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Building Energy and Automation Research Laboratory

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Researchers:

Prof. Shengwei Wang (Chair Professor and Director)

Prof. Linda Fu Xiao (Professor and Deputy Director)

Dr. Hangxin Li (Research Assistant Professor)

Dr. Kui Shan (Research Assistant Professor)

Research staff:

Chaoqun Zhuang (post-doc fellow), Huilong Wang (Post-doc fellow/HKPhD fellowship awardee), Wenzhuo Li (Post-doc fellow/HKPhD fellowship awardee), Chong Zhang (post-doc fellow/Hong Kong Scholar awardee), Binglong Han (research assistant)

PhD students:

Hong Tang, Bing Su, Ao Li, Yao Lin, Shaobo Sun, Zhijie Chen, Jianing Luo, Zeming Zhao, Xinyue Li, Xiaoyu Jin, Wenxuan Zhao (HKPhD fellowship awardee), Tianhang Zhang (HKPhD fellowship awardee)

Overview of the Research Laboratory

The Building Energy and Automation Research Laboratory (BEAR Lab) is researching and developing innovative methodologies and technologies of building system design optimization, control optimization, diagnosis and commissioning for smart, energy-efficient and grid-responsive buildings. 

The BEAR Lab establishes a strong and energized team with multidisciplinary backgrounds and expertise in air-conditioning, energy systems, building automation and data science. The Lab adopts the multidisciplinary approach, which integrates information and IoT technologies, big-data analytics, machine learning (AI), uncertainty analysis and system simulation, to address the existing and emerging challenges in developing smart, energy-efficient and grid-responsive buildings. The main areas of interests/expertise of the Lab include: nonresidential buildings, energy-flexible and grid-responsive buildings, zero/low energy buildings, smart energy systems and micro-grids, cleanroom air-conditioning systems, district cooling systems, data center cooling systems, distributed built environment control devices, etc.

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Outline of main research focuses, methodologies and areas of interests/expertise

The BEAR Lab is very successful in securing both research grants and industrial funds, and transferring research results to technology development and applications. Over 50 research grants have been secured from different sources, including one CRF (Collaborative Research Fund) of RGC (Research Grant Council), one international key collaboration grant of NSFC (National Science Foundation of China), one major research grant from National Key R&D Programs of MOST (Ministry of Science and Technology of China), over 20 GRF (General Research Fund) grants of RGC, one Overseas Youth Talent Grant of NSFC and five Hong Kong PhD Fellowship grants. The Lab has also received over HKD 20 million from the industry for applied energy research and applications, and has conducted a large number of impactful energy optimization projects for new buildings and existing buildings in Hong Kong, such as International Commerce Centre (ICC), hotels, airport buildings, hospitals, industrial buildings, MTR underground station as well as buildings in PolyU campus, with energy savings from 15% to 40% and maximum annual energy saving of over 10M kWh per individual building. The BEAR Lab has been making substantial contributions to the smart and sustainable development and decarbonization in the building sector.

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Key members of the teams Members and some alumnus of the team (2018)

The team leader, Prof. Wang, was among the top 150 highly cited scholars worldwide in “Energy Science and Engineering” as released by Elsevier in 2016 and ranked no. 22 in “Building and Construction” in the world according to a Stanford study based on Scopus in 2020. The co-leader, Prof. Xiao, is the most active and influential scientist in building big-data analytics in the field. The team is very proud that the PhD graduates trained in the Lab are highly competitive in global search exercises for faculty members, and secured faculty positions in top/reputable good universities in the Mainland, Hong Kong, Australia, United Kingdom and United States. Most of the graduates are very successful in their career development, while being appointed/promoted to senior faculty positions or senior management positions in large/international firms.

 

Supporting Facilities and Software Packages

The existing facilities and software packages developed and installed in the affiliated Intelligent Building (IB) Laboratory include: building automation and control systems, HVAC and BMS dynamic simulation packages, optimal and robust control strategies for building systems, diagnosis and commissioning packages/strategies for building and energy systems, absorption thermal storage test rig, a frequency response control test rig, IoT and smart sensing network test rigs, and building automation system integration and management platform - IBmanager. These are the outputs of previous research as well as the excellent supporting facilities and tools for the continuous research and application development.

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Photos of Intelligent Building (IB) Laboratory

 

