This page has only limited features, please log in for full access.

Prof. Chengchu Yan
College of Urban Construction, Nanjing Tech University, Nanjing 210009, China

Basic Info


Research Keywords & Expertise

0 Renewable Energy
0 Thermal Energy Storage
0 Building energy efficiency
0 Zero-Energy Buildings
0 Energy flexible buildings

Fingerprints

Renewable Energy
Zero-Energy Buildings
Building demand response
Thermal Energy Storage

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 13 July 2021 in Building and Environment
Reads 0
Downloads 0

A comfortable indoor environment plays an important role in improving students' learning efficiency and health. How to optimize the design of primary and secondary school education buildings to achieve a comfortable indoor environment, considering both energy and cost is a considerable challenge. This paper proposes a two-stage multi-objective optimization method based on a meta-model to obtain the optimal design scheme for primary and secondary school education buildings, based on daylighting, thermal comfort, energy savings and economy. The method has two stages: building envelope optimization and building generation system optimization. In the stage of building envelope optimization, an artificial neural network (ANN) model coupling optimization algorithm is used to optimize the building envelope. The performances of the non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO) algorithm are compared in the optimization process. In the stage of building generation system optimization, the design optimization of the building photovoltaic generation system is studied. Finally, the effectiveness of the two-stage optimization method is verified by a typical teaching building in Nanjing. The results show that the optimal scheme set of building envelope design can be obtained by this optimization method, and the optimal tilt angle and azimuth angle of the photovoltaic generation system are 30° and 210°, respectively. The minimum payback periods of the photovoltaic generation system are 11.75 years and 9.32 years under the policy of selling electricity that is not permitted and selling electricity that is permitted, respectively.

ACS Style

Yizhe Xu; Guangli Zhang; Chengchu Yan; Gang Wang; Yanlong Jiang; Ke Zhao. A two-stage multi-objective optimization method for envelope and energy generation systems of primary and secondary school teaching buildings in China. Building and Environment 2021, 204, 108142 .

AMA Style

Yizhe Xu, Guangli Zhang, Chengchu Yan, Gang Wang, Yanlong Jiang, Ke Zhao. A two-stage multi-objective optimization method for envelope and energy generation systems of primary and secondary school teaching buildings in China. Building and Environment. 2021; 204 ():108142.

Chicago/Turabian Style

Yizhe Xu; Guangli Zhang; Chengchu Yan; Gang Wang; Yanlong Jiang; Ke Zhao. 2021. "A two-stage multi-objective optimization method for envelope and energy generation systems of primary and secondary school teaching buildings in China." Building and Environment 204, no. : 108142.

Journal article
Published: 17 February 2021 in Sustainable Energy Technologies and Assessments
Reads 0
Downloads 0

With the wide application of building automation systems (BASs), a large amount of building operation data are usually available, which provide a good basis for the optimal operation of a building’s heating, ventilation and air conditioning (HVAC) systems. In this study, a data mining (DM)-based method is proposed for the anomaly detection and dynamic energy performance evaluation of an HVAC system. In this method, first a DM technology is used to detect the abnormal operation data from historical operation data and identify the possible reasons for abnormalities. Then, the identified abnormal energy consumption data caused by faults are corrected. On this basis, a multilevel dynamic energy performance benchmark and a set of energy performance evaluation rules for the HVAC system are established. Finally, the real-time operation performance of an HVAC system is evaluated, and the causes of abnormal energy consumption are identified at multiple levels. The effectiveness of the proposed method is verified in a case study of a commercial building with a complex cooling system.

ACS Style

Yizhe Xu; Chengchu Yan; Jingfeng Shi; Zefeng Lu; Xiaofeng Niu; Yanlong Jiang; Faxing Zhu. An anomaly detection and dynamic energy performance evaluation method for HVAC systems based on data mining. Sustainable Energy Technologies and Assessments 2021, 44, 101092 .

