IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v172y2019icp794-807.html
   My bibliography  Save this article

Multi-objective combined heat and power unit commitment using particle swarm optimization

Author

Listed:
  • Anand, Himanshu
  • Narang, Nitin
  • Dhillon, J.S.

Abstract

The unit commitment (UC) problem is formulated by undertaking dual operating mode combined heat and power (CHP) units along with thermal and heat units. The extraction and backpressure mode of the CHP unit provides the facility to adopt immediate change in the generation, which depends upon the ratio of the heat and power generation. The impact of dual-mode CHP (DM-CHP) unit has been examined on multi-objective (MO) economic and profit based models, in order to deal with pollutant emission along with cost/profit. The model of CHP-UC problem is a mixed integer model, hence to deal with binary and real variables, binary particle swarm optimization (BPSO) and PSO technique have been employed, respectively. To demonstrate the effectiveness of the optimization technique, two test systems of thermal UC problem have been undertaken and the results are compared. In order to verify the benefits of DM-CHP unit, three test systems of CHP-UC problem have been undertaken and the impact of backpressure and extraction mode of CHP unit has been investigated in terms of cost/profit and emission. It has been verified from the results that backpressure and extraction mode of the CHP unit provide diverse UC status and generation schedule.

Suggested Citation

  • Anand, Himanshu & Narang, Nitin & Dhillon, J.S., 2019. "Multi-objective combined heat and power unit commitment using particle swarm optimization," Energy, Elsevier, vol. 172(C), pages 794-807.
  • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:794-807
    DOI: 10.1016/j.energy.2019.01.155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219301719
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.01.155?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. Nazari, M.E. & Ardehali, M.M., 2017. "Profit-based unit commitment of integrated CHP-thermal-heat only units in energy and spinning reserve markets with considerations for environmental CO2 emission cost and valve-point effects," Energy, Elsevier, vol. 133(C), pages 621-635.
    2. Anand, Himanshu & Narang, Nitin & Dhillon, J.S., 2018. "Profit based unit commitment using hybrid optimization technique," Energy, Elsevier, vol. 148(C), pages 701-715.
    3. 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.
    4. Patwal, Rituraj Singh & Narang, Nitin & Garg, Harish, 2018. "A novel TVAC-PSO based mutation strategies algorithm for generation scheduling of pumped storage hydrothermal system incorporating solar units," Energy, Elsevier, vol. 142(C), pages 822-837.
    5. Sadeghian, H.R. & Ardehali, M.M., 2016. "A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on Benders decomposition," Energy, Elsevier, vol. 102(C), pages 10-23.
    6. Rong, Aiying & Lahdelma, Risto, 2017. "An efficient model and algorithm for the transmission-constrained multi-site combined heat and power system," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1106-1117.
    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. Aml Sayed & Mohamed Ebeed & Ziad M. Ali & Adel Bedair Abdel-Rahman & Mahrous Ahmed & Shady H. E. Abdel Aleem & Adel El-Shahat & Mahmoud Rihan, 2021. "A Hybrid Optimization Algorithm for Solving of the Unit Commitment Problem Considering Uncertainty of the Load Demand," Energies, MDPI, vol. 14(23), pages 1-21, November.
    2. Xiaolong Yang & Yan Li & Dongxiao Niu & Lijie Sun, 2019. "Research on the Economic Benefit Evaluation of Combined Heat and Power (CHP) Technical Renovation Projects Based on the Improved Factor Analysis and Incremental Method in China," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    3. Ali Sulaiman Alsagri & Abdulrahman A. Alrobaian, 2022. "Optimization of Combined Heat and Power Systems by Meta-Heuristic Algorithms: An Overview," Energies, MDPI, vol. 15(16), pages 1-34, August.
    4. Wang, Hong-Jiang & Pan, Jeng-Shyang & Nguyen, Trong-The & Weng, Shaowei, 2022. "Distribution network reconfiguration with distributed generation based on parallel slime mould algorithm," Energy, Elsevier, vol. 244(PB).
    5. 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).
    6. Liu, Yikui & Wu, Lei & Li, Jie, 2019. "Towards accurate modeling of dynamic startup/shutdown and ramping processes of thermal units in unit commitment problems," Energy, Elsevier, vol. 187(C).
    7. Alex Chamba & Carlos Barrera-Singaña & Hugo Arcos, 2023. "Optimal Reactive Power Dispatch in Electric Transmission Systems Using the Multi-Agent Model with Volt-VAR Control," Energies, MDPI, vol. 16(13), pages 1-25, June.
    8. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    9. Lei, Kaixuan & Chang, Jianxia & Wang, Xuebin & Guo, Aijun & Wang, Yimin & Ren, Chengqing, 2023. "Peak shaving and short-term economic operation of hydro-wind-PV hybrid system considering the uncertainty of wind and PV power," Renewable Energy, Elsevier, vol. 215(C).
    10. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    11. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. Perrigot, Antoine & Perier-Muzet, Maxime & Ortega, Pascal & Stitou, Driss, 2020. "Technical economic analysis of PV-driven electricity and cold cogeneration systems using particle swarm optimization algorithm," Energy, Elsevier, vol. 211(C).
    13. Fragiacomo, Petronilla & Lucarelli, Giuseppe & Genovese, Matteo & Florio, Gaetano, 2021. "Multi-objective optimization model for fuel cell-based poly-generation energy systems," Energy, Elsevier, vol. 237(C).
    14. Xiong, Guojiang & Shuai, Maohang & Hu, Xiao, 2022. "Combined heat and power economic emission dispatch using improved bare-bone multi-objective particle swarm optimization," Energy, Elsevier, vol. 244(PB).
    15. Zhu, Xiaodong & Zhao, Shihao & Yang, Zhile & Zhang, Ning & Xu, Xinzhi, 2022. "A parallel meta-heuristic method for solving large scale unit commitment considering the integration of new energy sectors," Energy, Elsevier, vol. 238(PC).
    16. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    17. Donghui Wang & Chunming Liu, 2019. "Combination Optimization Configuration Method of Capacitance and Resistance Devices for Suppressing DC Bias in Transformers," Energies, MDPI, vol. 12(9), pages 1-13, May.
    18. M. A. El-Shorbagy & A. A. Mousa & M. A. Farag, 2019. "An intelligent computing technique based on a dynamic-size subpopulations for unit commitment problem," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 911-944, September.
    19. Ali, E.S. & Elazim, S.M. Abd & Balobaid, A.S., 2023. "Implementation of coyote optimization algorithm for solving unit commitment problem in power systems," Energy, Elsevier, vol. 263(PA).
    20. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    21. Basu, Mousumi, 2023. "Fuel constrained commitment scheduling for combined heat and power dispatch incorporating electric vehicle parking lot," Energy, Elsevier, vol. 276(C).