Representative Research Grants
  • Development of next-generation key technologies for smart buildings (RGC/CRF, 6.14M, 2020)
  • Development of Smart Energy Management Technologies for Buildings and Districts in High-Density Cities (SEM4Cities) (MOST, ~5.0M, 2020)
  • Development of a disturbance compensation-based frequency regulation control strategy engaging variable-speed HVAC devices for smart grid instantaneous power balancing with reduced impact on buildings (RGC/GRF, 874K, 2020)
  • Development of a Big Data-Driven Methodology to Characterize and Model the Energy Dynamics of Large Buildings with Complex Energy Systems (RGC/GRF, 534K, 2019)
  • Adaptive Full-range Decoupled Ventilation Strategy for Cleanrooms/Spaces Requiring Strict Temperature and Humidity Controls in Subtropical Regions: System Robust Optimal Design and Control (RGC/GRF, 748K, 2019)
  • Research and Application of Internally-cooled Membrane-Based Heat and Moisture Control System. (Guangzhou Science Technology and Innovation Commission, Co-PI, CNY2.0M, 2019)
  • Probabilistic Optimal and Adaptive Design and Test & Commissioning of District Cooling Systems Concerning Uncertainties and Reliability (RGC/GRF, 632K, 2018)
  • Optimized Design and Optimal Control of Smart Buildings of Enhanced Grid Friendliness and Responsiveness (Strategic Focus Area Scheme of RISUD, The Hong Kong polytechnic university, 2.5M, 2017)
  • Robust Optimal Design of Energy Systems for Grid-connected and Stand-alone Zero Energy Buildings (RGC/GRF, 483K, 2016)
  • Development of A Fast Building Power Demand Response Control Strategy for Smart Grids (RGC/GRF, 695K, 2015)
  • Energy Performance Assessment and Optimization on Existing Campus Buildings (University Sustainable Development Grant, 4.7M, 2015)
  • Energy Performance Assessment and Optimization on Phase 5 Building (University Sustainable Development Grant, 1.2 M, 2014)
  • Mining Massive Data Sets in Building Automation System for Improving Building Operational Performance. (RGC/GRF, 875K, 2014)
  • Dynamic Characterization and Modelling of Liquid Desiccant Dehumidification and Regeneration Processes. (NSFC, RMB250K, 2014)
  • Dynamic Characterization and Robust Control of Air Handling Processes with Decoupled Cooling and Dehumidification. (RGC/ECS, 550K, 2013)
  • Design and Control Optimizations of Net-Zero Energy Buildings Integrated with Micro-Grid (RGC/GRF, 646K, 2013)
  • Development of an Interactive Building Energy Demand Management Strategy for Smart Grid (RGC/GRF, 700K, 2012)
  • Study of Dynamic Characteristics and Energy Performance of Liquid Desiccant System Driven by Heat Pump for Optimization and Control. (RGC/GRF, $681K, 2012)
  • Development of an Automated Fault Diagnostic Strategy and Its Customization Tool for Chiller Systems in Buildings (RGC/GRF fundable, 2010, 105K)
  • Air-conditioning System Energy Saving Technologies based on Fault Detection and Diagnosis, (overseas collaborative research grant (Overseas Youth Talent Grant, National Science Foundation of China, Collaborator: Shanghai Jiao-tong University, 2011)
  • Study on the Feasibility and Cost-Effectiveness of a Hybrid Desiccant and Evaporative cooling System Applied in Hong Kong. (ECF, 204K, 2010)
  • Study on the Thermodynamic Characteristics and Optimal Control of Buildings with Energy Performance Enhanced by Integrating Phase Change Materials (PCMs) (RGC/GRF, 748K, 2009)
  • Modeling and Control of a Novel Independent Fresh Air Conditioning System with Membrane-Based Enthalpy Recovery. (Edward Sai Kim Hotung Fund, 548K, 2008)
  • Development and Site Validation of Online Optimal Control Strategies for Building Central Air-Conditioning Systems (RGC/GERG, 347K, 2008)
  • Development of A Novel Data Fusion Technique for Improving Robustness of Automatic Control and Diagnosis in Large Cooling Plants (RGC/CERG, 306K, 2008)
  • Development of A Sensor-based Adaptive Demand-Controlled Ventilation Strategy for Multi-zone VAV Air-conditioning Systems (RGC/CERG, 477K, 2007)
  • Development of A Model-based Building Energy Performance Diagnostic Tool (RGC/CERG, 371K, 2006)
  • Development of A Robust Fault Diagnostic Tool and Platform for Centralized Monitoring and Management of Building Chiller Plants (RGC/CERG,403K, 2005)
  • Development of a Middleware-Based Open Management Platform for Performance Monitoring and Diagnosis of Building Ventilation and Air-Conditioning Systems (RGC/CERG, 666K, 2004)
  • Robust and Optimal DDC Control of Outdoor Air Ventilation in Buildings (RGC/CERG, 470K, 2001)
  • Fault Validation and Fault Tolerant Control of Building Automation Systems (RGC/CERG, 710K, 2000)
  • Sensor fault diagnosis and validation of Building Management Systems (RGC/CERG, 405K, 1999

 

Selected Publications
(Books)
  • Wang SW, Intelligent Buildings and Building Automation, Spon Press (Taylor & Francis), London and New York, November 2009.
  • Wang SW (translated by Wang S.W. and Xu Z.Y.), Intelligent Buildings and Building Automation (Chinese edition), China Architecture and Building Press, Beijing, January, 2010.
  • Chen YM and Wang SW, Novel Methods for Transient Heat Transfer Analysis of Building Constructure, Science Press, Beijing, 2004.
  • Chen YM, Wang SW and Zhang L, System Identification and Its Application in Building Heat and Mass Transfer Processes, China Architecture and Building Press, Beijing, 2004.

