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Multi-attribute decision analysis for optimal design of park-level integrated energy systems based on load characteristics

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  • Wang, Meng
  • Zheng, J.H.
  • Li, Zhigang
  • Wu, Q.H.

Abstract

Considering the diversity of primary energy resources and load characteristics, this paper proposes a multi-attribute decision analysis method for the optimal design of park-level integrated energy systems (PLIES) in different areas. Firstly, a multi-objective optimization model is established to optimize the configuration designs and operation strategy of the PLIES, taking the peak-to-valley electric prices and the price-based demand response into consideration. Then, in order to figure out this model, this paper utilizes a multi-attribute decision analysis (MADA) support framework. The proposed MADA, consisting of a multi-objective optimal method designed with multi-objective particle swarm optimization (MOPSO) and an evidential reasoning-based multiple attribute decision-making method, is capable of tackling the decision analysis problem under various attributes. Finally, a case study is carried out for the hourly dispatch analysis and system utilization comparison, in order to evaluate the economic, energy saving and environmental performance under four park-level areas. The simulation studies indicate that: The PLIES proposed in this paper can alleviate the load pressure in peak horizon, as well as achieve better economic, energy saving and environmental benefits due to the optimal design and operation strategy compared with a separated production (SP) system.

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  • Wang, Meng & Zheng, J.H. & Li, Zhigang & Wu, Q.H., 2022. "Multi-attribute decision analysis for optimal design of park-level integrated energy systems based on load characteristics," Energy, Elsevier, vol. 254(PA).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pa:s0360544222012828
    DOI: 10.1016/j.energy.2022.124379
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    2. Jia, Jiandong & Li, Haiqiao & Wu, Di & Guo, Jiacheng & Jiang, Leilei & Fan, Zeming, 2024. "Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing," Renewable Energy, Elsevier, vol. 225(C).

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