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Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

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  • Yuqing Yang

    (National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China)

  • Weige Zhang

    (National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China)

  • Jiuchun Jiang

    (National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China)

  • Mei Huang

    (National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China)

  • Liyong Niu

    (National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China)

Abstract

With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs) is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS) has to be involved to mitigate the bad effects of DERs’ integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs) considered as the auxiliary technique are also introduced to attenuate the DERs’ influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs’ operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO) algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration. After simulation, the proposed scheduling strategies have been verified to be extremely effective for the enhancement of the distribution network characteristics.

Suggested Citation

  • Yuqing Yang & Weige Zhang & Jiuchun Jiang & Mei Huang & Liyong Niu, 2015. "Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration," Energies, MDPI, vol. 8(10), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:10718-10735:d:56403
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    References listed on IDEAS

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    1. Yuqing Yang & Weige Zhang & Liyong Niu & Jiuchun Jiang, 2015. "Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale," Energies, MDPI, vol. 8(2), pages 1-17, February.
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    Cited by:

    1. Moonjong Jang & Ho-Jin Choi & Chae-Gyun Lim & Byoungwoong An & Jungsub Sim, 2022. "Optimization of ESS Scheduling for Cost Reduction in Commercial and Industry Customers in Korea," Sustainability, MDPI, vol. 14(6), pages 1-16, March.
    2. Kongrit Mansiri & Sukruedee Sukchai & Chatchai Sirisamphanwong, 2018. "Fuzzy Control for Smart PV-Battery System Management to Stabilize Grid Voltage of 22 kV Distribution System in Thailand," Energies, MDPI, vol. 11(7), pages 1-19, July.
    3. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    4. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    5. Kou-Bin Liu & Chen-Yao Liu & Yi-Hua Liu & Yuan-Chen Chien & Bao-Sheng Wang & Yong-Seng Wong, 2016. "Analysis and Controller Design of a Universal Bidirectional DC-DC Converter," Energies, MDPI, vol. 9(7), pages 1-23, June.
    6. Yunna Wu & Meng Yang & Haobo Zhang & Kaifeng Chen & Yang Wang, 2016. "Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method," Energies, MDPI, vol. 9(3), pages 1-20, March.
    7. Luis Galván & Juan M. Navarro & Eduardo Galván & Juan M. Carrasco & Andrés Alcántara, 2019. "Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method," Energies, MDPI, vol. 12(4), pages 1-17, February.

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