 

(SCI Journal papers since 2010) 
  1. Tang H and SW Wang, “Energy flexibility quantification of grid-responsive buildings: Energy flexibility index and assessment of their effectiveness for applications”, Energy, V221, 119756, 2021.
  2. Li WZ, SW Wang and C Koo, “A real-time optimal control strategy for multi-zone VAV air-conditioning systems adopting a multi-agent based distributed optimization method”, Applied Energy, V287, 116605, 2021.
  3. Zhuang CQ, K Shan and SW Wang, “Coordinated demand-controlled ventilation strategy for energy-efficient operation in multi-zone cleanroom air-conditioning systems”, Building and Environment, V191, 107588, 2021.
  4. Wang HL and SW Wang, “A disturbance compensation enhanced control strategy of HVAC systems for improved building indoor environment control when providing power grid frequency regulation”, Renewable Energy, V169, pp. 1130-1342, 2021.
  5. Hu MM, F Xiao and SW Wang, “Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids”, Renewable and Sustainable Energy Reviews, V135, 110248, 2021.
  6. Marco Savino Piscitelli, Silvio Brandi, Alfonso Capozzoli and Xiao F, “A data analytics-based tool for the detection and diagnosis of anomalous daily energy patterns in buildings”, Building Simulation, Vol.14, pp. 131-147, 2021.
  7. Tang H, S Wang, H Li, “Flexibility Categorization, Sources, Capabilities and Technologies for Energy-Flexible and Grid-Responsive Buildings: State-of-The-Art and Future Perspective”, Energy, V219, 119598, 2020.
  8. Zhuang CQ, SW Wang and K Shan, “A risk-based robust optimal chiller sequencing control strategy for energy-efficient operation considering measurement uncertainties”, Applied Energy, V280, 115983, 2020.
  9. Zhuang CQ and SW Wang, “Uncertainty-based robust optimal design of cleanroom air-conditioning systems considering life-cycle performance”, Indoor and Built Environment, V29 (9), pp. 1214-1226, 2020.
  10. Wang HL and SW Wang, “The impact of providing frequency regulation service to power grids on indoor environment control and dedicated test signals for buildings”, Building and Environment, V183, 107217, 2020.
  11. Li WZ and SW Wang, “A multi-agent based distributed approach for optimal control of multi-zone ventilation systems considering indoor air quality and energy use”, Applied Energy, V275, 115371, 2020.
  12. Tang R, SW Wang and SB Sun, “Impacts of technology-guided occupant behavior on air-conditioning system control and building energy use”, Building Simulation, V14, pp. 209-217, 2020.
  13. L Xu, H Tang, SW Wang, “Adaptive optimal monthly peak building demand limiting strategy based on exploration-exploitation tradeoff”, Automation in Construction, V119, 103349, 2020.
  14. Su B and Wang SW, “An agent-based distributed real-time optimal control strategy for building HVAC systems for applications in the context of future IoT-based smart sensor networks”, Applied Energy V274, 115322, 2020.
  15. Li WZ, Koo C, Hong T, Oh J, Cha SH and Wang SW, “A novel operation approach for the energy efficiency improvement of the HVAC system in office spaces through real-time big data analytics”, Renewable and Sustainable Energy Reviews, V127, 109885, 2020.
  16. Li HX and Wang SW, “A systematic and probabilistic approach for optimal design and on-site adaptive balancing of building central cooling systems concerning uncertainties”, Science and Technology for the Built Environment, 1-13, 2020.
  17. Li HX and Wang SW, “Coordinated robust optimal design of building envelope and energy systems for zero/low energy buildings considering uncertainties”, Applied Energy, V265, 114779, 2020.
  18. Li HX and Wang SW, “Model-based multi-objective predictive scheduling and real-time optimal control of energy systems in zero/low energy buildings using a game theory approach” Automation in Construction”, V113, 103139, 2020.
  19. Wang HL, Wang SW and Shan K, “Experimental study on the dynamics, quality and impacts of using variable-speed pumps in buildings for frequency regulation of smart power grids”, Energy, 117406, 2020.
  20. Zhuang CQ and Wang SW, “Risk-based online robust optimal control of air-conditioning systems for buildings requiring strict humidity control considering measurement uncertainties”, Applied Energy, V261, 114451, 2020.
  21. Zhuang CQ and Wang SW, “An adaptive full-range decoupled ventilation strategy for buildings with spaces requiring strict humidity control and its applications in different climatic conditions”, Sustainable Cities and Society, V52, p.101838, 2020.
  22. Zhang Z, Zhang C and Xiao F, “Experimental and theoretical analysis of functional controllability for multi-condenser heat pumps”, Applied Thermal Engineering, V171, 115093, 2020.
  23. Hu M and Xiao F, “Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior”, Energy, 2020.
  24. Fan C, Sun Y, Xiao F, Ma J, Lee D, Wang JY and Tseng YC, “Statistical investigations of transfer learning-based methodology for short-term building energy predictions”, Applied Energy, V262, 114499, 2020.
  25. Xiao F, “Editorial: Building performance modeling and simulation”, Science and Technology for the Built Environment, V26(1), pp. 1-2, 2020.
  26. Hu M, Xiao F and Cheung H, “Identification of simplified energy performance models of variable-speed air conditioners using likelihood ratio test method”, Science and Technology for the Built Environment, V26(1), pp. 75-88, 2020.