AMA Style

Yizhe Xu, Chengchu Yan, Jingfeng Shi, Zefeng Lu, Xiaofeng Niu, Yanlong Jiang, Faxing Zhu. An anomaly detection and dynamic energy performance evaluation method for HVAC systems based on data mining. Sustainable Energy Technologies and Assessments. 2021; 44 ():101092.

Chicago/Turabian Style

Yizhe Xu; Chengchu Yan; Jingfeng Shi; Zefeng Lu; Xiaofeng Niu; Yanlong Jiang; Faxing Zhu. 2021. "An anomaly detection and dynamic energy performance evaluation method for HVAC systems based on data mining." Sustainable Energy Technologies and Assessments 44, no. : 101092.

Review
Published: 04 July 2020 in Sustainable Cities and Society
Reads 0
Downloads 0

Smart energy systems that integrate multiple energy sectors are considered a promising paradigm for providing a comprehensive and optimized solution for an achievable, affordable, and sustainable energy system in the near future. Although extensive studies on the definition, implementation and optimization of these systems have been conducted, the design and management of a smart energy system remains a critical challenge. This paper reviews the definition and composition of typical smart energy systems to provide a comprehensive and holistic understanding of smart energy systems. Design and operation optimization are addressed to achieve the synergies and complementary advantages of subsystems while maintaining the high performance of individual systems. Different objectives, models and algorithms for design optimization of a smart energy system are compared. Recent studies and applications of operation optimization for an entire system and individual subsystems are presented. The main challenges of the design optimization and operation optimization in the research and development of future smart energy systems are summarized.

ACS Style

Yizhe Xu; Chengchu Yan; Huifang Liu; Jin Wang; Zhang Yang; Yanlong Jiang. Smart energy systems: A critical review on design and operation optimization. Sustainable Cities and Society 2020, 62, 102369 .

AMA Style

Yizhe Xu, Chengchu Yan, Huifang Liu, Jin Wang, Zhang Yang, Yanlong Jiang. Smart energy systems: A critical review on design and operation optimization. Sustainable Cities and Society. 2020; 62 ():102369.

Chicago/Turabian Style

Yizhe Xu; Chengchu Yan; Huifang Liu; Jin Wang; Zhang Yang; Yanlong Jiang. 2020. "Smart energy systems: A critical review on design and operation optimization." Sustainable Cities and Society 62, no. : 102369.

Journal article
Published: 05 September 2019 in Science and Technology for the Built Environment
Reads 0
Downloads 0
ACS Style

Chen Jin; Chengchu Yan; Rui Tang; Hao Cai; Ruixuan Zeng. A fast building demand response method based on supply–demand coordination for urgent responses to smart grids. Science and Technology for the Built Environment 2019, 1 -11.

AMA Style

Chen Jin, Chengchu Yan, Rui Tang, Hao Cai, Ruixuan Zeng. A fast building demand response method based on supply–demand coordination for urgent responses to smart grids. Science and Technology for the Built Environment. 2019; ():1-11.

Chicago/Turabian Style

Chen Jin; Chengchu Yan; Rui Tang; Hao Cai; Ruixuan Zeng. 2019. "A fast building demand response method based on supply–demand coordination for urgent responses to smart grids." Science and Technology for the Built Environment , no. : 1-11.

Journal article
Published: 14 April 2019 in Applied Sciences
Reads 0
Downloads 0

Conventional and most optimal design methods for chiller plants often address the annual cooling load distribution of buildings and their peak cooling loads based on typical meteorological year (TMY) data, while the peak cooling load only appears a few times during the life-cycle and the sized chiller plant usually operates within its low efficient region. In this paper, a robust optimal design method based on life-cycle total cost was employed to optimize the design of a chiller plant with quantified analysis of uncertainty and reliability. By using the proposed design method, the optimized chiller plant can operate at its highly efficient region under various cooling load conditions, and provide sufficient cooling capacity even alongside some equipment/systems with failures. The minimum life-cycle total cost, which consists of the capital cost, operation, and availability-risk cost, can be achieved through optimizing the total cooling capacity and the numbers/sizes of chillers. A case study was conducted to illustrate the detailed implementation process of the proposed method. The performance of this design method was evaluated by comparing with that of other design methods.

