IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v116y2014icp230-242.html
   My bibliography  Save this article

A probability constrained multi-objective optimization model for CCHP system operation decision support

Author

Listed:
  • Hu, Mengqi
  • Cho, Heejin

Abstract

Due to its capability to reduce carbon dioxide emission and to increase energy efficiency, the combined cooling, heating, and power (CCHP) system has attracted great attention during the last decade. A large number of deterministic and stochastic optimization models have been proposed to study the CCHP operation strategy. However, fewer studies have been conducted to optimize CCHP operation simultaneously with multiple objectives such as minimizing operational cost, primary energy consumption (PEC) and carbon dioxide emissions (CDE) considering the reliability of the CCHP operation strategy. In this research, we propose a stochastic multi-objective optimization model to optimize the CCHP operation strategy for different climate conditions based on operational cost, PEC and CDE. The probability constraints are added into the stochastic model to guarantee the optimized CCHP operation strategy is reliable to satisfy the stochastic energy demand. The study shows that a higher reliability level of the probability constraint will increase the operational cost, PEC and CDE. To assist the multi-objective decision analysis, we developed an incentive model for PEC and CDE reduction. The analysis results demonstrate how the incentive values for PEC and CDE reduction can be effectively determined using the proposed model for different climate locations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:116:y:2014:i:c:p:230-242
    DOI: 10.1016/j.apenergy.2013.11.065
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913009732
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.11.065?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. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    2. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Chunfa, 2010. "Particle swarm optimization for redundant building cooling heating and power system," Applied Energy, Elsevier, vol. 87(12), pages 3668-3679, December.
    3. Jiang-Jiang, Wang & Chun-Fa, Zhang & You-Yin, Jing, 2010. "Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China," Applied Energy, Elsevier, vol. 87(4), pages 1247-1259, April.
    4. Kavvadias, K.C. & Maroulis, Z.B., 2010. "Multi-objective optimization of a trigeneration plant," Energy Policy, Elsevier, vol. 38(2), pages 945-954, February.
    5. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    6. Thorin, Eva & Brand, Heike & Weber, Christoph, 2005. "Long-term optimization of cogeneration systems in a competitive market environment," Applied Energy, Elsevier, vol. 81(2), pages 152-169, June.
    7. Tichi, S.G. & Ardehali, M.M. & Nazari, M.E., 2010. "Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm," Energy Policy, Elsevier, vol. 38(10), pages 6240-6250, October.
    8. Pohekar, S. D. & Ramachandran, M., 2004. "Application of multi-criteria decision making to sustainable energy planning--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(4), pages 365-381, August.
    9. Wu, Jing-yi & Wang, Jia-long & Li, Sheng, 2012. "Multi-objective optimal operation strategy study of micro-CCHP system," Energy, Elsevier, vol. 48(1), pages 472-483.
    10. Shi, Bin & Yan, Lie-Xiang & Wu, Wei, 2013. "Multi-objective optimization for combined heat and power economic dispatch with power transmission loss and emission reduction," Energy, Elsevier, vol. 56(C), pages 135-143.
    11. Maraver, Daniel & Sin, Ana & Royo, Javier & Sebastián, Fernando, 2013. "Assessment of CCHP systems based on biomass combustion for small-scale applications through a review of the technology and analysis of energy efficiency parameters," Applied Energy, Elsevier, vol. 102(C), pages 1303-1313.
    12. Wang, Jiangfeng & Zhao, Pan & Niu, Xiaoqiang & Dai, Yiping, 2012. "Parametric analysis of a new combined cooling, heating and power system with transcritical CO2 driven by solar energy," Applied Energy, Elsevier, vol. 94(C), pages 58-64.
    13. Liu, Mingxi & Shi, Yang & Fang, Fang, 2013. "Optimal power flow and PGU capacity of CCHP systems using a matrix modeling approach," Applied Energy, Elsevier, vol. 102(C), pages 794-802.
    14. Rong, Aiying & Lahdelma, Risto, 2005. "An efficient linear programming model and optimization algorithm for trigeneration," Applied Energy, Elsevier, vol. 82(1), pages 40-63, September.
    15. Li, Sheng & Sui, Jun & Jin, Hongguang & Zheng, Jianjiao, 2013. "Full chain energy performance for a combined cooling, heating and power system running with methanol and solar energy," Applied Energy, Elsevier, vol. 112(C), pages 673-681.
    16. Cho, Heejin & Mago, Pedro J. & Luck, Rogelio & Chamra, Louay M., 2009. "Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme," Applied Energy, Elsevier, vol. 86(12), pages 2540-2549, December.
    17. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    18. Liu, Mingxi & Shi, Yang & Fang, Fang, 2012. "A new operation strategy for CCHP systems with hybrid chillers," Applied Energy, Elsevier, vol. 95(C), pages 164-173.
    19. Popli, Sahil & Rodgers, Peter & Eveloy, Valerie, 2012. "Trigeneration scheme for energy efficiency enhancement in a natural gas processing plant through turbine exhaust gas waste heat utilization," Applied Energy, Elsevier, vol. 93(C), pages 624-636.
    20. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    21. Jing, You-Yin & Bai, He & Wang, Jiang-Jiang, 2012. "A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources," Energy Policy, Elsevier, vol. 42(C), pages 286-296.
    Full references (including those not matched with items on IDEAS)