  27. Fan C, Xiao F, Song M, and Wang J, “A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management”, Applied Energy, V 251, 2019.
  28. Lu T, Yang X, Xiao F and Wen T, “A mass conservative Lattice Boltzmann model for two-phase flows with moving contact lines at high density ratio”, Communications in Computational Physics, V26(4), pp. 1098-1117, 2019.
  29. Hu M, Xiao F, Jørgensen JB and Li R, “Price-responsive model predictive control of floor heating systems for demand response using building thermal mass”, Applied Thermal Engineering, V153, pp. 316-329, 2019.
  30. Kumar R, Patil D, Xiao F and Lu T, “Performance intensification of regeneration process for non-corrosive plastic plate vertical falling film tower”, Applied Thermal Engineering, V162, 2019.
  31. Fan C, Xiao F, Yan C, Liu C, Li Z and Wang J, “A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning”, Applied Energy, V235, pp. 1551-1560, 2019.
  32. Cui B, Fan C, Munk J, Mao N, Xiao F, Dong J and Kuruganti T, “A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses”, Applied Energy, V236, pp. 101-116, 2019.
  33. Li HX and Wang SW, “Coordinated optimal design of zero/low energy buildings and their energy systems based on multi-stage design optimization”, Energy V189, 116202, 2019.
  34. Li HX, Wang SW and Tang R, “Robust optimal design of zero/low energy buildings considering uncertainties and the impacts of objective functions”, Applied Energy, V254, p113683, 2019.
  35. Xu L, SW Wang and F Xiao, “A proactive-adaptive monthly peak demand limiting strategy for buildings with small-scale thermal storages considering load uncertainty”, Science and Technology for the Built Environment, Science and Technology for the Built Environment, V25, pp. 1456–1466, 2019.
  36. Zhuang CQ, SW Wang, K Shan, “Probabilistic optimal design of cleanroom air-conditioning systems facilitating optimal ventilation control under uncertainties”, Applied Energy, V253, 113576, 2019.
  37. Xu L, SW Wang, F Xiao, “An adaptive optimal monthly peak building demand limiting strategy considering load uncertainty”, Applied Energy, V 253, 113582, 2019.
  38. Tang R, SW Wang, H Li, “Game theory based interactive demand side management responding to dynamic pricing in price-based demand response of smart grids”, Applied Energy, V250, pp.118-130, 2019.
  39. Wang HL, SW Wang, R Tang, “Development of grid-responsive buildings: Opportunities, challenges, capabilities and applications of HVAC systems in non-residential buildings in providing ancillary services by fast demand responses to smart grids”, Applied Energy, V250, pp.697-712, 2019.
  40. Cheung H, SW Wang, “Reliability and availability assessment and enhancement of water-cooled multi-chiller cooling systems for data centers”, Reliability Engineering & System Safety, p.106573, 2019.
  41. Cheung H, SW Wang, “Optimal design of data center cooling systems concerning multi-chiller system configuration and component selection for energy-efficient operation and maximized free-cooling”, Renewable Energy, V143, pp.1717-1731, 2019.
  42. Hu MM, F Xiao, JB Jørgensen, SW Wang, “Frequency control of air conditioners in response to real-time dynamic electricity prices in smart grids”, Applied Energy, V242, 92-106, 2019.
  43. Tang R, SW Wang, “Model predictive control for thermal energy storage and thermal comfort optimization of building demand response in smart grids”, Applied Energy, V242, 873-882, 2019
  44. Tang R, HX Li, SW Wang, “A game theory-based decentralized control strategy for power demand management of building cluster using thermal mass and energy storage”, Applied Energy, V242, 809-820, 2019.
  45. Xu L, Wang SW and Tang R, “Probabilistic load forecasting for buildings considering weather forecasting uncertainty and uncertain peak load”, Applied Energy, V237, pp.180-195, 2019.
  46. Zhuang CQ, Wang SW and Shan K, “Adaptive full-range decoupled ventilation strategy and air-conditioning systems for cleanrooms and buildings requiring strict humidity control and their performance evaluation”, Energy, V168, pp.883-896, 2019.
  47. Kang J, Wang SW and Yan CC, “A new distributed energy system configuration for cooling dominated districts and the performance assessment based on real site measurements”, Renewable Energy, V131, pp. 390-403, 2019,
  48. Tang R, Wang SW and Shan K, “Optimal and near-optimal indoor temperature and humidity controls for direct load control and proactive building demand response towards smart grids”, Automation in Construction, V96, pp. 250-261, 2018.
  49. Cheung H, Wang SW, Zhuang CQ and Gu JF, “A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation”, Applied Energy, V222, pp. 329-342, 2018.
  50. Tang R, Wang SW Shan K and Cheung H, “Optimal control strategy of central air-conditioning systems of buildings at morning start period for enhanced energy efficiency and peak demand limiting”, Energy, V151, pp. 771-781, 2018.
  51. Kang J and Wang SW, “Robust optimal design of distributed energy systems based on life-cycle performance analysis using a probabilistic approach considering uncertainties of design inputs and equipment degradations”, Applied Energy, V231, pp. 615-627, 2018.
  52. Li HX, Wang SW and Cheung H, “Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions”, Applied Energy, V228, pp. 1280-1291, 2018.
