Integrated optimal scheduling and predictive control for energy management of an urban complex considering building thermal dynamics

被引:27
|
作者
Jin, Xiaolong [1 ,3 ]
Qi, Fengyu [2 ,3 ]
Wu, Qiuwei [1 ]
Mu, Yunfei [3 ]
Jia, Hongjie [3 ]
Yu, Xiaodan [3 ]
Li, Zhuoyang [3 ]
机构
[1] Tech Univ Denmark DTU, Dept Elect Engn, Ctr Elect Power & Energy CEE, DK-2800 Lyngby, Denmark
[2] State Grid Tianjin Elect Power Corp, Chengxi Dist Supply Co, Tianjin, Peoples R China
[3] Tianjin Univ, Key Lab Smart Grid, Minist Educ, Tianjin 30072, Peoples R China
基金
中国国家自然科学基金;
关键词
Hierarchical structure; Integrated optimal scheduling and predictive control; Operating cost; Peak-valley load difference; Thermal dynamics; Urban complex; NEURAL-NETWORK; SMART BUILDINGS; MODEL; SYSTEM; SIMULATION; OPERATION; SERVICES; WALLS; LOADS; FLOW;
D O I
10.1016/j.ijepes.2020.106273
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, an integrated optimal scheduling and predictive control scheme with a hierarchical structure is proposed for energy management of an urban complex (UC). The proposed scheme consists of a scheduling layer optimizing the energy usage of the UC and a control layer controlling the heating, ventilation, and air conditioning (HVAC) in each individual building. In the control layer, a detailed physical model of the individual building with HVAC system is developed to predict its energy consumption while considering the thermal dynamics of the building envelope with multiple layers of construction material. In the scheduling layer, a multi objective optimal scheduling is formulated based on the predictive energy consumption of the buildings to reduce the peak-valley load difference and minimize the operating cost of the UC. Finally, the optimal control schedules are obtained and issued to the individual HVACs. Numerical results show that the proposed method can reduce the operating cost and reduce the peak-valley load difference for the UC. Meanwhile, the HVACs can be controlled in an optimal way within the limits of indoor temperature.
引用
收藏
页数:13
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