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

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

References

[1] BuckmanA H, MayfieldM, BeckB M (2014). What is a smart building.Smart and Sustainable Built Environment, 3(2): 92–109

[2] ClaridgeD, HaberlJ, LiuM, (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. http://buildingsdatabook.eren.doe.gov/

[3] Department of Energy’s (DOE) (2017). EnergyPlus. https://energyplus.net/

[4] Electrical and Mechanical Services Department (EMSD) (2015). Hong Kong Energy End-use Data 2015. http://www.emsd.gov.hk/filemanager/en/content_762/HKEEUD2015.pdf

[5] GangW, AugenbroeG, WangS, FanC, XiaoF (2016). An uncertainty-based design optimization method for district cooling systems.Energy, 102: 516–527

[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

[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

[8] HaberlJ, ReddyA, ClaridgeD, (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

[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

[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

[14] OmerA M (2008). Energy, environment and sustainable development.Renewable & Sustainable Energy Reviews, 12(9): 2265–2300

[15] SunY, WangS, HuangG (2009). Chiller sequencing control with enhanced robustness for energy efficient operation.Energy and Building, 41(11): 1246–1255

[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

[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

[19] TRNSYS-Transient System Simulation Tool (2017). http://www.trnsys.com/

[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

[21] WangS, MaZ (2010). Control strategies for variable speed pumps in super high-rise building.ASHRAE Journal, 52(7): 36–43

RIGHTS & PERMISSIONS

2017 The Author(s) 2017. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)