Challenges of implementing economic model predictive control strategy for buildings interacting with smart energy systems

被引：62

作者：

Zong, Yi ^{[1
]}

Boening, Georg Martin ^{[2
]}

Santos, Rui Mirra ^{[3
]}

You, Shi ^{[1
]}

Hu, Junjie ^{[1
]}

Han, Xue ^{[1
]}

机构：

[1] Tech Univ Denmark, Dept Elect Engn, Ctr Elect Power & Energy, Riso Campus,Frederiksborgvej 399, DK-4000 Roskilde, Denmark

[2] Berlin Energy Agcy, Brummerstr 74, D-14195 Berlin, Germany

[3] Univ Lisbon, Inst Super Tecn, IDMEC, Av Rovisco Pais, P-1049001 Lisbon, Portugal

来源：

APPLIED THERMAL ENGINEERING | 2017年 / 114卷

关键词：

Active smart building; Data availability; Economic model predictive control; Modelling; Optimization; State estimation; STABILITY;

D O I：

10.1016/j.applthermaleng.2016.11.141

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

When there is a high penetration of renewables in the energy system, it requires proactive control of large numbers of distributed demand response resources to maintain the system's reliability and improve its operational economics. This paper presents the Economic Model Predictive Control (EMPC) strategy for energy management in smart buildings, which can act as active users interacting with smart energy systems. The challenges encountered during the implementation of EMPC for active demand side management are investigated in detail in this paper. A pilot testing study shows energy savings and load shifting can be achieved by applying EMPC with weather forecast and dynamic power price signals. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：1476 / 1486

页数：11

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