IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v70y2018icp525-535.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988318300252
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2018.01.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Longxi & Mu, Hailin & Gao, Weijun & Li, Miao, 2014. "Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings," Applied Energy, Elsevier, vol. 136(C), pages 206-216.
    2. Shaban Boloukat, Mohammad Hadi & Akbari Foroud, Asghar, 2016. "Stochastic-based resource expansion planning for a grid-connected microgrid using interval linear programming," Energy, Elsevier, vol. 113(C), pages 776-787.
    3. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    4. Wang, Jiangjiang & Sui, Jun & Jin, Hongguang, 2015. "An improved operation strategy of combined cooling heating and power system following electrical load," Energy, Elsevier, vol. 85(C), pages 654-666.
    5. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    6. Nie, S. & Li, Y.P. & Liu, J. & Huang, Charley Z., 2017. "Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty," Energy Economics, Elsevier, vol. 61(C), pages 313-329.
    7. Moradi, Mohammad H. & Hajinazari, Mehdi & Jamasb, Shahriar & Paripour, Mahmoud, 2013. "An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming," Energy, Elsevier, vol. 49(C), pages 86-101.
    8. Dong, Cong & Huang, Guohe & Cai, Yanpeng & Li, Wei & Cheng, Guanhui, 2014. "Fuzzy interval programming for energy and environmental systems management under constraint-violation and energy-substitution effects: A case study for the City of Beijing," Energy Economics, Elsevier, vol. 46(C), pages 375-394.
    9. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    10. Ersoz, Ibrahim & Colak, Uner, 2016. "Combined cooling, heat and power planning under uncertainty," Energy, Elsevier, vol. 109(C), pages 1016-1025.
    11. Jochem, Patrick & Schönfelder, Martin & Fichtner, Wolf, 2015. "An efficient two-stage algorithm for decentralized scheduling of micro-CHP units," European Journal of Operational Research, Elsevier, vol. 245(3), pages 862-874.
    12. Ji, Ling & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao & Song, Yi-Hang, 2017. "Explicit cost-risk tradeoff for renewable portfolio standard constrained regional power system expansion: A case study of Guangdong Province, China," Energy, Elsevier, vol. 131(C), pages 125-136.
    13. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q. & Wang, R.Z., 2016. "Impacts of feed-in tariff policies on design and performance of CCHP system in different climate zones," Applied Energy, Elsevier, vol. 175(C), pages 168-179.
    14. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    15. Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    16. Motevasel, Mehdi & Seifi, Ali Reza & Niknam, Taher, 2013. "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, Elsevier, vol. 51(C), pages 123-136.
    17. Han Su & Feifei Dong & Yong Liu & Rui Zou & Huaicheng Guo, 2017. "Robustness-Optimality Tradeoff for Watershed Load Reduction Decision Making under Deep Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3627-3640, September.
    18. Jiang, Xi Zhuo & Wang, Xiangyu & Feng, Lejun & Zheng, Danxing & Shi, Lin, 2017. "Adapted computational method of energy level and energy quality evolution for combined cooling, heating and power systems with energy storage units," Energy, Elsevier, vol. 120(C), pages 209-216.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gao, Lei & Hwang, Yunho & Cao, Tao, 2019. "An overview of optimization technologies applied in combined cooling, heating and power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    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. 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).
    5. 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).
    6. 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).
    7. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    2. Afzali, Sayyed Faridoddin & Cotton, James S. & Mahalec, Vladimir, 2020. "Urban community energy systems design under uncertainty for specified levels of carbon dioxide emissions," Applied Energy, Elsevier, vol. 259(C).
    3. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Liu, Yuquan & Xiong, Wen, 2017. "An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power," Applied Energy, Elsevier, vol. 201(C), pages 343-353.
    4. Zhou, Yizhou & Wei, Zhinong & Sun, Guoqiang & Cheung, Kwok W. & Zang, Haixiang & Chen, Sheng, 2018. "A robust optimization approach for integrated community energy system in energy and ancillary service markets," Energy, Elsevier, vol. 148(C), pages 1-15.
    5. Gu, Wei & Lu, Shuai & Wu, Zhi & Zhang, Xuesong & Zhou, Jinhui & Zhao, Bo & Wang, Jun, 2017. "Residential CCHP microgrid with load aggregator: Operation mode, pricing strategy, and optimal dispatch," Applied Energy, Elsevier, vol. 205(C), pages 173-186.
    6. Afzali, Sayyed Faridoddin & Mahalec, Vladimir, 2018. "Novel performance curves to determine optimal operation of CCHP systems," Applied Energy, Elsevier, vol. 226(C), pages 1009-1036.
    7. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    8. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    9. Morshed, Mohammad Javad & Hmida, Jalel Ben & Fekih, Afef, 2018. "A probabilistic multi-objective approach for power flow optimization in hybrid wind-PV-PEV systems," Applied Energy, Elsevier, vol. 211(C), pages 1136-1149.
    10. Pambour, Kwabena Addo & Cakir Erdener, Burcin & Bolado-Lavin, Ricardo & Dijkema, Gerard P.J., 2017. "SAInt – A novel quasi-dynamic model for assessing security of supply in coupled gas and electricity transmission networks," Applied Energy, Elsevier, vol. 203(C), pages 829-857.
    11. Maria Psillaki & Nikolaos Apostolopoulos & Ilias Makris & Panagiotis Liargovas & Sotiris Apostolopoulos & Panos Dimitrakopoulos & George Sklias, 2023. "Hospitals’ Energy Efficiency in the Perspective of Saving Resources and Providing Quality Services through Technological Options: A Systematic Literature Review," Energies, MDPI, vol. 16(2), pages 1-21, January.
    12. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
    13. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    14. Yuan, Yu & Bai, Zhang & Zhou, Shengdong & Zheng, Bo & Hu, Wenxin, 2022. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Flexible demand response characteristics," Applied Energy, Elsevier, vol. 325(C).
    15. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Zhao, Xin & Zheng, Wenyu & Hou, Zhihua & Chen, Heng & Xu, Gang & Liu, Wenyi & Chen, Honggang, 2022. "Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy," Energy, Elsevier, vol. 238(PA).
    17. Bao, Zhejing & Chen, Dawei & Wu, Lei & Guo, Xiaogang, 2019. "Optimal inter- and intra-hour scheduling of islanded integrated-energy system considering linepack of gas pipelines," Energy, Elsevier, vol. 171(C), pages 326-340.
    18. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2019. "Assessing Renewable Energy Sources for Electricity (RES-E) Potential Using a CAPM-Analogous Multi-Stage Model," Energies, MDPI, vol. 12(19), pages 1-20, September.
    19. He, Liangce & Lu, Zhigang & Zhang, Jiangfeng & Geng, Lijun & Zhao, Hao & Li, Xueping, 2018. "Low-carbon economic dispatch for electricity and natural gas systems considering carbon capture systems and power-to-gas," Applied Energy, Elsevier, vol. 224(C), pages 357-370.
    20. Chen, W.D. & Chua, K.J., 2022. "A novel and optimized operation strategy map for CCHP systems considering optimal thermal energy utilization," Energy, Elsevier, vol. 259(C).

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:70:y:2018:i:c:p:525-535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.