    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. Abdi, Hamdi, 2021. "Profit-based unit commitment problem: A review of models, methods, challenges, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    2. 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.
    3. Arandian, B. & Ardehali, M.M., 2017. "Effects of environmental emissions on optimal combination and allocation of renewable and non-renewable CHP technologies in heat and electricity distribution networks based on improved particle swarm ," Energy, Elsevier, vol. 140(P1), pages 466-480.
    4. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    5. Hossein Lotfi & Mohammad Hasan Nikkhah, 2024. "Multi-Objective Profit-Based Unit Commitment with Renewable Energy and Energy Storage Units Using a Modified Optimization Method," Sustainability, MDPI, vol. 16(4), pages 1-29, February.
    6. Rizk-Allah, Rizk M. & Hassanien, Aboul Ella & Snášel, Václav, 2022. "A hybrid chameleon swarm algorithm with superiority of feasible solutions for optimal combined heat and power economic dispatch problem," Energy, Elsevier, vol. 254(PC).
    7. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    8. 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.
    9. Zhang, Han & Han, Zhonghe & Wu, Di & Li, Peng & Li, Peng, 2023. "Energy optimization and performance analysis of a novel integrated energy system coupled with solar thermal unit and preheated organic cycle under extended following electric load strategy," Energy, Elsevier, vol. 272(C).
    10. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    11. Qin, Xin & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    12. Skolfield, J. Kyle & Escobedo, Adolfo R., 2022. "Operations research in optimal power flow: A guide to recent and emerging methodologies and applications," European Journal of Operational Research, Elsevier, vol. 300(2), pages 387-404.
    13. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    14. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
    15. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(C).
    16. Basu, Mousumi, 2022. "Fuel constrained short-term hydrothermal generation scheduling," Energy, Elsevier, vol. 239(PD).
    17. 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).
    18. Zhang, Rongda & Wei, Jing & Zhao, Xiaoli & Liu, Yang, 2022. "Economic and environmental benefits of the integration between carbon sequestration and underground gas storage," Energy, Elsevier, vol. 260(C).
    19. Elattar, Ehab E., 2019. "Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm," Energy, Elsevier, vol. 171(C), pages 256-269.
    20. Pavan Kumar Singh & Nitin Singh & Richa Negi, 2021. "Short-Term Wind Power Prediction Using Hybrid Auto Regressive Integrated Moving Average Model and Dynamic Particle Swarm Optimization," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 15(2), pages 111-138, April.

    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:172:y:2019:i:c:p:794-807. 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.