  53. Cheung H and Wang SW, “Impact of dynamics on the accuracies of different experimental data-processing methods for steady-state heat transfer rate measurement”, Journal of Thermal Science and Engineering Applications, V10 (2), Article Number: 021008, 2018.
  54. Tang R, Wang SW and Yan CC, “A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids”, Automation in Construction, V87, pp.74-83, 2018.
  55. Cheung H and Wang SW, “A comparison of the effect of empirical and physical modeling approaches to extrapolation capability of compressor models by uncertainty analysis: A case study with common semi-empirical compressor mass flow rate models”, International Journal of Refrigeration, V86, pp. 331-343, 2018.
  56. Shan K, Wang SW and Tang R, “Direct chiller power limiting for peak demand limiting control in buildings Methodology and on-site validation”, Automation in Construction, V85, pp.333-343, 2018.
  57. Lu T and Xiao F, “Lattice Boltzmann Simulation of Falling Film Flow under Low Reynolds Number”, Heat Transfer Engineering, V39(17-18), pp. 1531-1542, 2018.
  58. Hu M and Xiao F, “Price-responsive model-based optimal demand response control of inverter air conditioners using genetic algorithm”, Applied Energy, V219, pp. 151-164, 2018.
  59. Fan C, Xiao F, Zhao Y and Wang J, “Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data”, Applied Energy, V211, pp. 1123-1135, 2018.
  60. Fan C, Xiao F, Li Z and Wang J, “Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review. Energy and Buildings, V159, pp. 296-308, 2018.
  61. Fan C and Xiao F, “Mining big building operational data for improving building energy efficiency: A case study”, Building Services Engineering Research and Technology, V39(1), pp. 117-128, 2018.
  62. Fan C, Sun Y, Shan K, Xiao F and Wang J, “Discovering gradual patterns in building operations for improving building energy efficiency”, Applied Energy, V224, pp. 116-123, 2018.
  63. Kang J, Wang SW and Gang WJ, “Performance of distributed energy systems in buildings in cooling dominated regions and the impacts of energy policies”, Applied Thermal Engineering, V127, pp. 281-291, 2017.
  64. Yan CC, Gang WJ, Niu, XF, Peng XJ and Wang SW, “Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems”, Applied Energy, V205, pp. 635-643, 2017.
  65. Wang SW and Tang R, “Supply-based feedback control strategy of air-conditioning systems for direct load control of buildings responding to urgent requests of smart grids’, Applied Energy, V201, pp. 419-432, 2017.
  66. Cui BR, Xiao F and Wang SW, “Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings”, Applied Energy, V201, pp. 382-396, 2017.
  67. Shan K and Wang SW, “Energy efficient design and control of cleanroom environment control systems in subtropical regions–A comparative analysis and on-site validation”, Applied Energy, V204, pp. 582-595, 2017.
  68. Cui BR, Gao DC, Xiao F and Wang SW, “Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings”, Applied Energy, V201, pp. 382-396, 2017.
  69. Li HX and Wang SW, “Probabilistic optimal design concerning uncertainties and on-site adaptive commissioning of air-conditioning water pump systems in buildings, Applied Energy, V202, pp. 53-65, 2017.
  70. Gang WJ, Wang SW and Xiao F, “District cooling systems and individual cooling systems: Comparative analysis and impacts of key factors”, Science and Technology for the Built Environment”, V23(2), pp. 241-250, 2017.
  71. Lu YH, Wang SW, Yan CC and Huang ZJ, “Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties”, Applied Energy, V187, pp. 62-71, 2017.
  72. Gang WJ, Wang SW and Xiao F, “District cooling systems and individual cooling systems: Comparative analysis and impacts of key factors”, Science and Technology for the Built Environment, V23 (2), PP.241-250, 2017.
  73. Zhao Y, Wen J, Xiao F, Yang X and Wang SW, “Diagnostic Bayesian networks for diagnosing air handling units faults–part I: Faults in dampers, fans, filters and sensors”, Applied Thermal Engineering, V111, 1272-1286, 2017.
  74. Cheng Q, Wang SW and Yan CC, “Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability”, Energy V118, 489-501, 2017.
  75. Yan CC, Wang SW, Fan C and Xiao F, “Retrofitting building fire service water tanks as chilled water storage for power demand limiting”, Building Services Engineering Research and Technology, V38 (1), 47-63, 2017.
  76. Cheng Q, Wang SW, Yan CC and Xiao F, “Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings”, Applied Energy, V185, 1613-1624, 2017.
  77. Cheng Q, Wang SW and Yan CC, “Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost”, Energy and Buildings, V126, pp. 159-169, 2016.
  78. Yan CC, Wang SW, Fan C and Xiao F. “Retrofitting building fire service water tanks as chilled water storage for power demand limiting”, Building Services Engineering Research and Technology, 2016.
  79. Wang SW, “Making buildings smarter, grid-friendly, and responsive to smart grids”, Science and Technology for the Built Environment, V22:6, pp. 629-632, 2016.
  80. Tang R, Wang SW, Gao DC and Shan K, “A power limiting control strategy based on adaptive utility function for fast demand response of buildings in smart grids’, Science and Technology for the Built Environment V22(6), pp. 810-819, 2016.
