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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 optimization algorithm

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  • Arandian, B.
  • Ardehali, M.M.

Abstract

Combined heat and power (CHP) units are efficient from view point of source energy, however, for maximum utility company economic profit, it is necessary to account for all revenues and expenditures. The goal of this study is to examine the effects of considerations for environmental emissions in optimal combination and allocation of renewable and non-renewable CHP technologies including fuel cells (FC), internal combustion engines (ICE), and micro turbine (MT) in heat and electricity distribution networks based on improved particle swarm optimization algorithm, where the economic profit of utility company as the CHP owner and operator is maximized over the operation horizon. When all three technologies are available, the optimal combination and allocation results show that FC-CHP and MT-CHP are the preferred technologies and, the environmental emission costs do not allow for ICE-CHP technology to be included in the combination and, the yearly utility company economic profit is increased by 10.39, 28.37, and 13.95% due to optimal combination and allocation of CHP units in comparison with optimal allocation of FC, ICE, and MT technologies on individual basis, respectively. Also, by analyzing various HPRs, it is determined that the yearly utility company economic profit is increased when HPR is decreased.

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  • 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.
    • Handle: RePEc:eee:energy:v:140:y:2017:i:p1:p:466-480
    DOI: 10.1016/j.energy.2017.08.101
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    5. Yadegari, Saeed & Abdi, Hamdi & Nikkhah, Saman, 2020. "Risk-averse multi-objective optimal combined heat and power planning considering voltage security constraints," Energy, Elsevier, vol. 212(C).
    6. Zhang, Yan & Meng, Fanlin & Wang, Rui & Kazemtabrizi, Behzad & Shi, Jianmai, 2019. "Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid," Energy, Elsevier, vol. 179(C), pages 1265-1278.
    7. Kwan, Trevor Hocksun & Shen, Yongting & Yao, Qinghe, 2019. "An energy management strategy for supplying combined heat and power by the fuel cell thermoelectric hybrid system," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. 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.
    9. Arul Rajagopalan & Dhivya Swaminathan & Meshal Alharbi & Sudhakar Sengan & Oscar Danilo Montoya & Walid El-Shafai & Mostafa M. Fouda & Moustafa H. Aly, 2022. "Modernized Planning of Smart Grid Based on Distributed Power Generations and Energy Storage Systems Using Soft Computing Methods," Energies, MDPI, vol. 15(23), pages 1-18, November.

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