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A new algorithm for combined heat and power dynamic economic dispatch considering valve-point effects

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  • Bahmani-Firouzi, Bahman
  • Farjah, Ebrahim
  • Seifi, Alireza

Abstract

In this study, combined heat and power units are incorporated in the practical reserve constrained dynamic economic dispatch, which minimizes total production costs considering realistic constraints such as ramp rate limits and valve-point effects over a short time span. The integration of combined heat and power units and considering power ramp constraints for these units necessitate an efficient tool to cope with joint characteristics of electricity power-heat. Unlike pervious approaches, the system spinning reserve requirements are clearly formulated in the problem and a novel charged system search algorithm is proposed to solve it. In the proposed algorithm a novel self-adaptive learning framework, adaptive selection operation and repelling force modeling are used in order to increase the population diversity and amend the convergence criteria. The proposed framework is applied for three small, medium and large test systems in order to evaluate its efficiency and feasibility.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:52:y:2013:i:c:p:320-332
    DOI: 10.1016/j.energy.2013.01.004
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    References listed on IDEAS

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    Cited by:

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    6. 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.
    7. 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).
    8. Ghasemi, Mojtaba & Aghaei, Jamshid & Akbari, Ebrahim & Ghavidel, Sahand & Li, Li, 2016. "A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems," Energy, Elsevier, vol. 107(C), pages 182-195.
    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. Jabari, Farkhondeh & Jabari, Hamid & Mohammadi-ivatloo, Behnam & Ghafouri, Jafar, 2019. "Optimal short-term coordination of water-heat-power nexus incorporating plug-in electric vehicles and real-time demand response programs," Energy, Elsevier, vol. 174(C), pages 708-723.
    11. 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.
    12. Basu, M., 2023. "Multi-county combined heat and power dynamic economic emission dispatch incorporating electric vehicle parking lot," Energy, Elsevier, vol. 275(C).
    13. Zou, Dexuan & Gong, Dunwei & Ouyang, Haibin, 2023. "The dynamic economic emission dispatch of the combined heat and power system integrated with a wind farm and a photovoltaic plant," Applied Energy, Elsevier, vol. 351(C).
    14. Xiong, Guojiang & Shi, Dongyuan, 2018. "Hybrid biogeography-based optimization with brain storm optimization for non-convex dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 157(C), pages 424-435.
    15. 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.
    16. SeyedGarmroudi, SeyedDavoud & Kayakutlu, Gulgun & Kayalica, M. Ozgur & Çolak, Üner, 2024. "Improved Pelican optimization algorithm for solving load dispatch problems," Energy, Elsevier, vol. 289(C).
    17. 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.
    18. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    19. Zhang, Qiang & Zou, Dexuan & Duan, Na, 2023. "An improved differential evolution using self-adaptable cosine similarity for economic emission dispatch," Energy, Elsevier, vol. 283(C).
    20. Wakui, Tetsuya & Kinoshita, Takahiro & Yokoyama, Ryohei, 2014. "A mixed-integer linear programming approach for cogeneration-based residential energy supply networks with power and heat interchanges," Energy, Elsevier, vol. 68(C), pages 29-46.
    21. Santos, Maria Izabel & Uturbey, Wadaed, 2018. "A practical model for energy dispatch in cogeneration plants," Energy, Elsevier, vol. 151(C), pages 144-159.

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