IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v109y2016icp1016-1025.html
   My bibliography  Save this article

Combined cooling, heat and power planning under uncertainty

Author

Listed:
  • Ersoz, Ibrahim
  • Colak, Uner

Abstract

The main purpose of this study is to derive a methodology for the analysis to determine the best CCHP (Combined Cooling Heat and Power) scheme in the presence of uncertainties differently from deterministic method. The proposed methodology helps decision makers see all the possible risks that impact the amortization of the system. Decisions for investments are generally taken by the conventional method, which relies on the result of an economic analysis with the assumption that variables will remain stable at the time the analysis is made. Nevertheless, CCHP systems by their nature work under uncertainties during their economic life. The proposed method has been tested with a representative case in this article. All the variables that affect the feasibility of the investment have been simulated with the non-parametric technique with the assumption that all the variables change as per normal distribution. In addition, the impact of the variables on the objective function has been assessed with the local method of sensitivity analysis. In the light of these results, this study contributes to decision makers during the CCHP planning by providing a different point of view at the stage of design and economic analysis for systems with uncertainties.

Suggested Citation

  • Ersoz, Ibrahim & Colak, Uner, 2016. "Combined cooling, heat and power planning under uncertainty," Energy, Elsevier, vol. 109(C), pages 1016-1025.
    • Handle: RePEc:eee:energy:v:109:y:2016:i:c:p:1016-1025
    DOI: 10.1016/j.energy.2016.04.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216304844
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.04.071?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. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty: Part I: Multiple time frame approach," Applied Energy, Elsevier, vol. 88(4), pages 1059-1067, April.
    2. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    3. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    4. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    5. Tian, Zhe & Niu, Jide & Lu, Yakai & He, Shunming & Tian, Xue, 2016. "The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy," Applied Energy, Elsevier, vol. 165(C), pages 430-444.
    6. Al-Mansour, Fouad & Kožuh, Mitja, 2007. "Risk analysis for CHP decision making within the conditions of an open electricity market," Energy, Elsevier, vol. 32(10), pages 1905-1916.
    7. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty. Part II: Decision theory-based assessment of planning alternatives," Applied Energy, Elsevier, vol. 88(4), pages 1075-1083, April.
    8. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    9. Jradi, M. & Riffat, S., 2014. "Tri-generation systems: Energy policies, prime movers, cooling technologies, configurations and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 396-415.
    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. Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
    2. Bohlayer, Markus & Zöttl, Gregor, 2018. "Low-grade waste heat integration in distributed energy generation systems - An economic optimization approach," Energy, Elsevier, vol. 159(C), pages 327-343.
    3. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    4. Kim, Min Jae & Kim, Tong Seop & Flores, Robert J. & Brouwer, Jack, 2020. "Neural-network-based optimization for economic dispatch of combined heat and power systems," Applied Energy, Elsevier, vol. 265(C).
    5. Tataraki, Kalliopi G. & Kavvadias, Konstantinos C. & Maroulis, Zacharias B., 2018. "A systematic approach to evaluate the economic viability of Combined Cooling Heating and Power systems over conventional technologies," Energy, Elsevier, vol. 148(C), pages 283-295.
    6. Bai, Zhang & Liu, Qibin & Gong, Liang & Lei, Jing, 2019. "Application of a mid-/low-temperature solar thermochemical technology in the distributed energy system with cooling, heating and power production," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Antonio Piacentino & Roberto Gallea & Pietro Catrini & Fabio Cardona & Domenico Panno, 2016. "On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation," Energies, MDPI, vol. 9(12), pages 1-31, December.
    8. Bai, Zhang & Liu, Taixiu & Liu, Qibin & Lei, Jing & Gong, Liang & Jin, Hongguang, 2018. "Performance investigation of a new cooling, heating and power system with methanol decomposition based chemical recuperation process," Applied Energy, Elsevier, vol. 229(C), pages 1152-1163.
    9. Onishi, Viviani C. & Antunes, Carlos H. & Fraga, Eric S. & Cabezas, Heriberto, 2019. "Stochastic optimization of trigeneration systems for decision-making under long-term uncertainty in energy demands and prices," Energy, Elsevier, vol. 175(C), pages 781-797.
    10. 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).
    11. 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.
    12. 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.
    13. 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.

