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Research on Multi-Objective Optimization Model for Hybrid Energy System Considering Combination of Wind Power and Energy Storage

Author

Listed:
  • Jing Wu

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Zhongfu Tan

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Keke Wang

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Yi Liang

    (School of Management, Hebei GEO University, Shijiazhuang 050031, China
    Strategy and Management Base of Mineral Resources in Hebei Province, Hebei GEO University, Shijiazhuang 050031, China)

  • Jinghan Zhou

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

Abstract

With the development of renewable energy, the grid connection is faced with great pressure, for its generation uncertainty and fluctuation requires larger reserve capacity, and higher operation costs. Energy storage system, as a flexible unit in the energy system, can effectively share the reserve pressure of the system by charging and discharging behaviors. In order to further improve the renewable energy utilization, the combination of wind power and energy storage for hybrid energy system is proposed. On considering the power generation characteristics, the objective functions are maximizing the system revenue and minimizing the system energy loss. Combined with the robust optimization theory, the model is transformed and solved. The results show that the application of the energy storage will effectively promote the renewable energy consumption, and the combination of the wind power and energy storage will achieve more effective utilization of the night-time wind power and cut down the total system cost.

Suggested Citation

  • Jing Wu & Zhongfu Tan & Keke Wang & Yi Liang & Jinghan Zhou, 2021. "Research on Multi-Objective Optimization Model for Hybrid Energy System Considering Combination of Wind Power and Energy Storage," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3098-:d:515296
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    References listed on IDEAS

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    1. Yang, Lian & Tai, Nengling & Fan, Chunju & Meng, Yuanye, 2016. "Energy regulating and fluctuation stabilizing by air source heat pump and battery energy storage system in microgrid," Renewable Energy, Elsevier, vol. 95(C), pages 202-212.
    2. Behboodi, Sahand & Chassin, David P. & Djilali, Ned & Crawford, Curran, 2017. "Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach," Applied Energy, Elsevier, vol. 189(C), pages 336-351.
    3. Chen, Yizhong & He, Li & Li, Jing, 2017. "Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty," Energy, Elsevier, vol. 130(C), pages 581-598.
    4. Gejirifu De & Zhongfu Tan & Menglu Li & Liling Huang & Xueying Song, 2018. "Two-Stage Stochastic Optimization for the Strategic Bidding of a Generation Company Considering Wind Power Uncertainty," Energies, MDPI, vol. 11(12), pages 1-21, December.
    5. Fischer, David & Harbrecht, Alexander & Surmann, Arne & McKenna, Russell, 2019. "Electric vehicles’ impacts on residential electric local profiles – A stochastic modelling approach considering socio-economic, behavioural and spatial factors," Applied Energy, Elsevier, vol. 233, pages 644-658.
    6. José Luis Torres-Madroñero & César Nieto-Londoño & Julián Sierra-Pérez, 2020. "Hybrid Energy Systems Sizing for the Colombian Context: A Genetic Algorithm and Particle Swarm Optimization Approach," Energies, MDPI, vol. 13(21), pages 1-30, October.
    7. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    8. Pu, Lei & Wang, Xiuhui & Tan, Zhongfu & Wang, Huaqing & Yang, JiaCheng & Wu, Jing, 2020. "Is China's electricity price cross-subsidy policy reasonable? Comparative analysis of eastern, central, and western regions," Energy Policy, Elsevier, vol. 138(C).
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    Cited by:

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    4. Jun Dong & Yaoyu Zhang & Yuanyuan Wang & Yao Liu, 2021. "A Two-Stage Optimal Dispatching Model for Micro Energy Grid Considering the Dual Goals of Economy and Environmental Protection under CVaR," Sustainability, MDPI, vol. 13(18), pages 1-28, September.
    5. Zhang, M.Y. & Chen, J.J. & Yang, Z.J. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Stochastic day-ahead scheduling of irrigation system integrated agricultural microgrid with pumped storage and uncertain wind power," Energy, Elsevier, vol. 237(C).
    6. Khashayar Hamedi & Shahrbanoo Sadeghi & Saeed Esfandi & Mahdi Azimian & Hessam Golmohamadi, 2021. "Eco-Emission Analysis of Multi-Carrier Microgrid Integrated with Compressed Air and Power-to-Gas Energy Storage Technologies," Sustainability, MDPI, vol. 13(9), pages 1-18, April.
    7. Zhao, Huiru & Li, Bingkang & Lu, Hao & Wang, Xuejie & Li, Hongze & Guo, Sen & Xue, Wanlei & Wang, Yuwei, 2022. "Economy-environment-energy performance evaluation of CCHP microgrid system: A hybrid multi-criteria decision-making method," Energy, Elsevier, vol. 240(C).

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