Design and control optimization of energy systems of smart buildings today and in the near future

doi:10.15302/J-FEM-2017005

Front. Eng

2017, Vol. 4

Issue (1) : 58-66 https://doi.org/10.15302/J-FEM-2017005

RESEARCH ARTICLE

Design and control optimization of energy systems of smart buildings today and in the near future

Shengwei WANG¹(

), Wenjie GANG^1,²

¹. Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong, China
². Department of Building Environment and Energy Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Download: PDF(1943 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Buildings contribute to a major part of energy consumption in urban areas, especially in areas like Hong Kong which is full of high-rise buildings. Smart buildings with high efficiency can reduce the energy consumption largely and help achieve green cities or smart cities. Design and control optimization of building energy systems therefore plays a significant role to obtain the optimal performance. This paper introduces a general methodology for the design and control optimization of building energy systems in the life cycle. When the design scheme of building energy systems is optimized, primary steps and related issues are introduced. To improve the operation performance, the optimal control strategies that can be used by different systems are presented and key issues are discussed. To demonstrate the effect of the methods, the energy system of a high-rise building is introduced. The design on the chilled water pump system and cooling towers is improved. The control strategies for chillers, pumps and fresh air systems are optimized. The energy saving and cost from the design and control optimization methods are analyzed. The presented methodology will provide users and stakeholders an effective approach to improve the energy efficiency of building energy systems and promote the development of smart buildings and smart cities.

Keywords Design optimization Optimal control Smart building Energy efficiency

Corresponding Author(s): Shengwei WANG

Online First Date: 07 April 2017 Issue Date: 19 April 2017

Cite this article:

Shengwei WANG,Wenjie GANG. Design and control optimization of energy systems of smart buildings today and in the near future[J]. Front. Eng, 2017, 4(1): 58-66.

URL:

https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2017005
https://academic.hep.com.cn/fem/EN/Y2017/V4/I1/58

Fig.1 Statistic data on the electricity consumption of office buildings and their space air conditioning from 2003 to 2013 in Hong Kong

Fig.2 Primary steps for design optimization and optimal control

Fig.3 The International Commerce Centre (ICC) (http://www.shkp-icc.com/website/showGeneralContent.do#)

Fig.4 Layout of the central cooling system for ICC

Fig.5 Layout of the secondary chilled water loop systems in Zones 3 and 4

Fig.6 Optimized control diagram for the chillers

Fig.7 The indoor air CO₂ concentration of different zones at 15/F based on the DCV method

Fig.8 Annual energy consumption in the past four years

Tab.1 Comparison of ICC annual energy consumption

1	BuckmanA H, MayfieldM, BeckB M (2014). What is a smart building.Smart and Sustainable Built Environment, 3(2): 92–109 https://doi.org/10.1108/SASBE-01-2014-0003
2	ClaridgeD, HaberlJ, LiuM, et al. (1994). Can you achieve 150% of predicted retrofit savings? Is it time for recommissioning? Proceedings of the 1994 ACEEE Summer Study DOE. Buildings energy data book.
3	Department of Energy’s (DOE) (2017). EnergyPlus.
4	Electrical and Mechanical Services Department (EMSD) (2015). Hong Kong Energy End-use Data 2015.
5	GangW, AugenbroeG, WangS, FanC, XiaoF (2016). An uncertainty-based design optimization method for district cooling systems.Energy, 102: 516–527 https://doi.org/10.1016/j.energy.2016.02.107
6	GangW, WangS, YanC, XiaoF (2015). Robust optimal design of building cooling systems concerning uncertainties using mini-max regret theory.Science and Technology for the Built Environment, 21(6): 789–799 https://doi.org/10.1080/23744731.2015.1056657
7	GaoD, WangS, SunY (2011). A fault-tolerant and energy efficient control strategy for primary–secondary chilled water systems in buildings.Energy and Building, 43(12): 3646–3656 https://doi.org/10.1016/j.enbuild.2011.09.037
8	HaberlJ, ReddyA, ClaridgeD, et al. (1994). Reducing building energy costs using optimized operation strategies for constant volume air handling systems. Proceedings of the Ninth Symposium on Improving Building Systems in Hot and Humid Climates, Arlington, TX, May 19 ‒ 20, 1994
10	MaZ J, WangS W, PauW K (2008). Alternative designs of the complex secondary chilled water system for a super high-rise building.ASHRAE Journal, 50(5): 42–52
11	MaZ, WangS (2009). An optimal control strategy for complex building central chilled water systems for practical and real-time applications.Building and Environment, 44(6): 1188–1198 https://doi.org/10.1016/j.buildenv.2008.08.011
12	MaZ, WangS (2009). Energy efficient control of variable speed pumps in complex building central air-conditioning systems.Energy and Building, 41(2): 197–205 https://doi.org/10.1016/j.enbuild.2008.09.002
13	MaZ, WangS, XiaoF (2009). Online performance evaluation of alternative control strategies for building cooling water systems prior to in situ implementation.Applied Energy, 86(5): 712–721 https://doi.org/10.1016/j.apenergy.2008.05.017
14	OmerA M (2008). Energy, environment and sustainable development.Renewable & Sustainable Energy Reviews, 12(9): 2265–2300 https://doi.org/10.1016/j.rser.2007.05.001
15	SunY, WangS, HuangG (2009). Chiller sequencing control with enhanced robustness for energy efficient operation.Energy and Building, 41(11): 1246–1255 https://doi.org/10.1016/j.enbuild.2009.07.023
16	SunY, WangS, HuangG (2010). Model-based optimal start control strategy for multi-chiller plants in commercial buildings.Building Services Engineering Research and Technology, 31(2): 113–129 https://doi.org/10.1177/0143624409359979
17	SunZ, WangS, MaZ (2011). In-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation strategy in a multi-zone office building.Building and Environment, 46(1): 124–133 https://doi.org/10.1016/j.buildenv.2010.07.008
19	TRNSYS-Transient System Simulation Tool (2017).
20	WangS, GaoD, SunY, XiaoF (2013). An online adaptive optimal control strategy for complex building chilled water systems involving intermediate heat exchangers.Applied Thermal Engineering, 50(1): 614–628 https://doi.org/10.1016/j.applthermaleng.2012.06.010
21	WangS, MaZ (2010). Control strategies for variable speed pumps in super high-rise building.ASHRAE Journal, 52(7): 36–43

[1]	Patrick X.W. ZOU, Morshed ALAM, Van Manh PHUNG, Dipika WAGLE, Rodney STEWART, Edoardo BERTONE, Oz SAHIN, Chris BUNTINE. Achieving energy efficiency in government buildings through mandatory policy and program enforcement[J]. Front. Eng, 2017, 4(1): 92-103.
[2]	Yin-biao Chen,Yi Zhang,Wen Ling. Practice on Ultra-low Emission and Energy Efficient Technologies in Coal-fired Power Plants[J]. Front. Eng, 2016, 3(4): 377-383.
[3]	Xing Wei,Han-ding Guo. A Comprehensive Evaluation of Policy Effectiveness for Energy Efficiency in Existing Buildings[J]. Front. Eng, 2014, 1(4): 341-347.

Viewed

Full text

Abstract

Cited

Shared

Discussed