Optimal scheduling of smart building microgrids based on AQPSO
To enhance the economic efficiency and low-carbon performance of smart building operations， this paper proposes an optimal economic scheduling strategy for smart building microgrids based on the adaptive quantum particle swarm optimization （AQPSO）. Firstly， a smart building microgrid model incorpora...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2025-06-01
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| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=84c80d6a-5812-471b-8cb9-64bd7b6535df |
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| Summary: | To enhance the economic efficiency and low-carbon performance of smart building operations， this paper proposes an optimal economic scheduling strategy for smart building microgrids based on the adaptive quantum particle swarm optimization （AQPSO）. Firstly， a smart building microgrid model incorporating photovoltaic， wind power， and electric vehicle （EV） is established， considering constraints such as power balance， thermal comfort， and the total charging/discharging power of EV clusters， with the objective of minimizing energy costs over the building’s operational cycle. Secondly， the improved quantum particle swarm optimization （QPSO） is improved through adaptive parameter control， and the AQPSO is employed to solve the model. Finally， four scenarios are set up for case analysis. The results demonstrate that the AQPSO outperforms traditional methods in terms of convergence speed and optimization capability. The proposed model and optimal scheduling strategy effectively reduce building operating costs， carbon emissions， and carbon emission costs， while improving the utilization rate of clean energy. |
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| ISSN: | 1007-1881 |