  81. Shan K, Wang SW, Yan CC and Xiao F. “Building demand response and control methods for smart grids: A review”, Science and Technology for the Built Environment, V22(6), pp. 692-704, 2016.
  82. Gang WJ, Wang SW, Augenbroe G and Xiao F, Robust optimal design of district cooling systems and the impacts of uncertainty and reliability, Energy and Buildings, V122, pp. 11-22, 2016.
  83. Gao DC, Wang SW and Shan K, In-situ implementation and evaluation of an online robust pump speed control strategy for avoiding low Delta-T syndrome in complex chilled water systems of high-rise buildings”, Applied Energy, V171, pp.541-554, 2016.
  84. Shan K, Wang SW, Gao DC and Xiao F, “Development and validation of an effective and robust chiller sequence control strategy using data-driven models”, V65, pp. 78–85, 2016.
  85. Gang WJ, Augenbroe G, Wang SW, Fan F and Xiao F, “An uncertainty-based design optimization method for district cooling systems”, Energy, V102, pp. 516–527, 2016.
  86. Gang WJ, Wang SW, Xiao F and Gao, DC, “District cooling systems: Technology integration, system optimization, challenges and opportunities for applications”, Renewable & Sustainable Energy Reviews, V53, pp. 253-264, 2016.
  87. Yan CC, Shi WX, Li XT and Wang SW, “A seasonal cold storage system based on separate type heat pipe for sustainable building cooling”, Renewable Energy, V85, pp. 880-889, 2016.
  88. Gang WJ, Wang SW, Xia F. and Cao DC, “Robust optimal design of building cooling systems considering cooling load uncertainty and equipment reliability”, Applied Energy, V159, pp. 265-275, 2015.
  89. Zhao Y, Wen J, and Wang SW, “Diagnostic Bayesian networks for diagnosing air handling units faults - Part II: Faults in coils and sensors”, Applied Thermal Engineering, V90, pp. 145-157, 2016.
  90. Lu YH, Wang SW and Shan K, “Design optimization and optimal control of grid-connected and standalone nearly/net zero energy buildings”, Applied Energy, V155, pp. 463-477, 2015.
  91. Gang WJ, Wang SW, Yan CC and Xiao F, “Robust optimal design of building cooling systems concerning uncertainties using mini-max regret theory”, Science and Technology for The Built Environment, V21(6), pp. 789-799, 2015.
  92. Shan K, Wang SW, Gao DC and Lee SWS, “In-situ validation of a fault tolerant control strategy for VAV systems”, Applied Thermal Engineering, V87, pp. 362-370, 2015.
  93. Shen LM, Chen HX, Xiao F and Wang SW, “The practical performance forecast and analysis of thermoelectric module from macro to micro”, Energy Conversion and Management, V100, pp. 23-29, 2015.
  94. Cui BR, Gao DC, Wang SW and Xue X, “Effectiveness and life-cycle cost-benefit analysis of active cold storages for building demand management for smart grid applications”, Applied Energy, V147, pp. 523-535, 2015.
  95. Gang WJ, Wang SW, Shan K and Gao DC, “Impacts of Cooling Load Calculation Uncertainties on the Design Optimization of Building Cooling Systems”, Energy and Buildings, V94, pp.1–9, 2015.
  96. Lu YH, Wang SW, Sun YJ and Yan CC, “Optimal Scheduling of Buildings with Energy Generation and Thermal Energy Storage under Dynamic Electricity Pricing Using Mixed-integer Nonlinear Programming”, Applied Energy, V147, pp. 49-58, 2015.
  97. Gao DC, Wang SW and Shan K, “A System-level Fault Detection and Diagnosis Method for Low Delta-T Syndrome in the Complex HVAC Systems, Applied Energy, V164, pp. 1028-1038, 2015. (SCI Journal)
  98. Yan CC, Wang SW, Xiao F and Gao DC, “A Multi-level Energy Performance Diagnosis Method for Energy Information-Poor Buildings”, Energy, V83, pp.189-203, 2015.
  99. Cui BB, Wang SW, Yan CC and Xue X, “Evaluation of a fast power demand response strategy using active and passive building cold storages for smart grid applications”, Energy Conversion and Management, V102, pp.227-238, 2015.
  100. Yan CC, Xue X, Wang SW and Cui BR, “A novel air-conditioning system for proactive power demand response to smart grid”, Energy Conversion and Management, V102, pp. 239-246, 2015.
  101. Xue X, Wang SW, Yan CC and Cui BR, “A fast chiller power demand response control strategy for buildings connected to smart grid”, Applied Energy, V137, pp. 77-87, 2015.
  102. Yan CC, Wang SW, Shan K and Lu YH, “A simplified analytical model to evaluate the impact of radiant heat on building cooling load”, Applied Thermal Engineering, V77, pp. 30-41, 2015.
  103. Lu YH, Wang SW, Zhao Y and Yan CC, “Renewable energy system optimization of low/zero energy buildings using single-objective and multi-objective optimization methods”, Energy and Buildings, V89, pp.61-75, 2015.
  104. Gang WJ, Wang SW, Gao DC and Xiao F, “Performance assessment of district cooling systems for a new development district at planning stage”, Applied Energy, V140, pp. 33-43, 2015.
  105. Zhao Y, Lu YH, Yan CC and Wang SW, “MPC-based optimal scheduling of grid-connected low energy buildings with thermal energy storages”, Energy and Buildings, V86, pp.415-426, 2015.
  106. Yan CC, Wang SW, Ma ZJ and Shi WX, “A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis”, Renewable Energy, V74, pp. 271-278, 2015.
  107. Gang WJ, Wang JB, and Wang SW, “Performance analysis of hybrid ground source heat pump systems based on ANN predictive control”, Applied Energy, V136, pp. 1138-1144, 2014.
  108. Zhao Y, Xiao F, Wen J, Lu YH and Wang SW, “A robust pattern recognition-based fault detection and diagnosis (FDD) method for chillers”, HVAC&R Research, V20 (7), pp. 798-809, 2014.
