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Optimization of Combined Heat and Power Systems by Meta-Heuristic Algorithms: An Overview

Author

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  • Ali Sulaiman Alsagri

    (Department of Mechanical Engineering, College of Engineering, Qassim University, Unaizah 56452, Saudi Arabia)

  • Abdulrahman A. Alrobaian

    (Department of Mechanical Engineering, College of Engineering, Qassim University, Buraydah 51431, Saudi Arabia)

Abstract

Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed, based on numerical, experimental, parametric, and algorithmic optimization routes. Due to the significance of algorithmic optimization, as a systematic method for optimizing energy systems, this novel review paper is focused on the meta-heuristic optimization algorithms, implemented in CHP energy systems. By considering the applied objective functions, the main sections are divided into single-objective and multi-objective algorithms. In each case, the units’ combination is briefly detailed, the objective functions are introduced, and analyses are conducted. The main aim of this paper is to gather a database for the optimization of CHPs, demonstrate the effect of the applied optimization methods on the objective functions, and finally, introduce the most efficient methods. The most significant feature of this paper is that it covers all types of CHP optimization issues including scheduling, sizing, and designing problems, finding the extent of each optimization issue in the relevant papers in the last decade. Based on the findings, in the single-objective problems the combined heat and power economic dispatch (CHPED) issue as a subcategory of the scheduling problems is introduced as the most paid topic; the designing issue is known as the lowest paid topic. In the multi-objective problems, working on various types of CHP optimization problems has been conducted with an almost similar share. The combined heat and power economic emission dispatch (CHPEED) problem with the most share, and the sizing issue with the lowest share. The CHP designing and sizing optimization issues could be introduced as topics to work on more in the future. Additionally, the numerical results of CHPED and CHPEED problems solved by various algorithms are presented and compared. In this regard, specified test systems are considered.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5977-:d:891301
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    as
    1. Kazemiani-Najafabadi, Parisa & Amiri Rad, Ehsan, 2021. "Multi-objective optimization of a novel offshore CHP plant based on a 3E analysis," Energy, Elsevier, vol. 224(C).
    2. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2019. "Solving the combined heat and power economic dispatch problems by an improved genetic algorithm and a new constraint handling strategy," Applied Energy, Elsevier, vol. 237(C), pages 646-670.
    3. 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.
    4. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2017. "Generation and storage scheduling of combined heat and power," Energy, Elsevier, vol. 124(C), pages 693-705.
    5. Basu, M., 2019. "Squirrel search algorithm for multi-region combined heat and power economic dispatch incorporating renewable energy sources," Energy, Elsevier, vol. 182(C), pages 296-305.
    6. Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Nowdeh, Saber Arabi & Ramachandaramurthy, Vigna K. & Kalam, Akhtar & Guerrero, Josep M., 2020. "Optimal allocation for combined heat and power system with respect to maximum allowable capacity for reduced losses and improved voltage profile and reliability of microgrids considering loading condi," Energy, Elsevier, vol. 196(C).
    7. Vishwanathan, Gokul & Sculley, Julian P. & Fischer, Adam & Zhao, Ji-Cheng, 2018. "Techno-economic analysis of high-efficiency natural-gas generators for residential combined heat and power," Applied Energy, Elsevier, vol. 226(C), pages 1064-1075.
    8. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "Hybrid Gravitational Search Algorithm-Particle Swarm Optimization with Time Varying Acceleration Coefficients for large scale CHPED problem," Energy, Elsevier, vol. 126(C), pages 841-853.
    9. Aboelsood Zidan & Hossam A. Gabbar, 2016. "DG Mix and Energy Storage Units for Optimal Planning of Self-Sufficient Micro Energy Grids," Energies, MDPI, vol. 9(8), pages 1-18, August.
    10. Azizipanah-Abarghooee, Rasoul & Niknam, Taher & Bina, Mohammad Amin & Zare, Mohsen, 2015. "Coordination of combined heat and power-thermal-wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods," Energy, Elsevier, vol. 79(C), pages 50-67.
    11. Garcia-Saez, Irene & Méndez, Juan & Ortiz, Carlos & Loncar, Drazen & Becerra, José A. & Chacartegui, Ricardo, 2019. "Energy and economic assessment of solar Organic Rankine Cycle for combined heat and power generation in residential applications," Renewable Energy, Elsevier, vol. 140(C), pages 461-476.
    12. 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.
    13. Abusoglu, Aysegul & Kanoglu, Mehmet, 2009. "Exergoeconomic analysis and optimization of combined heat and power production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2295-2308, December.
    14. 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.
    15. Elsido, Cristina & Bischi, Aldo & Silva, Paolo & Martelli, Emanuele, 2017. "Two-stage MINLP algorithm for the optimal synthesis and design of networks of CHP units," Energy, Elsevier, vol. 121(C), pages 403-426.