ACS Style

Chengchu Yan; Qi Cheng; Hao Cai. Life-Cycle Optimization of a Chiller Plant with Quantified Analysis of Uncertainty and Reliability in Commercial Buildings. Applied Sciences 2019, 9, 1548 .

AMA Style

Chengchu Yan, Qi Cheng, Hao Cai. Life-Cycle Optimization of a Chiller Plant with Quantified Analysis of Uncertainty and Reliability in Commercial Buildings. Applied Sciences. 2019; 9 (8):1548.

Chicago/Turabian Style

Chengchu Yan; Qi Cheng; Hao Cai. 2019. "Life-Cycle Optimization of a Chiller Plant with Quantified Analysis of Uncertainty and Reliability in Commercial Buildings." Applied Sciences 9, no. 8: 1548.

Journal article
Published: 26 March 2019 in Building and Environment
Reads 0
Downloads 0

Locating the sources of contaminants or hazardous substances in indoor environments is extremely important for ensuring indoor air quality and indoor environmental safety. Existing source localization studies have focused on environments with strong airflow, and very few studies have addressed the more challenging source localization problems in environments with no strong airflow. In this study, we developed a mobile robot for source localization and used the robot to test and compare three single-robot source localization algorithms (E. coli, spiral and hex-path) that have the potential to be applied to environments with no strong airflow. Each algorithm was tested by 15 independent experiments. Considering both the success rates and average numbers of steps, the performance of the three algorithms from high to low was in the order of the hex-path algorithm, E. coli algorithm, and spiral algorithm, with the success rates of 73.3%, 66.7% and 60.0%, and the average numbers of steps of 51.43, 54.12, and 63.67, respectively. Based on the same comparison criteria, all three algorithms can significantly improve the success rate or reduce the average number of steps compared with a random algorithm that encounters the source solely by chance. This study can provide more choices for developing single-robot source localization methods for environments with no strong airflow and can provide inspiration and guidance for improving existing methods and developing new methods.

ACS Style

Yibin Yang; Qilin Feng; Hao Cai; Jiheng Xu; Fei Li; Zhengdong Deng; Chengchu Yan; Xianting Li. Experimental study on three single-robot active olfaction algorithms for locating contaminant sources in indoor environments with no strong airflow. Building and Environment 2019, 155, 320 -333.

AMA Style

Yibin Yang, Qilin Feng, Hao Cai, Jiheng Xu, Fei Li, Zhengdong Deng, Chengchu Yan, Xianting Li. Experimental study on three single-robot active olfaction algorithms for locating contaminant sources in indoor environments with no strong airflow. Building and Environment. 2019; 155 ():320-333.

Chicago/Turabian Style

Yibin Yang; Qilin Feng; Hao Cai; Jiheng Xu; Fei Li; Zhengdong Deng; Chengchu Yan; Xianting Li. 2019. "Experimental study on three single-robot active olfaction algorithms for locating contaminant sources in indoor environments with no strong airflow." Building and Environment 155, no. : 320-333.

Conference paper
Published: 04 March 2019 in IOP Conference Series: Earth and Environmental Science
Reads 0
Downloads 0

As the major electricity consumers worldwide, buildings can play an important role for power balance of smart grid through demand response (DR). Demand side-based control and supply side-based control are two typical types of DR measures when using centralized building air-conditioning systems for DR. For demand side-based control, the major disadvantage is that the response speed is generally too slow to allow buildings providing an immediate power reduction for the smart grid. For supply side-based control, the response speed is fast enough while it may cause control disorder to the whole system and uneven indoor temperature increase among different zones. In order to overcome above disadvantages, we proposed a novel DR method for building air-conditioning systems, which combines both the demand side-based and supply side-based control simultaneously. It consists of two major steps. First, some running chillers will be shut down to provide an immediate power reduction once urgent power reduction requests from smart grids are received by buildings. Second, the indoor air temperature set-points will be adjusted stepwise based on an "incremental schedule" to achieve a uniformly indoor temperature rise among all concerned zones/rooms. By implementing such two steps, an immediate power reduction is achieved while minimizing the uneven sacrifice of thermal comfort among different occupants. Two new performance indexes are proposed to evaluate the thermal comfort performance of DR methods. The proposed DR method is implemented and tested as case study in a virtual building dynamically simulated by TRNSYS. Five scenarios with different incremental steps for adjusting the temperature set-points are compared to determine the optimum "incremental schedule". Results show that buildings can provide immediate power reduction and achieve a small and even thermal comfort sacrifice by implementing the proposed compound DR method.

