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A Hierarchical Optimal Operation Strategy of Hybrid Energy Storage System in Distribution Networks with High Photovoltaic Penetration

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  • Jian Chen

    (Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan 250061, China)

  • Jiaqi Li

    (Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan 250061, China)

  • Yicheng Zhang

    (School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Guannan Bao

    (State Grid Shandong Electric Power Dispatching & Control Center, Jinan 250001, China)

  • Xiaohui Ge

    (Electric Power Research Institute of State Grid Zhejiang Electric Power Co., LTD., Hangzhou 310014, China)

  • Peng Li

    (Electric Power Research Institute of State Grid Zhejiang Electric Power Co., LTD., Hangzhou 310014, China)

Abstract

In this paper, a hierarchical optimal operation strategy for a hybrid energy storage system (HESS) is proposed, which is suitable to be utilized in distribution networks (DNs) with high photovoltaic (PV) penetration to achieve PV power smoothing, voltage regulation and price arbitrage. Firstly, a fuzzy-logic based variable step-size control strategy for an ultracapacitor (UC) with the improvement of the lifetime of UC and tracking performance is adopted to smooth PV power fluctuations. The impact of PV forecasting errors is eliminated by adjusting the UC power in real time. Secondly, a coordinated control strategy, which includes centralized and local controls, is proposed for lithium-ion batteries. The centralized control is structured to determine the optimal battery unit for voltage regulation or price arbitrage according to lithium-ion battery performance indices. A modified lithium-ion battery aging model with better accuracy is proposed and the coupling relationship between the lifetime and the effective capacity is also considered. Additionally, the local control of the selected lithium-ion battery unit determines the charging/discharging power. A case study is used to validate the operation strategy and the results show that the lifetime equilibrium among different lithium-ion battery units can be achieved using the proposed strategy.

Suggested Citation

  • Jian Chen & Jiaqi Li & Yicheng Zhang & Guannan Bao & Xiaohui Ge & Peng Li, 2018. "A Hierarchical Optimal Operation Strategy of Hybrid Energy Storage System in Distribution Networks with High Photovoltaic Penetration," Energies, MDPI, vol. 11(2), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:389-:d:130679
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    References listed on IDEAS

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    1. Hao Xiao & Wei Pei & Zuomin Dong & Li Kong & Dan Wang, 2018. "Application and Comparison of Metaheuristic and New Metamodel Based Global Optimization Methods to the Optimal Operation of Active Distribution Networks," Energies, MDPI, vol. 11(1), pages 1-29, January.
    2. Fathima, A. Hina & Palanisamy, K., 2015. "Optimization in microgrids with hybrid energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 431-446.
    3. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    4. Fossati, Juan P. & Galarza, Ainhoa & Martín-Villate, Ander & Fontán, Luis, 2015. "A method for optimal sizing energy storage systems for microgrids," Renewable Energy, Elsevier, vol. 77(C), pages 539-549.
    5. Tran Thai Trung & Seon-Ju Ahn & Joon-Ho Choi & Seok-Il Go & Soon-Ryul Nam, 2014. "Real-Time Wavelet-Based Coordinated Control of Hybrid Energy Storage Systems for Denoising and Flattening Wind Power Output," Energies, MDPI, vol. 7(10), pages 1-25, October.
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    Cited by:

    1. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    2. Tiezhou Wu & Xiao Shi & Li Liao & Chuanjian Zhou & Hang Zhou & Yuehong Su, 2019. "A Capacity Configuration Control Strategy to Alleviate Power Fluctuation of Hybrid Energy Storage System Based on Improved Particle Swarm Optimization," Energies, MDPI, vol. 12(4), pages 1-11, February.
    3. Zhao, Bo & Ren, Junzhi & Chen, Jian & Lin, Da & Qin, Ruwen, 2020. "Tri-level robust planning-operation co-optimization of distributed energy storage in distribution networks with high PV penetration," Applied Energy, Elsevier, vol. 279(C).
    4. Djamila Rekioua, 2023. "Energy Storage Systems for Photovoltaic and Wind Systems: A Review," Energies, MDPI, vol. 16(9), pages 1-26, May.
    5. Miguel Ángel Pardo & Ricardo Cobacho & Luis Bañón, 2020. "Standalone Photovoltaic Direct Pumping in Urban Water Pressurized Networks with Energy Storage in Tanks or Batteries," Sustainability, MDPI, vol. 12(2), pages 1-20, January.
    6. Jae Woong Shim & Heejin Kim & Kyeon Hur, 2019. "Incorporating State-of-Charge Balancing into the Control of Energy Storage Systems for Smoothing Renewable Intermittency," Energies, MDPI, vol. 12(7), pages 1-13, March.
    7. João Martins & Sergiu Spataru & Dezso Sera & Daniel-Ioan Stroe & Abderezak Lashab, 2019. "Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems," Energies, MDPI, vol. 12(7), pages 1-15, April.

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