    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. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    2. 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.
    3. Wei, Dajun & Chen, Alian & Sun, Bo & Zhang, Chenghui, 2016. "Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system," Energy, Elsevier, vol. 98(C), pages 296-307.
    4. 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.
    5. Jayasekara, Saliya & Halgamuge, Saman K. & Attalage, Rahula A. & Rajarathne, Rohitha, 2014. "Optimum sizing and tracking of combined cooling heating and power systems for bulk energy consumers," Applied Energy, Elsevier, vol. 118(C), pages 124-134.
    6. Liu, Mingxi & Shi, Yang & Fang, Fang, 2014. "Combined cooling, heating and power systems: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 1-22.
    7. Al Moussawi, Houssein & Fardoun, Farouk & Louahlia, Hasna, 2017. "Selection based on differences between cogeneration and trigeneration in various prime mover technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 491-511.
    8. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    9. Wang, Jiang-Jiang & Xu, Zi-Long & Jin, Hong-Guang & Shi, Guo-hua & Fu, Chao & Yang, Kun, 2014. "Design optimization and analysis of a biomass gasification based BCHP system: A case study in Harbin, China," Renewable Energy, Elsevier, vol. 71(C), pages 572-583.
    10. Cao, Tao & Hwang, Yunho & Radermacher, Reinhard, 2017. "Development of an optimization based design framework for microgrid energy systems," Energy, Elsevier, vol. 140(P1), pages 340-351.
    11. 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.
    12. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    13. Liu, Mingxi & Shi, Yang & Fang, Fang, 2013. "Optimal power flow and PGU capacity of CCHP systems using a matrix modeling approach," Applied Energy, Elsevier, vol. 102(C), pages 794-802.
    14. Wang, Jiangjiang & Yang, Ying & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Life cycle assessment (LCA) optimization of solar-assisted hybrid CCHP system," Applied Energy, Elsevier, vol. 146(C), pages 38-52.
    15. Ahn, Hyeunguk & Rim, Donghyun & Freihaut, James D., 2018. "Performance assessment of hybrid chiller systems for combined cooling, heating and power production," Applied Energy, Elsevier, vol. 225(C), pages 501-512.
    16. Carvalho, Monica & Lozano, Miguel A. & Serra, Luis M., 2012. "Multicriteria synthesis of trigeneration systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 91(1), pages 245-254.
    17. Ahn, Hyeunguk & Freihaut, James D. & Rim, Donghyun, 2019. "Economic feasibility of combined cooling, heating, and power (CCHP) systems considering electricity standby tariffs," Energy, Elsevier, vol. 169(C), pages 420-432.
    18. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2018. "Effect of load following strategies, hardware, and thermal load distribution on stand-alone hybrid CCHP systems," Applied Energy, Elsevier, vol. 220(C), pages 735-753.
    19. Wang, Jiangjiang & Lu, Yanchao & Yang, Ying & Mao, Tianzhi, 2016. "Thermodynamic performance analysis and optimization of a solar-assisted combined cooling, heating and power system," Energy, Elsevier, vol. 115(P1), pages 49-59.
    20. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.

    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:appene:v:116:y:2014:i:c:p:230-242. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.