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Multi-Objective Optimization of a Microgrid Considering the Uncertainty of Supply and Demand

Author

Listed:
  • Shiping Geng

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, Beijing 102206, China)

  • Gengqi Wu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, Beijing 102206, China)

  • Caixia Tan

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

  • Dongxiao Niu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, Beijing 102206, China)

  • Xiaopeng Guo

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

Abstract

Starting from the perspective of the uncertainty of supply and demand, using the Copula function and fuzzy numbers a scenario generation method, considering the uncertainty of scenery, and a random fuzzy model of energy demand uncertainty are proposed. Then, through the energy flow direction and the energy supply, production, conversion, storage, and demand, a multi-objective model considering the economic and environmental protection of a park is constructed. Here, the park refers to a microgrid that gathers distributed energy such as wind and photovoltaics and has requirements for cooling, heat, and electricity at the same time. Next, combining the constraints of each link, the particle swarm algorithm is used to solve the model. Finally, an example is analyzed in a certain park. The results of the example show that, on the one hand, the proposed scenario generation method and fuzzy number method can reduce the uncertainty of supply and demand, effectively fitting the wind and photovoltaic output and various energy demands. On the other hand, considering the economy and environmental protection of the park at the same time, the configuration of energy storage equipment can not only improve the economy of the park, but also promote the consumption of renewable energy.

Suggested Citation

  • Shiping Geng & Gengqi Wu & Caixia Tan & Dongxiao Niu & Xiaopeng Guo, 2021. "Multi-Objective Optimization of a Microgrid Considering the Uncertainty of Supply and Demand," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:3:p:1320-:d:487961
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    References listed on IDEAS

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    1. Wang, Yuwei & Tang, Liu & Yang, Yuanjuan & Sun, Wei & Zhao, Huiru, 2020. "A stochastic-robust coordinated optimization model for CCHP micro-grid considering multi-energy operation and power trading with electricity markets under uncertainties," Energy, Elsevier, vol. 198(C).
    2. Lingmin, Chen & Jiekang, Wu & Fan, Wu & Huiling, Tang & Changjie, Li & Yan, Xiong, 2020. "Energy flow optimization method for multi-energy system oriented to combined cooling, heating and power," Energy, Elsevier, vol. 211(C).
    3. Kong, Xiangyu & Xiao, Jie & Liu, Dehong & Wu, Jianzhong & Wang, Chengshan & Shen, Yu, 2020. "Robust stochastic optimal dispatching method of multi-energy virtual power plant considering multiple uncertainties," Applied Energy, Elsevier, vol. 279(C).
    4. Li, Hangxin & Wang, Shengwei, 2020. "Coordinated robust optimal design of building envelope and energy systems for zero/low energy buildings considering uncertainties," Applied Energy, Elsevier, vol. 265(C).
    5. Valizadeh Haghi, H. & Tavakoli Bina, M. & Golkar, M.A. & Moghaddas-Tafreshi, S.M., 2010. "Using Copulas for analysis of large datasets in renewable distributed generation: PV and wind power integration in Iran," Renewable Energy, Elsevier, vol. 35(9), pages 1991-2000.
    6. Turk, Ana & Wu, Qiuwei & Zhang, Menglin & Østergaard, Jacob, 2020. "Day-ahead stochastic scheduling of integrated multi-energy system for flexibility synergy and uncertainty balancing," Energy, Elsevier, vol. 196(C).
    7. Song, Yazhi & Liu, Tiansen & Liang, Dapeng & Li, Yin & Song, Xiaoqiu, 2019. "A Fuzzy Stochastic Model for Carbon Price Prediction Under the Effect of Demand-related Policy in China's Carbon Market," Ecological Economics, Elsevier, vol. 157(C), pages 253-265.
    8. Moradi, Mohammad H. & Eskandari, Mohsen, 2014. "A hybrid method for simultaneous optimization of DG capacity and operational strategy in microgrids considering uncertainty in electricity price forecasting," Renewable Energy, Elsevier, vol. 68(C), pages 697-714.
    9. Yu, L. & Li, Y.P. & Huang, G.H., 2016. "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China," Energy, Elsevier, vol. 98(C), pages 190-203.
    10. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
    11. Ju, Liwei & Tan, Qinliang & Lin, Hongyu & Mei, Shufang & Li, Nan & Lu, Yan & Wang, Yao, 2020. "A two-stage optimal coordinated scheduling strategy for micro energy grid integrating intermittent renewable energy sources considering multi-energy flexible conversion," Energy, Elsevier, vol. 196(C).
    12. 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).
    13. Ju, Liwei & Zhao, Rui & Tan, Qinliang & Lu, Yan & Tan, Qingkun & Wang, Wei, 2019. "A multi-objective robust scheduling model and solution algorithm for a novel virtual power plant connected with power-to-gas and gas storage tank considering uncertainty and demand response," Applied Energy, Elsevier, vol. 250(C), pages 1336-1355.
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    2. 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.
    3. Gao, Jianwei & Meng, Qichen & Liu, Jiangtao & Wang, Ziying, 2024. "Thermoelectric optimization of integrated energy system considering wind-photovoltaic uncertainty, two-stage power-to-gas and ladder-type carbon trading," Renewable Energy, Elsevier, vol. 221(C).

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