ACS Style

Chen Jin; Chengchu Yan; Rui Tang. A Compound HVAC-Based Demand Response Method for Urgent Responses of Commercial Buildings Towards Smart Grids. IOP Conference Series: Earth and Environmental Science 2019, 238, 012064 .

AMA Style

Chen Jin, Chengchu Yan, Rui Tang. A Compound HVAC-Based Demand Response Method for Urgent Responses of Commercial Buildings Towards Smart Grids. IOP Conference Series: Earth and Environmental Science. 2019; 238 (1):012064.

Chicago/Turabian Style

Chen Jin; Chengchu Yan; Rui Tang. 2019. "A Compound HVAC-Based Demand Response Method for Urgent Responses of Commercial Buildings Towards Smart Grids." IOP Conference Series: Earth and Environmental Science 238, no. 1: 012064.

Journal article
Published: 01 February 2019 in Energy Procedia
Reads 0
Downloads 0

Building energy systems are gradually changing from a single form of conventional energies to a multi-energy system that usually includes multiple renewable energy sources. The poor reliability and controllability of renewable energies are likely to cause mismatches between supply and demand, which significantly affect the energy efficiency of the whole building. This paper proposes a systematic methodology for the design optimization of building energy systems integrated by a multiple renewable energy source. A unified mathematical model of multi-energy systems is established based on the concept of energy-hub, in which the core idea is to use a matrix approach to standardize the unified modeling of a variety of building energy processes including energy generation, energy utilization and energy storage. The operating performance of system with different energy sources mixes and system configurations can be effectively predicted. Lifecycle total cost of the entire system, mainly consisting of initial cost and operating cost, is used as the objective function to identify the best design scenarios for sustainable building development. A case study is conducted on the application of the proposed method for optimal design of a typical hybrid renewable energy system in Beijing.

ACS Style

Shuangjun Xu; Chengchu Yan; Chen Jin. Design Optimization of Hybrid Renewable Energy Systems for Sustainable Building Development based on Energy-Hub. Energy Procedia 2019, 158, 1015 -1020.

AMA Style

Shuangjun Xu, Chengchu Yan, Chen Jin. Design Optimization of Hybrid Renewable Energy Systems for Sustainable Building Development based on Energy-Hub. Energy Procedia. 2019; 158 ():1015-1020.

Chicago/Turabian Style

Shuangjun Xu; Chengchu Yan; Chen Jin. 2019. "Design Optimization of Hybrid Renewable Energy Systems for Sustainable Building Development based on Energy-Hub." Energy Procedia 158, no. : 1015-1020.

Journal article
Published: 27 November 2018 in Applied Energy
Reads 0
Downloads 0

The development of advanced data-driven approaches for building energy management is becoming increasingly essential in the era of big data. Machine learning techniques have gained great popularity in predictive modeling due to their excellence in capturing nonlinear and complicated relationships. However, it is a big challenge for building professionals to fully understand the inference mechanism learnt and put trust into the prediction made, as the models developed are typically of high complexity and low interpretability. To enhance the practical value of advanced machine learning techniques in the building field, this study proposes a comprehensive methodology to explain and evaluate data-driven building energy performance models. The methodology is developed based on the framework of interpretable machine learning. It can help building professionals to understand the inference mechanism learnt, e.g., why a certain prediction is made and what are the supporting and conflicting evidences towards the prediction. A novel metric, i.e., trust, is proposed as an alternative approach other than conventional accuracy metrics to evaluate model performance. The methodology has been validated based on actual building operational data. The results obtained are valuable for the development of intelligent and user-friendly building management systems.