  109. Fan C, Xiao F and Wang SW, “Development of prediction models for next-day building energy consumption and peak power demand using data Mining techniques”, Applied Energy, V127, pp.1-10, 2014.
  110. Cui BR, Wang SW and Sun YJ, “Life-cycle cost benefit analysis and optimal design of small scale active storage system for building demand limiting”, Energy, V73, pp.787-800, 2014.
  111. Wang SW, Xue X and Yan CC, “Building power demand response methods toward smart grid”, HVAC&R Research, V20(6), pp.665-687, 2014.
  112. Xiao F, Zhao Y, Wen J and Wang SW, “Bayesian network based FDD strategy for variable air volume terminals”, Automation in Construction, V41, pp. 106-118, 2014, 2014.
  113. Shen LM Chen HX, Xiao F, Yang YX and Wang SW “The step-change cooling performance of miniature thermoelectric module for pulse laser”, Energy Conversion and Management, V80, pp. 39-45, 2014.
  114. Xue X, Wang SW, Sun YJ and Xiao F, “An interactive building power demand management strategy for facilitating smart grid optimization”, Applied Energy, V116, pp. 297-310, 2014.
  115. Xu X.H, Yu JH, Wang SW and Wang JB, “Research and application of active hollow core slabs in building systems for utilizing low energy sources”, Applied Energy, V116, pp.424-435, 2014.
  116. Zhao Y, Wang SW and Xiao F, “Pattern recognition-based chillers fault detection method using support vector data description (SVDD)”, Applied Energy, V112, pp.1041-1048, 2013.
  117. Sun YJ, Huang GS, Li ZW and Wang SW, “Multiplexed optimization for complex air conditioning systems”, Building and Environment, V65, pp. 99-108, 2013.
  118. Shan K, Wang SW, Xiao F and Sun YJ, “Sensitivity and Uncertainty Analysis of Measurements in Outdoor air flow Control Strategies”, HVAC&R Research, V19(4), pp. 423-434, 2013.
  119. Zhao Y, Wang SW and Xiao F, “A system-level incipient fault detection method for HVAC&R systems”, HVAC&R Research, V19(5). pp. 593-601, 2013.
  120. Huang GS, Sun YJ and Wang SW, “Building instantaneous cooling load fused measurement: multiple-sensor-based fusion versus chiller-model-based fusion”, Building Services Engineering Research & Technology, V34(2), pp. 177-194, 2013.
  121. Zhao Y, Wang SW, Xiao F and Ma ZJ, “A simplified physical model-based fault detection and diagnosis strategy and its customized tool for centrifugal chillers”, HVAC&R Research, V19(3), pp. 283-294, 2013.
  122. Sun YJ, Wang SW, Xiao F and Huang GS, “In-situ Performance Comparison and Evaluation of Three Chiller Sequencing Control Strategies in a Super High-rise Building”, Energy and Buildings, V61, pp.333-343, 2013.
  123. Sun YJ, Wang SW, Xiao F and Gao DC, “Peak Load Shifting Control Using Different Cold Thermal Energy Storage Facilities in Commercial Buildings: A Review”, Energy Conversion and Management, V71, pp.101-114, 2013.
  124. Sun YJ, Huang GS, Li ZW and Wang SW, “Multiplex Optimization for Complex Air Conditioning Systems”, Building and Environment, V65, pp.99-108, 2013.
  125. Shen LM, Xiao F, Chen HX and Wang SW, “Investigation of a novel thermoelectric radiant air-conditioning system”, Energy and Buildings, V59(4), pp. 123-132, 2013.
  126. Zhao Y, Wang SW and Xiao F, “A statistical fault detection and diagnosis method for centrifugal chillers based on exponentially-weighted moving average control charts and support vector regression”, Applied Thermal Engineering, V51(1–2), pp. 560-572, 2013.
  127. Zhao Y, Xiao F and Wang SW, “An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network”, Energy and Buildings, V57(2), pp. 278-288, 2013.
  128. Wang SW, Gao DC, Sun YJ and Xiao F, “An online adaptive optimal control strategy for complex building chilled water systems involving intermediate heat exchangers”, Applied Thermal Engineering, V50(1), pp. 614-628, 2013.
  129. Sun YJ, Wang SW and Xiao F, “Development and validation of a simplified online cooling load prediction strategy for a super high-rise building in Hong Kong “, Energy Conversion and Management, V68(4),pp. 20-27, 2013.
  130. Wang SW, Yan CC, and Xiao F, “Quantitative energy performance assessment methods for existing buildings Review”, Energy and Buildings, V55(12), pp. 873-888, 2012.
  131. Wang S.W. Yan C.C. and Xiao F “A simplified energy performance assessment method for existing buildings based on energy bill disaggregation”, Energy and Buildings, V55(12), pp. 563-574, 2012.
  132. Shan K, Sun YJ, Wang, SW and Yan CC, “Development and In-situ validation of a multi-zone demand-controlled ventilation strategy using a limited number of sensors”, Building and Environment, V57(11), pp. 28-37, 2012.
  133. Gao DC, Wang SW, Sun YJ and F Xiao, “Diagnosis of the low temperature difference syndrome in the chilled water system of a super high-rise building: A case study”, Applied Energy V98 pp. 597-606, 2012.
  134. Ge GM, Xiao F and Wang SW, “Optimization of a liquid desiccant based dedicated outdoor air-chilled ceiling system serving multi-zone spaces”, Building Simulation, V5(3), pp. 257-266, 2012.
  135. Shen LM, Xiao F, Chen HX and Wang SW, “Numerical and experimental analysis of transient supercooling effect of voltage pulse on thermoelectric element”, International Journal of Refrigeration, V35(4), pp.1156–1165, 2012.
