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Virtual-battery based droop control and energy storage system size optimization of a DC microgrid for electric vehicle fast charging station

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  • Wang, Shuoqi
  • Lu, Languang
  • Han, Xuebing
  • Ouyang, Minggao
  • Feng, Xuning

Abstract

DC microgrid is supposed to be a feasible solution to reduce the negative impact of electric vehicle (EV) fast charging on the electric grid and improve the penetration of photovoltaics (PV) generation. In this paper, an improved decentralized Virtual-battery based droop control with the capability of bus voltage maintenance, load power dispatch and SOC balance of the energy storage system (ESS) is proposed to ensure the autonomous and stable operation of the DC microgrid. The reference output voltage and virtual resistance in the droop control loop are altered dynamically based on the Virtual-battery model of the ESS. The coordinated control among the PV-ESS-Grid integrated system is realized through the primary Bus-Signaling control, where the reference voltages at which the control modes of the PV array and the grid are switched are designed based on the VirtualOCV of the ESS. The effectiveness of the proposed control strategy is validated in MATLAB/Simulink environment with an equivalent bus capacitance-based model where the EV charging profile is obtained from real-world charging data of a fast charging station. The merits of the control strategy including higher PV utilization, less frequent connection of the grid and more precise voltage tracking are highlighted in comparison with the conventional droop control strategy. Finally, the sizing of the ESSs is optimized based on the total cost of the DC microgrid, including the daily electricity cost purchased from the grid and the depreciation cost of the ESSs based on the expanded capacity degradation model of Li-ion batteries.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318331
    DOI: 10.1016/j.apenergy.2019.114146
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    9. Haupt, Leon & Schöpf, Michael & Wederhake, Lars & Weibelzahl, Martin, 2020. "The influence of electric vehicle charging strategies on the sizing of electrical energy storage systems in charging hub microgrids," Applied Energy, Elsevier, vol. 273(C).
    10. Wei Zhang & Ming Zhong & Junfei Han & Yumei Sun & Yang Wang, 2022. "Research on the strategy of lithium-ion battery–supercapacitor hybrid energy storage to suppress power fluctuation of direct current microgrid [Load frequency control of a novel renewable energy in," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 1012-1017.
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    13. Nick Rigogiannis & Ioannis Bogatsis & Christos Pechlivanis & Anastasios Kyritsis & Nick Papanikolaou, 2023. "Moving towards Greener Road Transportation: A Review," Clean Technol., MDPI, vol. 5(2), pages 1-25, June.
    14. 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.
    15. Sijia Li & Arman Oshnoei & Frede Blaabjerg & Amjad Anvari-Moghaddam, 2023. "Hierarchical Control for Microgrids: A Survey on Classical and Machine Learning-Based Methods," Sustainability, MDPI, vol. 15(11), pages 1-22, June.
    16. Md. Shafiul Alam & Abdullah A. Almehizia & Fahad Saleh Al-Ismail & Md. Alamgir Hossain & Muhammad Azharul Islam & Md. Shafiullah & Aasim Ullah, 2022. "Frequency Stabilization of AC Microgrid Clusters: An Efficient Fractional Order Supercapacitor Controller Approach," Energies, MDPI, vol. 15(14), pages 1-22, July.
    17. Nandini K. Krishnamurthy & Jayalakshmi N. Sabhahit & Vinay Kumar Jadoun & Dattatraya Narayan Gaonkar & Ashish Shrivastava & Vidya S. Rao & Ganesh Kudva, 2023. "Optimal Placement and Sizing of Electric Vehicle Charging Infrastructure in a Grid-Tied DC Microgrid Using Modified TLBO Method," Energies, MDPI, vol. 16(4), pages 1-27, February.
    18. Ammar Armghan & Muhammad Kashif Azeem & Hammad Armghan & Ming Yang & Fayadh Alenezi & Mudasser Hassan, 2021. "Dynamical Operation Based Robust Nonlinear Control of DC Microgrid Considering Renewable Energy Integration," Energies, MDPI, vol. 14(13), pages 1-23, July.
    19. Xie, Peng & Jia, Youwei & Lyu, Cheng & Wang, Han & Shi, Mengge & Chen, Hongkun, 2022. "Optimal sizing of renewables and battery systems for hybrid AC/DC microgrids based on variability management," Applied Energy, Elsevier, vol. 321(C).
    20. Matej Tkac & Martina Kajanova & Peter Bracinik, 2023. "A Review of Advanced Control Strategies of Microgrids with Charging Stations," Energies, MDPI, vol. 16(18), pages 1-25, September.

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