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Stochastic multi-objective optimization of combined heat and power economic/emission dispatch

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  • Shaabani, Yousef ali
  • Seifi, Ali Reza
  • Kouhanjani, Masoud Joker

Abstract

In this paper, an optimization technique based on time-varying acceleration particle swarm optimization (TVAC-PSO) is applied for optimizing economic dispatch and emission reduction problems in a system consisting of CHP units. At first algorithm is used for deterministic model that for comparison with previous works. Besides, its convergence speed is adequately high. Then Monte Carlo method is implemented to solve the stochastic model providing real situation. In the Monte Carlo simulation you have a range of values as a result, and you are able to understand the risk and uncertainty in the model. Deterministic models used for conventional economic dispatch problems are not able to address some real conditions in practical applications. Deterministic models of power system applications are incapable to express the uncertainties that come from energy demand and supply of intermittent renewable systems. Due to the presence of these various uncertain variables stochastic attitude is inevitable in practical applications. Therefore, solving economic dispatch and emission reduction problems simultaneously and stochastically that is the main objective of this paper has a great level of importance. For modeling accurately, both power transmission losses and nonlinear fuel cost function are considered. The proposed method is applied to a 7-unit test system.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:141:y:2017:i:c:p:1892-1904
    DOI: 10.1016/j.energy.2017.11.124
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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. 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.
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    7. 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.
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    12. 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.
    13. Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Somayeh Asadi, 2020. "Optimal Operation of Multi-Carrier Energy Networks Considering Uncertain Parameters and Thermal Energy Storage," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    14. Li, Peng & Guo, Tianyu & Abeysekera, Muditha & Wu, Jianzhong & Han, Zhonghe & Wang, Zixuan & Yin, Yunxing & Zhou, Fengquan, 2021. "Intraday multi-objective hierarchical coordinated operation of a multi-energy system," Energy, Elsevier, vol. 228(C).
    15. SeyedGarmroudi, SeyedDavoud & Kayakutlu, Gulgun & Kayalica, M. Ozgur & Çolak, Üner, 2024. "Improved Pelican optimization algorithm for solving load dispatch problems," Energy, Elsevier, vol. 289(C).
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    17. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    18. Bonan Huang & Chaoming Zheng & Qiuye Sun & Ruixue Hu, 2019. "Optimal Economic Dispatch for Integrated Power and Heating Systems Considering Transmission Losses," Energies, MDPI, vol. 12(13), pages 1-19, June.
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