ACS Style

Cheng Fan; Fu Xiao; Chengchu Yan; Chengliang Liu; Zhengdao Li; Jiayuan Wang. A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning. Applied Energy 2018, 235, 1551 -1560.

AMA Style

Cheng Fan, Fu Xiao, Chengchu Yan, Chengliang Liu, Zhengdao Li, Jiayuan Wang. A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning. Applied Energy. 2018; 235 ():1551-1560.

Chicago/Turabian Style

Cheng Fan; Fu Xiao; Chengchu Yan; Chengliang Liu; Zhengdao Li; Jiayuan Wang. 2018. "A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning." Applied Energy 235, no. : 1551-1560.

Journal article
Published: 17 July 2018 in Renewable Energy
Reads 0
Downloads 0

In this paper, a new configuration of distributed energy system (DES), which integrates a district cooling system, is proposed as a new energy-efficient technology to be used in cooling dominated districts. An optimal design approach is developed for DES design and operation scheduling by using the real site measurements of energy demands. A case study on the DES in a high density district, i.e., a university campus in Hong Kong, is performed. The energy and economic performance of the DES, the matching performance of on-site generations and the efficiency of electric chillers are analyzed and compared with that of the centralized energy system (CES). It can be found that the proposed DES is a cost-effective and energy-efficient technology for the regions concerned. The DES contributes to substantial primary energy saving of 9.6% and a significant reduction in the operating cost of 44%. The distributed generations in the DES can match electricity demand very well around the year while the absorption chillers can match cooling demand well in transition months. Compared with the CES, the DES allows electric chillers of larger capacities to be used and to operate at higher part load ratios, resulting in higher energy efficiency in operation.

ACS Style

Jing Kang; Shengwei Wang; Chengchu Yan. A new distributed energy system configuration for cooling dominated districts and the performance assessment based on real site measurements. Renewable Energy 2018, 131, 390 -403.

AMA Style

Jing Kang, Shengwei Wang, Chengchu Yan. A new distributed energy system configuration for cooling dominated districts and the performance assessment based on real site measurements. Renewable Energy. 2018; 131 ():390-403.

Chicago/Turabian Style

Jing Kang; Shengwei Wang; Chengchu Yan. 2018. "A new distributed energy system configuration for cooling dominated districts and the performance assessment based on real site measurements." Renewable Energy 131, no. : 390-403.

Journal article
Published: 21 June 2018 in Buildings
Reads 0
Downloads 0

Low delta-T syndrome often occurs in building chilled water systems, which makes systems fail to operate as efficiently as originally anticipated. Extensive studies have been conducted on the subject of low delta-T syndrome with the aims of investigating the potential causes behind and the ways to keep delta-T high. This paper addresses to explain the causes of degrading delta-T from a mathematic perspective and to analyze the impacts of important operational parameters on the delta-T quantitatively. A simplified global cooling coil model representing the relationship between the total cooling load and the total water flow rate of chilled water systems is developed, which can be used to predict the system delta-T under different load distribution and system operation conditions. It is proved mathematically that the load distribution characteristic is an important factor in influencing the system delta-T of a chilled water system. This finding explains why the system delta-T is always lower than the delta-T of individual coils, particularly under low partial load conditions. A system-level fault detection and diagnosis (FDD) method is proposed for identifying the possible causes of the low delta-T problem. A case study is conducted to validate the proposed global model and FDD method in a real building.

ACS Style

Chengchu Yan; Xiuxiu Yang; Yizhe Xu. Mathematical Explanation and Fault Diagnosis of Low Delta-T Syndrome in Building Chilled Water Systems. Buildings 2018, 8, 84 .

AMA Style

Chengchu Yan, Xiuxiu Yang, Yizhe Xu. Mathematical Explanation and Fault Diagnosis of Low Delta-T Syndrome in Building Chilled Water Systems. Buildings. 2018; 8 (7):84.

