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Planning and operation method of the regional integrated energy system considering economy and environment

Author

Listed:
  • Wang, Yongli
  • Wang, Yudong
  • Huang, Yujing
  • Li, Fang
  • Zeng, Ming
  • Li, Jiapu
  • Wang, Xiaohai
  • Zhang, Fuwei

Abstract

This paper presents a two-stage optimization method for a coupled capacity planning and operation problem, cast within the economical operation of Regional Integrated Energy System. The first stage optimization of the proposed model represents a regional integrated energy system planner whose purpose is to minimize its energy and environmental cost, while the second stage is an operation problem whose primary role is to achieve the optimal operation scheme of the system. The regional integrated energy system planner pursues best interests by co-optimizing the capacity configuration and power output of individual energy supply module, while the regional integrated energy system maximizes the installed capacity of renewable energy sources and minimizes the environmental costs. To illustrate the advantage of the proposed method, the NSGA-II algorithm and the mixed integer linear programming method are implemented to solve the model based on simulation. Besides, application of the optimization method proposed to the energy infrastructure of a regional integrated energy system in China is discussed, and the results obtained through simulation are compared to the bi-level optimization objectives. The results show that the proposed method is economical and effective in practical application.

Suggested Citation

  • Wang, Yongli & Wang, Yudong & Huang, Yujing & Li, Fang & Zeng, Ming & Li, Jiapu & Wang, Xiaohai & Zhang, Fuwei, 2019. "Planning and operation method of the regional integrated energy system considering economy and environment," Energy, Elsevier, vol. 171(C), pages 731-750.
    • Handle: RePEc:eee:energy:v:171:y:2019:i:c:p:731-750
    DOI: 10.1016/j.energy.2019.01.036
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    1. Quashie, Mike & Marnay, Chris & Bouffard, François & Joós, Géza, 2018. "Optimal planning of microgrid power and operating reserve capacity," Applied Energy, Elsevier, vol. 210(C), pages 1229-1236.
    2. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    3. Meybodi, Mehdi Aghaei & Behnia, Masud, 2011. "Impact of carbon tax on internal combustion engine size selection in a medium scale CHP system," Applied Energy, Elsevier, vol. 88(12), pages 5153-5163.
    4. Huang, Yun-Hsun & Wu, Jung-Hua & Hsu, Yu-Ju, 2016. "Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty," Energy, Elsevier, vol. 116(P1), pages 1145-1157.
    5. Lorestani, A. & Ardehali, M.M., 2018. "Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm," Energy, Elsevier, vol. 145(C), pages 839-855.
    6. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    7. Majewski, Dinah Elena & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems," Energy, Elsevier, vol. 118(C), pages 590-599.
    8. Alipour, Manijeh & Zare, Kazem & Seyedi, Heresh, 2018. "A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids," Energy, Elsevier, vol. 149(C), pages 135-146.
    9. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    10. Andrić, I. & Fournier, J. & Lacarrière, B. & Le Corre, O. & Ferrão, P., 2018. "The impact of global warming and building renovation measures on district heating system techno-economic parameters," Energy, Elsevier, vol. 150(C), pages 926-937.
    11. Li, Yantong & Huang, Gongsheng & Xu, Tao & Liu, Xiaoping & Wu, Huijun, 2018. "Optimal design of PCM thermal storage tank and its application for winter available open-air swimming pool," Applied Energy, Elsevier, vol. 209(C), pages 224-235.
    12. Leimert, Jonas M. & Neubert, Michael & Treiber, Peter & Dillig, Marius & Karl, Jürgen, 2018. "Combining the Heatpipe Reformer technology with hydrogen-intensified methanation for production of synthetic natural gas," Applied Energy, Elsevier, vol. 217(C), pages 37-46.
    13. Song, Tangnyu & Huang, Guohe & Zhou, Xiong & Wang, Xiuquan, 2018. "An inexact two-stage fractional energy systems planning model," Energy, Elsevier, vol. 160(C), pages 275-289.
    Full references (including those not matched with items on IDEAS)

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