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Optimization Method of Multi-body Integrated Energy System Considering Air Compression Energy Storage

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International Conference on Neural Computing for Advanced Applications (NCAA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1869))

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Abstract

Integrated energy system (IES) with compressed air energy storage (CAES) has significant benefits in energy utilization and gradually becomes a research hotspot, and the problem of how to establish a set of integrated energy optimization operation model in the context of compressed air energy storage needs to be solved urgently. Based on the above background, a master-slave game strategy between energy service providers and load aggregators is proposed. Firstly, this paper introduces the system framework and the mathematical model of the equipment. Secondly, the optimal operation model is established for energy service provider (ESP) and load aggregator (LA) respectively, and two scenarios are set to verify the effectiveness of compressed air energy storage. The results show that the model proposed in this paper can effectively balance the interests of energy service provider and load aggregator and ensure the economy of the system.

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Acknowledgements

This work is supported in part by the Natural Science Youth Foundation of Shandong Province, China under Grant ZR2021QE240, and in part by PhD Research Fund of Shandong Jianzhu University, China under Grant X21040Z.

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Authors and Affiliations

  1. School of Information and Electrical Engineering, Shandong University of Construction, Jinan, 250101, China

    Chongyi Tian, Xiangshun Kong, Yubing Liu & Bo Peng

  2. ShandongKey: Laboratory of Intelligent Building·Technology, Jinan, 250101, China

    Chongyi Tian, Xiangshun Kong, Yubing Liu & Bo Peng

Authors
  1. Chongyi Tian
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  2. Xiangshun Kong
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  3. Yubing Liu
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  4. Bo Peng
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Corresponding author

Correspondence to Bo Peng .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Chaohu University, Hefei, China

    Yinggen Ke

  3. Chongqing University, Chongqing, China

    Zhou Wu

  4. South China Normal University, Guangzhou, China

    Tianyong Hao

  5. Hefei University of Technology, Hefei, China

    Zhao Zhang

  6. Technical University of Denmark, Kongens Lyngby, Denmark

    Weizhi Meng

  7. Chaohu University, Hefei, China

    Yuanyuan Mu

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Tian, C., Kong, X., Liu, Y., Peng, B. (2023). Optimization Method of Multi-body Integrated Energy System Considering Air Compression Energy Storage. In: Zhang, H., et al. International Conference on Neural Computing for Advanced Applications. NCAA 2023. Communications in Computer and Information Science, vol 1869. Springer, Singapore. https://doi.org/10.1007/978-981-99-5844-3_29

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  • DOI: https://doi.org/10.1007/978-981-99-5844-3_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5843-6

  • Online ISBN: 978-981-99-5844-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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