DECENTRALIZED APPROACH TO MULTI-ZONE GREY-BOX MODELING FOR MODEL-BASED PREDICTIVE CONTROL

被引：0

作者：

Joe, Jaewan ^{[1
]}

Cui, Borui ^{[1
]}

Im, Piljae ^{[1
]}

Dong, Jin ^{[1
]}

Teja, Kuruganti ^{[1
]}

机构：

[1] Oak Ridge Natl Lab, Oak Ridge, TN 37830 USA

来源：

2020 ASHRAE BUILDING PERFORMANCE ANALYSIS CONFERENCE AND SIMBUILD | 2020年

基金：

美国能源部;

关键词：

SYSTEM-IDENTIFICATION; CONTROL STRATEGY; PERFORMANCE; BUILDINGS; OPERATION; ENERGY;

D O I：

暂无

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This study aims to improve the easiness of utilizing the grey-box model (i.e., Resistance-Capacitance circuit) for Model- based Predictive Control (MPC). The primary barrier of implementing the MPC is estimating the control-oriented building model that needs to be computationally inexpensive and quick but reasonably precise in predicting building load and indoor conditions. The estimating of the model parameters becomes more complicated when the building scale is larger; e.g., multi-zone building. In this study, a decentralized approach is introduced; each zone is split and individually estimated with measured boundary temperature from adjacent zones integrated into one single system model. The proposed decentralized method is demonstrated with experimental data from a full-scale multi-zone test cell compared with the centraliozed reference case.

引用

页码：545 / 551

页数：7

共 19 条

[1]

[Anonymous], 2019, Mathworks<(R)

[2]

[Anonymous], 2017, ASHRAE Handbook - Fundamentals (SI)

[3]

Arendt K, 2018, ASHRAE IBPSA USA BUI, P173

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