni
  • Qi, Junjian
  • Wu, Qiuwei
  • Ma, Shicong
  • Li, Canbing

Abstract

In this paper, optimal strategies are proposed for electric vehicles in charging stations to participate in the secondary frequency regulation, while considering their charging demands. In order to fairly allocate the dispatch from the control center among electric vehicles according to their charging demands, two optimal real-time strategies are proposed, respectively based on area control error and area regulation requirement. With the proposed strategies, the expected charging of electric vehicles is optimally tracked in real time by using the regulation task from the control center. Simulations on a two-area interconnected power grid show that the proposed two strategies can respectively lead to a 12.66% and 16.78% frequency deviation reduction and a 13.76% and 9.86% generator regulation reduction. At the same time, the charging demands of EVs can also be ensured.

Suggested Citation

  • Liu, Hui & Huang, Kai & Wang, Ni & Qi, Junjian & Wu, Qiuwei & Ma, Shicong & Li, Canbing, 2019. "Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement," Applied Energy, Elsevier, vol. 240(C), pages 46-55.
    • Handle: RePEc:eee:appene:v:240:y:2019:i:c:p:46-55
    DOI: 10.1016/j.apenergy.2019.02.044
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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. Zhong, Jin & He, Lina & Li, Canbing & Cao, Yijia & Wang, Jianhui & Fang, Baling & Zeng, Long & Xiao, Guoxuan, 2014. "Coordinated control for large-scale EV charging facilities and energy storage devices participating in frequency regulation," Applied Energy, Elsevier, vol. 123(C), pages 253-262.
    3. Wang, Mingshen & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2017. "Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1673-1683.
    4. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2015. "Value of flexible electric vehicles in providing spinning reserve services," Applied Energy, Elsevier, vol. 157(C), pages 60-74.
    5. Kempton, Willett & Kubo, Toru, 2000. "Electric-drive vehicles for peak power in Japan," Energy Policy, Elsevier, vol. 28(1), pages 9-18, January.
    6. DeForest, Nicholas & MacDonald, Jason S. & Black, Douglas R., 2018. "Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration," Applied Energy, Elsevier, vol. 210(C), pages 987-1001.
    7. Gough, Rebecca & Dickerson, Charles & Rowley, Paul & Walsh, Chris, 2017. "Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage," Applied Energy, Elsevier, vol. 192(C), pages 12-23.
    8. Green II, Robert C. & Wang, Lingfeng & Alam, Mansoor, 2011. "The impact of plug-in hybrid electric vehicles on distribution networks: A review and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 544-553, January.
    9. 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.
    10. Meng, Jian & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qu, Bo, 2016. "Dynamic frequency response from electric vehicles considering travelling behavior in the Great Britain power system," Applied Energy, Elsevier, vol. 162(C), pages 966-979.
    11. Zheng, Yanchong & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2018. "A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid," Applied Energy, Elsevier, vol. 217(C), pages 1-13.
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    7. Howlader, Abdul Motin & Sadoyama, Staci & Roose, Leon R. & Chen, Yan, 2020. "Active power control to mitigate voltage and frequency deviations for the smart grid using smart PV inverters," Applied Energy, Elsevier, vol. 258(C).
    8. Johnson, Samuel C. & Rhodes, Joshua D. & Webber, Michael E., 2020. "Understanding the impact of non-synchronous wind and solar generation on grid stability and identifying mitigation pathways," Applied Energy, Elsevier, vol. 262(C).
    9. Fei Zeng & Zhinong Wei & Guoqiang Sun & Mingshen Wang & Haiteng Han, 2023. "Frequency Regulation of Electric Vehicle Aggregator Considering User Requirements with Limited Data Collection," Energies, MDPI, vol. 16(2), pages 1-21, January.
    10. Geng, Lijun & Lu, Zhigang & He, Liangce & Zhang, Jiangfeng & Li, Xueping & Guo, Xiaoqiang, 2019. "Smart charging management system for electric vehicles in coupled transportation and power distribution systems," Energy, Elsevier, vol. 189(C).
    11. Sui, Quan & Wei, Fanrong & Zhang, Rui & Lin, Xiangning & Tong, Ning & Wang, Zhixun & Li, Zhengtian, 2019. "Optimal use of electric energy oriented water-electricity combined supply system for the building-integrated-photovoltaics community," Applied Energy, Elsevier, vol. 247(C), pages 549-558.
    12. Ashish Shrestha & Francisco Gonzalez-Longatt, 2021. "Frequency Stability Issues and Research Opportunities in Converter Dominated Power System," Energies, MDPI, vol. 14(14), pages 1-28, July.
    13. Deepak Kumar Gupta & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems," Energies, MDPI, vol. 14(6), pages 1-16, March.
    14. Yin, Linfei & Wu, Yunzhi, 2022. "Mode-decomposition memory reinforcement network strategy for smart generation control in multi-area power systems containing renewable energy," Applied Energy, Elsevier, vol. 307(C).
    15. Li, Pengfei & Hu, Weihao & Xu, Xiao & Huang, Qi & Liu, Zhou & Chen, Zhe, 2019. "A frequency control strategy of electric vehicles in microgrid using virtual synchronous generator control," Energy, Elsevier, vol. 189(C).
    16. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    17. Guoxin Ming & Jian Geng & Jiantao Liu & Yiyuan Chen & Kun Yuan & Kaifeng Zhang, 2022. "Load Frequency Robust Control Considering Intermittent Characteristics of Demand-Side Resources," Energies, MDPI, vol. 15(12), pages 1-20, June.
    18. 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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