Chicago/Turabian Style

Chengchu Yan; Xiuxiu Yang; Yizhe Xu. 2018. "Mathematical Explanation and Fault Diagnosis of Low Delta-T Syndrome in Building Chilled Water Systems." Buildings 8, no. 7: 84.

Journal article
Published: 16 April 2018 in Current Sustainable/Renewable Energy Reports
Reads 0
Downloads 0

This paper reviews the data mining (DM)-related research and applications at the building operation stage. It aims to summarize DM-based solutions for building energy management and reveal current research and development outcomes in analyzing massive building operational data using advanced DM techniques. Previous studies mainly adopt DM techniques for two tasks, i.e., (1) predictive modeling; (2) fault detection and diagnosis. The knowledge discovered has been successfully utilized to facilitate the decision-making during building operations. Domain expertise play the dominant role in the knowledge discovery process, which limits the chance of discovering novel knowledge. DM is a promising technology for the development of intelligent and automated building management systems. Despite encouraging results, more research efforts should be made in (1) exploring the usefulness of unsupervised DM, (2) developing generic analytic frameworks, and (3) analyzing unstructured and multi-relational data sets.

ACS Style

Cheng Fan; Fu Xiao; Chengchu Yan. Research and Applications of Data Mining Techniques for Improving Building Operational Performance. Current Sustainable/Renewable Energy Reports 2018, 5, 181 -188.

AMA Style

Cheng Fan, Fu Xiao, Chengchu Yan. Research and Applications of Data Mining Techniques for Improving Building Operational Performance. Current Sustainable/Renewable Energy Reports. 2018; 5 (2):181-188.

Chicago/Turabian Style

Cheng Fan; Fu Xiao; Chengchu Yan. 2018. "Research and Applications of Data Mining Techniques for Improving Building Operational Performance." Current Sustainable/Renewable Energy Reports 5, no. 2: 181-188.

Journal article
Published: 01 March 2018 in Automation in Construction
Reads 0
Downloads 0
ACS Style

Rui Tang; Shengwei Wang; Chengchu Yan. A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids. Automation in Construction 2018, 87, 74 -83.

AMA Style

Rui Tang, Shengwei Wang, Chengchu Yan. A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids. Automation in Construction. 2018; 87 ():74-83.

Chicago/Turabian Style

Rui Tang; Shengwei Wang; Chengchu Yan. 2018. "A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids." Automation in Construction 87, no. : 74-83.

Journal article
Published: 01 November 2017 in Applied Energy
Reads 0
Downloads 0
ACS Style

Chengchu Yan; Wenjie Gang; Xiaofeng Niu; Xujian Peng; Shengwei Wang. Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems. Applied Energy 2017, 205, 635 -643.

AMA Style

Chengchu Yan, Wenjie Gang, Xiaofeng Niu, Xujian Peng, Shengwei Wang. Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems. Applied Energy. 2017; 205 ():635-643.

Chicago/Turabian Style

Chengchu Yan; Wenjie Gang; Xiaofeng Niu; Xujian Peng; Shengwei Wang. 2017. "Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems." Applied Energy 205, no. : 635-643.

Journal article
Published: 01 February 2017 in Applied Energy
Reads 0
Downloads 0

It is acknowledged that the conventional design methods can easily lead to oversized system or unsatisfactory performance for different design conditions. Most existing studies on design optimization of net zero energy building (nZEB) are conducted based on deterministic data/information. However, the question is: How is the actual performance of a design nZEB in different years considering uncertainties? This study, therefore, proposed a robust design method for sizing renewable energy systems in nZEB concerning uncertainties in renewable resources and demand load. The proposed robust design method is applied to the planning of renewable energy system for the Hong Kong Zero Carbon Building. The annual performance of nZEB under the optimal design options are systematically investigated and compared using the proposed robust design method and the deterministic method. It is meaningful to obtain a fitting formula to identify the relationship between the probability of achieving annual zero energy balance and the design mismatch ratio. On the basis of Monte Carlo uncertainty propagation methods, the uncertainty of nZEB performance is quantified which provides flexibility for designers in selecting appropriate design options according to the required probability of achieving nZEB during the design stage.Department of Building Services Engineerin

ACS Style

Yuehong Lu; Shengwei Wang; Chengchu Yan; Zhijia Huang. Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties. Applied Energy 2017, 187, 62 -71.

