三峡大学学报（自然科学版）2025，Vol.47Issue(4)：80-87,8.DOI:10.13393/j.cnki.issn.1672-948X.2025.04.011
基于MPC的低碳建筑光储系统能源管理方法研究
Research on Energy Management Methods of Low-Carbon Buildings Photovoltaic Storage System Based on MPC
摘要
Abstract
As energy management within low carbon buildings,most studies use the control that maximizes energy self-consumption.Under the control,the photovoltaic(PV)storage system in a low-carbon building tends to charge the energy storage system during low electricity price hours,thus the energy bill is minimized.However,it causes the charging time of the energy storage system to be staggered with the output peak of PV.Therefore,the power generated by PV cannot be fully utilized by the users and transmitted to the grid.It will result in a output waste of PV.To address this phenomenon,firstly a model of temporal convolutional network-based PV output and user demand prediction is constructed in this paper,and then the model predictive control(MPC)is utilized to optimize the energy management in low-carbon buildings based on the prediction results.By minimizing the input of external grid power,MPC indirectly forces the PV power to be consumed by the users themselves as much as possible.Meanwhile,in order to prolong the lifetime of the energy storage system,the control will try to avoid it being in a high charge state for a long time.Finally,the simulation analysis proves that the adopted energy management method of low-carbon building can effectively improve the utilization rate of PV and extend the service life of the energy storage system.关键词
低碳建筑/能源管理/预测模型/储能系统/模型预测控制Key words
low carbon buildings/energy management/predictive modeling/energy storage systems/model predictive control分类
信息技术与安全科学引用本文复制引用
毛睿,向昆,范李平,赵剑楠,王灿,席磊,马辉..基于MPC的低碳建筑光储系统能源管理方法研究[J].三峡大学学报（自然科学版）,2025,47(4):80-87,8.基金项目
国家自然科学基金项目(52377191) （52377191）
