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Research on Optimal Configuration of Landscape Storage in Public Buildings Based on Improved NSGA-II

Author

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  • Shibo Li

    (College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China)

  • Hu Zhou

    (College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China)

  • Genzhu Xu

    (College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China)

Abstract

The transition to clean and low-carbon energy in public buildings is crucial to energy saving and green social development. This paper focus on the sustainable development of public buildings and the construction of complementary power generation systems in existing public buildings. In the study, it was found that the constraints of the energy storage system could not be satisfied, which would result in the failure of the energy storage system for the purpose of peak regulation and stable operation of the microgrid. In order to satisfy the constraint conditions of the energy storage system, a spatial transformation method was proposed that improves the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The simulation results show that the spatial transformation Non-dominated Sorting Genetic Algorithm-II (STNSGA-II) has advantages in dealing with the strong constraints of the energy storage system. The introduction of the complementary power generation system with energy storage system in public buildings can save 23.74% to 31.17% from the perspective of optimal cost, and can reduce of CO 2 emissions by at least 2478 kg from the perspective of carbon emission reduction. This study presents a case for transforming public buildings from simple consumers of energy systems to active contributors supporting large-scale wind and PV access.

Suggested Citation

  • Shibo Li & Hu Zhou & Genzhu Xu, 2023. "Research on Optimal Configuration of Landscape Storage in Public Buildings Based on Improved NSGA-II," Sustainability, MDPI, vol. 15(2), pages 1-29, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1460-:d:1033445
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    References listed on IDEAS

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