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Distribution Power Loss Reduction of Standalone DC Microgrids Using Adaptive Differential Evolution-Based Control for Distributed Battery Systems

Author

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  • Junli Deng

    (College of Informatics, Huazhong Agricultural University, Wuhan 430000, China)

  • Yuan Mao

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Yun Yang

    (Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China)

Abstract

With high penetrations of renewable energy sources (RES), distributed battery systems (DBS) are widely adopted in standalone DC microgrids to stabilize the bus voltages by balancing the active power. This paper presents an Adaptive Differential Evolution (ADE)-based hierarchical control for DBS to achieve online distribution power loss mitigation as well as bus voltage regulations in standalone DC microgrids. The hierarchical control comprises two layers, i.e., ADE for the secondary layer and local proportional-integral (PI) control for the primary layer. The secondary layer control provides the bus voltage references for the primary control by optimizing the fitness function, which contains the parameters of the bus voltage deviations and the power loss on the distribution lines. Simultaneously, the state-of-charge (SoC) of the battery packs are controlled by local controllers to prevent over-charge and deep-discharge. Case studies using a Real-Time Digital Simulator (RTDS) validate that the proposed ADE-based hierarchical control can effectively reduce the distribution power loss and regulate the bus voltages within the tolerances in DC microgrids.

Suggested Citation

  • Junli Deng & Yuan Mao & Yun Yang, 2020. "Distribution Power Loss Reduction of Standalone DC Microgrids Using Adaptive Differential Evolution-Based Control for Distributed Battery Systems," Energies, MDPI, vol. 13(9), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2129-:d:351161
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    References listed on IDEAS

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    1. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Yusta-Loyo, José M. & Domínguez-Navarro, José A. & Ramírez-Rosado, Ignacio J. & Lujano, Juan & Aso, Ismael, 2011. "Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage," Applied Energy, Elsevier, vol. 88(11), pages 4033-4041.
    2. Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang, 2018. "State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles," Energies, MDPI, vol. 11(7), pages 1-36, July.
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    Cited by:

    1. Gerber, Daniel L. & Nordman, Bruce & Brown, Richard & Poon, Jason, 2023. "Cost analysis of distributed storage in AC and DC microgrids," Applied Energy, Elsevier, vol. 344(C).
    2. Hu Xiong & Bin Xiang & Yuan Mao, 2023. "An Auxiliary Passive Circuit and Control Design for Wireless Power Transfer Systems in DC Microgrids with Zero Voltage Switching and Accurate Output Regulations," Energies, MDPI, vol. 16(2), pages 1-21, January.
    3. Martin Ćalasan & Tatjana Konjić & Katarina Kecojević & Lazar Nikitović, 2020. "Optimal Allocation of Static Var Compensators in Electric Power Systems," Energies, MDPI, vol. 13(12), pages 1-24, June.
    4. Mahmoud Elshenawy & Ashraf Fahmy & Adel Elsamahy & Shaimaa A. Kandil & Helmy M. El Zoghby, 2022. "Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique," Energies, MDPI, vol. 15(19), pages 1-30, September.

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