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Explicit cost-risk tradeoff for optimal energy management in CCHP microgrid system under fuzzy-risk preferences

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  • Ji, Ling
  • Zhang, Bei-Bei
  • Huang, Guo-He
  • Xie, Yu-Lei
  • Niu, Dong-Xiao

Abstract

In this paper, a fuzzy risk-explicit interval parameter programming (FREIPP) approach was provided for multiple energy supply and demand management in microgrid system under uncertainties. The FREIPP method integrates risk-explicit interval linear programming and fuzzy theory within a general framework. It can tackle fuzzy and interval uncertainties in terms of various cost coefficients, forecasted load demand, decision maker's risk attitude and other uncertainties in microgrid system management. Compared with traditional interval parameter programming, the proposed method has distinct advantages in minimizing the system cost and risk simultaneously and providing more risk explicit solutions with the regard of obscure risk preference of decision maker. The FREIPP approach was successfully applied in a microgrid system with combined cooling, heating and power (CCHP) generation for three types of decision maker (i.e. defensive, neutral and aggressive). The obtained results indicated that the proposed FREIPP approach could provide optimal operation strategies with explicit cost-risk tradeoff information for decision maker when facing multiple complex uncertainties. Furthermore, it could help decision maker with different risk tolerance select desired optimal risk-aversion strategies, which is more realistic in real-world decision making process.

Suggested Citation

  • Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "Explicit cost-risk tradeoff for optimal energy management in CCHP microgrid system under fuzzy-risk preferences," Energy Economics, Elsevier, vol. 70(C), pages 525-535.
    • Handle: RePEc:eee:eneeco:v:70:y:2018:i:c:p:525-535
    DOI: 10.1016/j.eneco.2018.01.017
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    Cited by:

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    2. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    3. Ji, Ling & Zhang, Beibei & Huang, Guohe & Wang, Peng, 2020. "A novel multi-stage fuzzy stochastic programming for electricity system structure optimization and planning with energy-water nexus - A case study of Tianjin, China," Energy, Elsevier, vol. 190(C).
    4. Zuo, Qiting & Wu, Qingsong & Yu, Lei & Li, Yongping & Fan, Yurui, 2021. "Optimization of uncertain agricultural management considering the framework of water, energy and food," Agricultural Water Management, Elsevier, vol. 253(C).
    5. Yin, J.N. & Huang, G.H. & Xie, Y.L. & An, Y.K., 2021. "Carbon-subsidized inter-regional electric power system planning under cost-risk tradeoff and uncertainty: A case study of Inner Mongolia, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    6. Jonek-Kowalska, Izabela, 2019. "Efficiency of Enterprise Risk Management (ERM) systems. Comparative analysis in the fuel sector and energy sector on the basis of Central-European companies listed on the Warsaw Stock Exchange," Resources Policy, Elsevier, vol. 62(C), pages 405-415.
    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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    More about this item

    Keywords

    CCHP; Risk-explicit interval parameter programming; Fuzzy theory; Risk attitude; Energy management schemes;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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