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Optimal scheduling of building integrated energy systems using an improved ant lion algorithm
[Technical characteristics of China's new generation power system in energy transformation]

Author

Listed:
  • Liming Wei
  • Shuo Xv

Abstract

In order to deal with the increasingly severe energy shortage problem, to find new energy solutions and to alleviate the dual pressure of domestic energy and environment, building a new type of multi-energy complementary power system has become one of the hot issues in recent years. This paper presents an optimal scheduling model of building integrated energy system (BIES) based on the comprehensive utilization of electricity, heat and gas. Based on the traditional combined cooling, heating, and power (CCHP) system, this model adds wind power and photoelectric renewable energy power generation systems, ground source heat pump system and energy storage system. Then, taking the environmental cost and system operation and maintenance cost as the objective function, it is solved by using the improved multi-objective ant lion algorithm based on differential evolution. Finally, a building in Northeast China is taken as an example to verify the simulation. The simulation results show that the optimal scheduling model of building integrated energy system proposed in this paper can promote the consumption of renewable energy such as wind power and photoelectric, realize the peak cutting and valley filling of power load, effectively reduce the economic operation cost of the system, reduce carbon emissions and effectively solve the problem of environmental pollution to a certain extent.

Suggested Citation

  • Liming Wei & Shuo Xv, 2022. "Optimal scheduling of building integrated energy systems using an improved ant lion algorithm [Technical characteristics of China's new generation power system in energy transformation]," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 720-729.
    • Handle: RePEc:oup:ijlctc:v:17:y:2022:i::p:720-729.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctac054
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    References listed on IDEAS

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    1. Roy, Kallol & Mandal, Kamal Krishna & Mandal, Atis Chandra, 2019. "Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system," Energy, Elsevier, vol. 167(C), pages 402-416.
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    Cited by:

    1. Ye Li & Shixuan Li & Shiyao Xia & Bojia Li & Xinyu Zhang & Boyuan Wang & Tianzhen Ye & Wandong Zheng, 2023. "A Review on the Policy, Technology and Evaluation Method of Low-Carbon Buildings and Communities," Energies, MDPI, vol. 16(4), pages 1-43, February.
    2. Auza, Anna & Asadi, Ehsan & Chenari, Behrang & Gameiro da Silva, Manuel, 2024. "Review of cost objective functions in multi-objective optimisation analysis of buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

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