Deriving sequences of operation for air handling units through building performance optimization

被引：24

作者：

Gunay, H. Burak ^{[1
]}

Newsham, Guy ^{[2
]}

Ashouri, Araz ^{[2
]}

Wilton, Ian ^{[2
]}

机构：

[1] Carleton Univ, Dept Civil & Environm Engn, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada

[2] Natl Res Council Canada, Construct Res Ctr, Ottawa, ON, Canada

来源：

JOURNAL OF BUILDING PERFORMANCE SIMULATION | 2020年 / 13卷 / 05期

关键词：

Building energy performance; optimization; air handling unit; operation; MODEL-PREDICTIVE-CONTROL; IMPROVING ENERGY EFFICIENCY; CONTROL STRATEGY; ROBUST-CONTROL; CONTROL-SYSTEM; OUTDOOR AIR; FLOW RATE; EQUIPMENT; PLUG; UNCERTAINTIES;

D O I：

10.1080/19401493.2020.1793221

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Operational parameters of air handling units (AHUs) play an important role in the energy and comfort performance of commercial buildings. Current guidelines to determine these parameters are based on heuristics and are not informed by formal optimization. This paper presents a building performance optimization method to derive sequence of operations for multi-zone AHUs. To this end, 27 variants of a generic EnergyPlus office building model are built representing three levels of occupancy, envelope, and HVAC capacity scenarios. The supply temperature, morning start time, and economizer settings of the model are optimized for the 27 scenarios by using a genetic algorithm. The results highlight that optimal supply temperature setpoints transition from similar to 12 degrees C to a range of similar to 16 degrees C to similar to 20 degrees C over an outdoor temperature range of similar to 20 degrees C to similar to 0 degrees C. Energy savings are estimated as similar to 20% relative to a reference case with a constant supply temperature and preheating/precooling period.

引用

页码：501 / 515

页数：15

共 48 条

[21]

Hydeman M., 2015, RP1455 ASHRAE

[22]

Hydeman M, 2015, ASHRAE J, V57, P58

[23] Prediction-based online optimal control of outdoor air of multi-zone VAV air conditioning systems [J].

Jin, XQ ;

Ren, HG ;

Xiao, XK .

ENERGY AND BUILDINGS, 2005, 37 (09) :939-944

[24] Ten questions concerning model predictive control for energy efficient buildings [J].

Killian, M. ;

Kozek, M. .

BUILDING AND ENVIRONMENT, 2016, 105 :403-412

[25] MPC control for improving energy efficiency of a building air handler for multi-zone VAVs [J].

Liang, Wei ;

Quinte, Rebecca ;

Jia, Xiaobao ;

Sun, Jian-Qiao .

BUILDING AND ENVIRONMENT, 2015, 92 :256-268

[26] Prediction of plug loads in office buildings: Simplified and probabilistic methods [J].

Mahdavi, Ardeshir ;

Tahmasebi, Farhang ;

Kayalar, Mine .

ENERGY AND BUILDINGS, 2016, 129 :322-329

[27] The dark side of occupants' behaviour on building energy use [J].

Masoso, O. T. ;

Grobler, L. J. .

ENERGY AND BUILDINGS, 2010, 42 (02) :173-177

[28] Nonlinear multivariable control and performance analysis of an air-handling unit [J].

Moradi, Hamed ;

Saffar-Avval, Majid ;

Bakhtiari-Nejad, Firooz .

ENERGY AND BUILDINGS, 2011, 43 (04) :805-813

[29]

Morris R., 2016, Final Report - Updating CWEEDS Weather Files

[30] Minimizing delivered energy and life cycle cost using Graphical script: An office building retrofitting case [J].

Rabani, Mehrdad ;

Madessa, Habtamu Bayera ;

Mohseni, Omid ;

Nord, Natasa .

APPLIED ENERGY, 2020, 268

← 1 2 3 4 5 →