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Capacity planning and optimization for integrated energy system in industrial park considering environmental externalities

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  • Sun, Jingqi
  • Ruze, Nuermaimaiti
  • Zhang, Jianjun
  • Shi, Jing
  • Shen, Boyang

Abstract

The integrated energy system (IES) is developing rapidly duo to its high energy efficiency and environmental protection. Environmental protection is an advantage of IES, and the costs of environmental externalities should be considered in the construction cost of IES in industrial parks. This paper considered the environmental externalities of coal, wind and photovoltaic power generation of industrial park IES (IP-IES) as a part of the unit cost of IP-IES, and constructed a capacity planning and optimization model, whose objective function is to minimize the cost per unit power generation. Subsequently, particle swarm optimization (PSO) is adopted into the model, and the model results are compared to the actual values, in order to determine the reasonable ratios of various types of capacity. Case study results show that: (1) considering environmental externality costs, photovoltaic and wind power have an advantage over thermal power. (2) Reasonable capacity planning can reduce the unit power generation cost.

Suggested Citation

  • Sun, Jingqi & Ruze, Nuermaimaiti & Zhang, Jianjun & Shi, Jing & Shen, Boyang, 2021. "Capacity planning and optimization for integrated energy system in industrial park considering environmental externalities," Renewable Energy, Elsevier, vol. 167(C), pages 56-65.
  • Handle: RePEc:eee:renene:v:167:y:2021:i:c:p:56-65
    DOI: 10.1016/j.renene.2020.11.045
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    1. Wang, Jinman & Wang, Ruogu & Zhu, Yucheng & Li, Jiayan, 2018. "Life cycle assessment and environmental cost accounting of coal-fired power generation in China," Energy Policy, Elsevier, vol. 115(C), pages 374-384.
    2. Li, Yingjue & Wei, Kexiang & Yang, Wenxian & Wang, Qiong, 2020. "Improving wind turbine blade based on multi-objective particle swarm optimization," Renewable Energy, Elsevier, vol. 161(C), pages 525-542.
    3. Arnaudo, Monica & Topel, Monika & Puerto, Pablo & Widl, Edmund & Laumert, Björn, 2019. "Heat demand peak shaving in urban integrated energy systems by demand side management - A techno-economic and environmental approach," Energy, Elsevier, vol. 186(C).
    4. 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.
    5. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
    6. Wang, Yongli & Li, Ruiwen & Dong, Huanran & Ma, Yuze & Yang, Jiale & Zhang, Fuwei & Zhu, Jinrong & Li, Shuqing, 2019. "Capacity planning and optimization of business park-level integrated energy system based on investment constraints," Energy, Elsevier, vol. 189(C).
    7. Turconi, Roberto & Boldrin, Alessio & Astrup, Thomas, 2013. "Life cycle assessment (LCA) of electricity generation technologies: Overview, comparability and limitations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 555-565.
    8. Wang, Yuwei & Tang, Liu & Yang, Yuanjuan & Sun, Wei & Zhao, Huiru, 2020. "A stochastic-robust coordinated optimization model for CCHP micro-grid considering multi-energy operation and power trading with electricity markets under uncertainties," Energy, Elsevier, vol. 198(C).
    9. Zhao, Xiaoli & Cai, Qiong & Ma, Chunbo & Hu, Yanan & Luo, Kaiyan & Li, William, 2017. "Economic evaluation of environmental externalities in China’s coal-fired power generation," Energy Policy, Elsevier, vol. 102(C), pages 307-317.
    10. Ajdad, H. & Filali Baba, Y. & Al Mers, A. & Merroun, O. & Bouatem, A. & Boutammachte, N., 2019. "Particle swarm optimization algorithm for optical-geometric optimization of linear fresnel solar concentrators," Renewable Energy, Elsevier, vol. 130(C), pages 992-1001.
    11. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
    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. Zhao, Xiaoli & Liu, Suwei & Yan, Fengguang & Yuan, Ziqian & Liu, Zhiwen, 2017. "Energy conservation, environmental and economic value of the wind power priority dispatch in China," Renewable Energy, Elsevier, vol. 111(C), pages 666-675.
    14. Pu, Lei & Wang, Xiuhui & Tan, Zhongfu & Wang, Huaqing & Yang, JiaCheng & Wu, Jing, 2020. "Is China's electricity price cross-subsidy policy reasonable? Comparative analysis of eastern, central, and western regions," Energy Policy, Elsevier, vol. 138(C).
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