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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

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  • Sadeghian, H.R.
  • Ardehali, M.M.

Abstract

The utilization of energy efficient CHP (combined heat and power) systems provides opportunities for GENCOs (generation companies) to simultaneously increase their economic benefits and decrease environmental emissions. The goals of this study are to develop and simulate a novel approach for optimal economic dispatch scheduling for a GENCO to maximize economic profit and minimize environmental emissions based on integration of CHP systems with conventional TG (thermal power generating) units, where a DBD (double Benders decomposition) solution approach is proposed for optimization. The CHP PBUC (profit based unit commitment) problem with non-convex constraints for integration of CHP units into GENCOs generation portfolio is solved and, the results for several cases along with sensitivity analyses are reported. The results from DBD approach for optimization are validated based on comparison with those from gravitational search and imperialistic competitive algorithms as well as other algorithms examined in other studies. When CHP units are integrated with a 10-TG unit system, results from implementing the proposed DBD approach are extremely encouraging, as GENCO profit for providing electricity and heat energy is increased by 518.78% and environmental emissions are reduced by 7.57%, in comparison with case of GENCO using TG units for meeting the same electricity demand.

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  • 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.
    • Handle: RePEc:eee:energy:v:102:y:2016:i:c:p:10-23
    DOI: 10.1016/j.energy.2016.02.044
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    12. 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.
    13. Hadis Moradi & Mahdi Esfahanian & Amir Abtahi & Ali Zilouchian, 2017. "Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties," Energies, MDPI, vol. 10(9), pages 1-17, September.
    14. Kim, Tae Hyun & Shin, Hansol & Kwag, Kyuhyeong & Kim, Wook, 2020. "A parallel multi-period optimal scheduling algorithm in microgrids with energy storage systems using decomposed inter-temporal constraints," Energy, Elsevier, vol. 202(C).
    15. Geng, Zhaowei & Conejo, Antonio J. & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2017. "Electricity production scheduling under uncertainty: Max social welfare vs. min emission vs. max renewable production," Applied Energy, Elsevier, vol. 193(C), pages 540-549.
    16. 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).
    17. Witthayapraphakorn, Aphisak & Charnsethikul, Peerayuth, 2019. "Benders decomposition with special purpose method for the sub problem in lot sizing problem under uncertain demand," Operations Research Perspectives, Elsevier, vol. 6(C).
    18. 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.
    19. Fu, Yiwei & Lu, Zongxiang & Hu, Wei & Wu, Shuang & Wang, Yiting & Dong, Ling & Zhang, Jietan, 2019. "Research on joint optimal dispatching method for hybrid power system considering system security," Applied Energy, Elsevier, vol. 238(C), pages 147-163.
    20. 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.
    21. 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.
    22. Chaduvula, Hemanth & Das, Debapriya, 2023. "Analysis of microgrid configuration with optimal power injection from grid using point estimate method embedded fuzzy-particle swarm optimization," Energy, Elsevier, vol. 282(C).
    23. Xu Chen & Shuai Fang & Kangji Li, 2023. "Reinforcement-Learning-Based Multi-Objective Differential Evolution Algorithm for Large-Scale Combined Heat and Power Economic Emission Dispatch," Energies, MDPI, vol. 16(9), pages 1-23, April.
    24. Xiaofeng Dong & Chao Quan & Tong Jiang, 2018. "Optimal Planning of Integrated Energy Systems Based on Coupled CCHP," Energies, MDPI, vol. 11(10), pages 1-27, October.

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