    16. Liangce He & Zhigang Lu & Lili Pan & Hao Zhao & Xueping Li & Jiangfeng Zhang, 2019. "Optimal Economic and Emission Dispatch of a Microgrid with a Combined Heat and Power System," Energies, MDPI, vol. 12(4), pages 1-19, February.
    17. Akbar Maleki & Marc A. Rosen & Fathollah Pourfayaz, 2017. "Optimal Operation of a Grid-Connected Hybrid Renewable Energy System for Residential Applications," Sustainability, MDPI, vol. 9(8), pages 1-20, July.
    18. Pandian Vasant & Gerhard-Wilhelm Weber & Vo Ngoc Dieu, 2015. "Classical and Hybrid Optimization Approaches and Their Applications in Engineering and Economics," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-2, June.
    19. 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.
    20. Gimelli, A. & Mottola, F. & Muccillo, M. & Proto, D. & Amoresano, A. & Andreotti, A. & Langella, G., 2019. "Optimal configuration of modular cogeneration plants integrated by a battery energy storage system providing peak shaving service," Applied Energy, Elsevier, vol. 242(C), pages 974-993.
    21. Aikaterini Papadimitriou & Vassilios Vassiliou & Kalliopi Tataraki & Eugenia Giannini & Zacharias Maroulis, 2020. "Economic Assessment of Cogeneration Systems in Operation," Energies, MDPI, vol. 13(9), pages 1-15, May.
    22. Bach Hoang Dinh & Thang Trung Nguyen & Nguyen Vu Quynh & Le Van Dai, 2018. "A Novel Method for Economic Dispatch of Combined Heat and Power Generation," Energies, MDPI, vol. 11(11), pages 1-27, November.
    23. Zidan, Aboelsood & Gabbar, Hossam A. & Eldessouky, Ahmed, 2015. "Optimal planning of combined heat and power systems within microgrids," Energy, Elsevier, vol. 93(P1), pages 235-244.
    24. N. Jayakumar & S. Subramanian & E.B. Elanchezhian & S. Ganesan, 2015. "An application of grey wolf optimisation for combined heat and power dispatch," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 11(2), pages 183-206.
    25. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "Economic dispatch of multiple energy carriers," Energy, Elsevier, vol. 138(C), pages 861-872.
    26. 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.
    27. Jafari, Amirreza & Ganjeh Ganjehlou, Hamed & Khalili, Tohid & Bidram, Ali, 2020. "A fair electricity market strategy for energy management and reliability enhancement of islanded multi-microgrids," Applied Energy, Elsevier, vol. 270(C).
    28. Costa, M. & Di Blasio, G. & Prati, M.V. & Costagliola, M.A. & Cirillo, D. & La Villetta, M. & Caputo, C. & Martoriello, G., 2020. "Multi-objective optimization of a syngas powered reciprocating engine equipping a combined heat and power unit," Applied Energy, Elsevier, vol. 275(C).
    29. Jiecheng Zhu & Xitian Wang & Da Xie & Chenghong Gu, 2019. "Control Strategy for MGT Generation System Optimized by Improved WOA to Enhance Demand Response Capability," Energies, MDPI, vol. 12(16), pages 1-20, August.
    30. Mellal, Mohamed Arezki & Williams, Edward J., 2015. "Cuckoo optimization algorithm with penalty function for combined heat and power economic dispatch problem," Energy, Elsevier, vol. 93(P2), pages 1711-1718.
    31. Shaabani, Yousef ali & Seifi, Ali Reza & Kouhanjani, Masoud Joker, 2017. "Stochastic multi-objective optimization of combined heat and power economic/emission dispatch," Energy, Elsevier, vol. 141(C), pages 1892-1904.
    32. Sanaye, Sepehr & Mohammadi Nasab, Amir, 2012. "Modeling and optimizing a CHP system for natural gas pressure reduction plant," Energy, Elsevier, vol. 40(1), pages 358-369.
    33. Kong, Xiangyu & Sun, Fangyuan & Huo, Xianxu & Li, Xue & Shen, Yu, 2020. "Hierarchical optimal scheduling method of heat-electricity integrated energy system based on Power Internet of Things," Energy, Elsevier, vol. 210(C).
    34. Ahmadi, Pouria & Dincer, Ibrahim, 2010. "Exergoenvironmental analysis and optimization of a cogeneration plant system using Multimodal Genetic Algorithm (MGA)," Energy, Elsevier, vol. 35(12), pages 5161-5172.
    35. Zou, Dexuan & Gong, Dunwei, 2022. "Differential evolution based on migrating variables for the combined heat and power dynamic economic dispatch," Energy, Elsevier, vol. 238(PA).
    36. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Seifi, Alireza, 2013. "A new algorithm for combined heat and power dynamic economic dispatch considering valve-point effects," Energy, Elsevier, vol. 52(C), pages 320-332.
    37. Dongmin Yu & Yuanzhu Meng & Gangui Yan & Gang Mu & Dezhi Li & Simon Le Blond, 2017. "Sizing Combined Heat and Power Units and Domestic Building Energy Cost Optimisation," Energies, MDPI, vol. 10(6), pages 1-17, June.
    38. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2017. "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, Elsevier, vol. 202(C), pages 308-322.
    39. Lorestani, A. & Ardehali, M.M., 2018. "Optimization of autonomous combined heat and power system including PVT, WT, storages, and electric heat utilizing novel evolutionary particle swarm optimization algorithm," Renewable Energy, Elsevier, vol. 119(C), pages 490-503.
    40. Liu, Ming & Wang, Shan & Yan, Junjie, 2021. "Operation scheduling of a coal-fired CHP station integrated with power-to-heat devices with detail CHP unit models by particle swarm optimization algorithm," Energy, Elsevier, vol. 214(C).
    41. Yongli Wang & Haiyang Yu & Mingyue Yong & Yujing Huang & Fuli Zhang & Xiaohai Wang, 2018. "Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss," Energies, MDPI, vol. 11(7), pages 1-21, June.
    42. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
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