  136. Ge GM, Xiao F and Wang SW, “Neural network based prediction method for preventing condensation in chilled ceiling systems”, Energy and Buildings, V45, pp. 290-298, 2012.
  137. Ge GM, Xiao F, Wang SW and Pu L, “Effects of discharge recirculation in cooling towers on energy efficiency and visible plume potential of chilling plants”, Applied Thermal Engineering, V39, pp. 37-44,2012.
  138. Ma ZJ and Wang SW, “Fault-tolerant supervisory control of building condenser cooling systems for energy efficiency”, HVAC&R Research, V18(1-2), pp.126-146, 2012.
  139. Xuan YM, Xiao F, Niu XF, Huang GS and Wang SW, “Research and applications of evaporative cooling in China: A review (I) – Research”, Renewable and Sustainable Energy Reviews, 16(5), pp. 3535-3546, 2012.
  140. Xuan YM, Xiao F, Niu XF, Huang GS and Wang SW, “Research and applications of evaporative cooling in China: A review (II) – Systems and equipment”, Renewable and Sustainable Energy Reviews, 16(5), pp.3523-3534, 2012.
  141. Gao DC, Wang SW and Sun YJ, “A fault-tolerant and energy efficient control strategy for primary-secondary chilled water systems in buildings, Energy and Buildings, V43(12), pp.3646-3656, 2011.
  142. Zhu N, Wang SW, Ma ZJ and Sun YJ, “Energy Performance and Optimal Control of Air-conditioned Buildings with Envelopes Enhanced by Phase Change Materials”, Energy Conversion and Management, V52(1), pp.3197–3205, 2011.
  143. Xiao F, Zheng CY and Wang SW, “A fault detection and diagnosis strategy with enhanced sensitivity for centrifugal chillers”, Applied Thermal Engineering, 31(17-18), pp.3963-3970, 2011.
  144. Wang SW, “Use of Phase Change Materials in Buildings – Can They Play A Role in Demand Side Management for Smart Grid?”, editorial, HVAC&R Research, V17(5), pp. 615-618, 2011.
  145. Sun ZW, Wang SW and Zhu N, “Model-based Optimal Control of Outdoor Air Flow Rate of an Air-Conditioning System with Primary Air Handling Unit”, Indoor and Built Environment, V20(6), pp.626-637, 2011.
  146. Wang SW, Sun ZW, Sun YJ and Zhu Na, “Online Optimal Ventilation Control of Building Air-conditioning Systems”, Indoor and Built Environment, V20(1), pp. 129-136, 2011.
  147. Ma ZJ and Wang SW, “Online Fault Detection and Robust Control of Condenser Cooling Water Systems in Building Central Chiller Plants”, Energy and Buildings, V43(1), pp.153-165, 2011.
  148. Ma Z.J. and Wang S.W., “Enhancing The Performance of Large Primary-Secondary Chilled Water Systems by Using Bypass Check Valve”, Energy, V36(1), pp. 268-276, 2011.
  149. Ma ZJ and Wang SW, “Test and evaluation of energy saving potentials in a complex building central chilling system using genetic algorithms”, Building Services Engineering Research & Technology, 32 (2), pp.109–126, 2011.
  150. Ma ZJ and Wang SW, “Supervisory and optimal control of centralized chilling systems using simplified adaptive models and genetic algorithm”, Applied Energy, V88(1), pp.198-211, 2011.
  151. Sun ZW, Wang SW and Ma ZJ, “In-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation strategy in a multi-zone office building”, Building and Environment, V46(1), pp. 124-133, 2011.
  152. Wang SW, Ma ZJ and Gao DC, “Experimental validation of the feasibility by using a check valve to enhance the operational performance of a complex chilled water system”, Applied Thermal Engineering, V30(17-18), pp. 2827-2832, 2010.
  153. Xu XH, Wang SW, Wang JB and Xiao F, “Active pipe-embedded structures in buildings for utilizing low-grade energy sources: A review”, Energy and Buildings, V42(10), pp.1567-1581, 2010.
  154. Sun YJ, Wang SW and Huang GS, “A demand limiting strategy for maximizing monthly cost savings of commercial buildings”, Energy and Buildings, V42(11), pp. 2219-2230, 2010.
  155. Zhu N, Wang SW, Xu XH and Ma ZJ, “Simplified dynamic model of building structures integrated with SSPCM using GA-based parameter identification”, International Journal of Thermal Sciences, V49(9), pp.1722-1731, 2010.
  156. Wang SW, Zhou Q and Xiao F, “A system-level fault detection and diagnosis strategy for HVAC systems involving sensor faults”, Energy and Buildings, V42(4), pp. 477-490, 2010.
  157. Huang GS, Wang SW and Xu XH, “Robust model predictive control of VAV air-handling units concerning uncertainties and constraints’, HVAC&R Research, V16(1), pp.15-33, 2010.
  158. Sun YJ, Wang SW and Huang GS, “Model-based optimal start control strategy for multi-chiller plants in commercial buildings”, Building Services Engineering Research and Technology, V31(2), pp.113-129, 2010.
  159. Xu XH, Wang SW, Huang GS, “Robust MPC for temperature control of air-conditioning systems concerning on constraints and multitype uncertainties”, Building Services Engineering Research and Technology, V31(1), pp.39-55 2010.
  160. Sun ZW and Wang SW, “A CFD-based test method for control of indoor environment and space ventilation”, Building and Environment, V45(6), pp.1441-1447, 2010.
  161. Sun YJ, Wang SW, Huang GS, “Online sensor fault detection and diagnosis method for chiller sequencing control”, International Journal of Thermal Sciences, V49(3), pp. 589-602, 2010.
  162. Sun ZW, Wang SW, Zhou QL and Hui SE, “Experimental study on desulfurization efficiency and gas-liquid mass transfer in a new liquid-screen desulfurization system”, Applied Energy, V87(5), pp.1505-1512, 2010.

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