    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. Bai, Zhang & Liu, Taixiu & Liu, Qibin & Lei, Jing & Gong, Liang & Jin, Hongguang, 2018. "Performance investigation of a new cooling, heating and power system with methanol decomposition based chemical recuperation process," Applied Energy, Elsevier, vol. 229(C), pages 1152-1163.
    2. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    3. 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).
    4. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    5. Antonio Piacentino & Roberto Gallea & Pietro Catrini & Fabio Cardona & Domenico Panno, 2016. "On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation," Energies, MDPI, vol. 9(12), pages 1-31, December.
    6. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    7. Kang, Ligai & Yang, Junhong & An, Qingsong & Deng, Shuai & Zhao, Jun & Wang, Hui & Li, Zelin, 2017. "Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff," Applied Energy, Elsevier, vol. 194(C), pages 454-466.
    8. Capuder, Tomislav & Mancarella, Pierluigi, 2014. "Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options," Energy, Elsevier, vol. 71(C), pages 516-533.
    9. Tataraki, Kalliopi G. & Kavvadias, Konstantinos C. & Maroulis, Zacharias B., 2018. "A systematic approach to evaluate the economic viability of Combined Cooling Heating and Power systems over conventional technologies," Energy, Elsevier, vol. 148(C), pages 283-295.
    10. Tian, Zhe & Niu, Jide & Lu, Yakai & He, Shunming & Tian, Xue, 2016. "The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy," Applied Energy, Elsevier, vol. 165(C), pages 430-444.
    11. Gelegenis, John & Mavrotas, George, 2017. "An analytical study of critical factors in residential cogeneration optimization," Applied Energy, Elsevier, vol. 185(P2), pages 1625-1632.
    12. Walden, Jasper V.M. & Bähr, Martin & Glade, Anselm & Gollasch, Jens & Tran, A. Phong & Lorenz, Tom, 2023. "Nonlinear operational optimization of an industrial power-to-heat system with a high temperature heat pump, a thermal energy storage and wind energy," Applied Energy, Elsevier, vol. 344(C).
    13. Fadhil Y. Al-Aboosi & Mahmoud M. El-Halwagi, 2019. "A Stochastic Optimization Approach to the Design of Shale Gas/Oil Wastewater Treatment Systems with Multiple Energy Sources under Uncertainty," Sustainability, MDPI, vol. 11(18), pages 1-39, September.
    14. Pini Prato, Alessandro & Strobino, Fabrizio & Broccardo, Marco & Parodi Giusino, Luigi, 2012. "Integrated management of cogeneration plants and district heating networks," Applied Energy, Elsevier, vol. 97(C), pages 590-600.
    15. Schachter, J.A. & Mancarella, P., 2016. "A critical review of Real Options thinking for valuing investment flexibility in Smart Grids and low carbon energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 261-271.
    16. Niu, Jide & Tian, Zhe & Lu, Yakai & Zhao, Hongfang & Lan, Bo, 2019. "A robust optimization model for designing the building cooling source under cooling load uncertainty," Applied Energy, Elsevier, vol. 241(C), pages 390-403.
    17. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty: Part I: Multiple time frame approach," Applied Energy, Elsevier, vol. 88(4), pages 1059-1067, April.
    18. Olamaei, Javad & Nazari, Mohammad Esmaeil & Bahravar, Sepideh, 2018. "Economic environmental unit commitment for integrated CCHP-thermal-heat only system with considerations for valve-point effect based on a heuristic optimization algorithm," Energy, Elsevier, vol. 159(C), pages 737-750.
    19. Sun, Li & Gai, Limei & Smith, Robin, 2017. "Site utility system optimization with operation adjustment under uncertainty," Applied Energy, Elsevier, vol. 186(P3), pages 450-456.
    20. Xin Liu & Yuzhang Ji & Ziyang Guo & Shufu Yuan & Yongxu Chen & Weijun Zhang, 2023. "Study of Key Parameters and Uncertainties Based on Integrated Energy Systems Coupled with Renewable Energy Sources," Sustainability, MDPI, vol. 15(23), pages 1-29, November.

    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:energy:v:109:y:2016:i:c:p:1016-1025. 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.journals.elsevier.com/energy .

    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.