AMA Style

Yuehong Lu, Shengwei Wang, Chengchu Yan, Zhijia Huang. Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties. Applied Energy. 2017; 187 ():62-71.

Chicago/Turabian Style

Yuehong Lu; Shengwei Wang; Chengchu Yan; Zhijia Huang. 2017. "Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties." Applied Energy 187, no. : 62-71.

Journal article
Published: 01 January 2017 in Applied Energy
Reads 0
Downloads 0

Conventional design of chiller plant is typically based on the peak cooling loads of buildings, while the cooling load reaches its peak level for only a small proportion of time in a year. This results in that even a perfectly designed chiller plant could be very significantly oversized in actual operation and it thus causes significant energy wastes. In this paper, an uncertainty-based optimal design based on probabilistic approach is proposed to optimize the chiller plant design. It ensures that the chiller plant operate at a high efficiency and the minimum annual total cost (including annual operational cost and annual capital cost) could be achieved under various possible cooling load conditions, considering the uncertain variables in cooling load calculation (i.e., weather conditions). On the premise of determining the minimum sufficient number of Monte Carlo simulation, this method maximizes the operating COP (coefficient of performance) and minimizing the annual total cost. A case study on the chiller plant of a building in Hong Kong is conducted to demonstrate the design process and validate the uncertainty-based optimal design method.

ACS Style

Qi Cheng; Shengwei Wang; Chengchu Yan; Fu Xiao. Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings. Applied Energy 2017, 185, 1613 -1624.

AMA Style

Qi Cheng, Shengwei Wang, Chengchu Yan, Fu Xiao. Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings. Applied Energy. 2017; 185 ():1613-1624.

Chicago/Turabian Style

Qi Cheng; Shengwei Wang; Chengchu Yan; Fu Xiao. 2017. "Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings." Applied Energy 185, no. : 1613-1624.

Journal article
Published: 01 January 2017 in Procedia Engineering
Reads 0
Downloads 0
ACS Style

Chengchu Yan; Shengwei Wang; Xiuxiu Yang; Jing Kang. Three-level Energy Performance Calculation and Assessment Method for Information Poor Buildings. Procedia Engineering 2017, 205, 2223 -2230.

AMA Style

Chengchu Yan, Shengwei Wang, Xiuxiu Yang, Jing Kang. Three-level Energy Performance Calculation and Assessment Method for Information Poor Buildings. Procedia Engineering. 2017; 205 ():2223-2230.

Chicago/Turabian Style

Chengchu Yan; Shengwei Wang; Xiuxiu Yang; Jing Kang. 2017. "Three-level Energy Performance Calculation and Assessment Method for Information Poor Buildings." Procedia Engineering 205, no. : 2223-2230.

Journal article
Published: 01 January 2017 in Energy
Reads 0
Downloads 0

Conventional design of cooling water systems mainly focused on the individual components of cooling water system, not the system as a whole. In this paper, a robust optimal design based on sequential Monte Carlo simulation is proposed to optimize the design of cooling water system. Monte Carlo simulation is used to obtain the cooling load distribution of required accuracy, power consumption and unmet cooling load. Convergence assessment is conducted to terminate the sampling process of Monte Carlo simulation. Under different penalty ratios and repair rates, this proposed design minimizes the annual total cost of cooling water system. A case study of a building in Hong Kong is conducted to demonstrate the design process and test the robust optimal design method. The results show that the minimum total cost could be achieved under various possible cooling load conditions considering the uncertainties of design inputs and reliability of system components.Department of Building Services Engineerin

ACS Style

Qi Cheng; Shengwei Wang; Chengchu Yan. Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability. Energy 2017, 118, 489 -501.

AMA Style

Qi Cheng, Shengwei Wang, Chengchu Yan. