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Combined Heat and Power Economic Dispatching within Energy Network using Hybrid Metaheuristic Technique

Author

Listed:
  • Paramjeet Kaur

    (Department of Electrical & Electronics Engineering, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal 462033, India)

  • Krishna Teerth Chaturvedi

    (Department of Electrical & Electronics Engineering, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal 462033, India)

  • Mohan Lal Kolhe

    (Faculty of Engineering and Science, University of Agder, P.O. Box 422, 4604 Kristiansand, Norway)

Abstract

Combined heat and power (CHP) plants have opportunities to work as distributed power generation for providing heat and power demand. Furthermore, CHP plants contribute effectively to overcoming the intermittence of renewable energy sources as well as load dynamics. CHP plants need optimal solution(s) for providing electrical and heat energy demand simultaneously within the smart network environment. CHP or cogeneration plant operations need appropriate techno-economic dispatching of combined heat and power with minimising produced energy cost. The interrelationship between heat and power development in a CHP unit, the valve point loading effect, and forbidden working regions of a thermal power plant make the CHP economic dispatch’s (CHPED) objective function discontinuous. It adds complexity in the CHPED optimisation process. The key objective of the CHPED is operating cost minimisation while meeting the desired power and heat demand. To optimise the dispatch operation, three different algorithms, like Jaya algorithm, Rao 3 algorithm, and hybrid CHPED algorithm (based on first two) are adopted containing different equality and inequality restrictions of generating units. The hybrid CHPED algorithm is developed by the authors, and it can handle all of the constraints. The success of the suggested algorithms is assessed on two test systems; 5-units and 24-unit power plants.

Suggested Citation

  • Paramjeet Kaur & Krishna Teerth Chaturvedi & Mohan Lal Kolhe, 2023. "Combined Heat and Power Economic Dispatching within Energy Network using Hybrid Metaheuristic Technique," Energies, MDPI, vol. 16(3), pages 1-17, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1221-:d:1044510
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    References listed on IDEAS

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    1. 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.
    2. Abdollahi, Elnaz & Wang, Haichao & Lahdelma, Risto, 2016. "An optimization method for multi-area combined heat and power production with power transmission network," Applied Energy, Elsevier, vol. 168(C), pages 248-256.
    3. 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.
    4. Zou, Dexuan & Li, Steven & Wang, Gai-Ge & Li, Zongyan & Ouyang, Haibin, 2016. "An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects," Applied Energy, Elsevier, vol. 181(C), pages 375-390.
    5. Ahmed Ginidi & Abdallah Elsayed & Abdullah Shaheen & Ehab Elattar & Ragab El-Sehiemy, 2021. "An Innovative Hybrid Heap-Based and Jellyfish Search Algorithm for Combined Heat and Power Economic Dispatch in Electrical Grids," Mathematics, MDPI, vol. 9(17), pages 1-25, August.
    6. Subbaraj, P. & Rengaraj, R. & Salivahanan, S., 2009. "Enhancement of combined heat and power economic dispatch using self adaptive real-coded genetic algorithm," Applied Energy, Elsevier, vol. 86(6), pages 915-921, June.
    7. 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.
    8. Rong, Aiying & Lahdelma, Risto, 2007. "An efficient envelope-based Branch and Bound algorithm for non-convex combined heat and power production planning," European Journal of Operational Research, Elsevier, vol. 183(1), pages 412-431, November.
    9. 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.
    10. 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.
    11. 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).
    12. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Gharehpetian, G.B., 2018. "A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2128-2143.
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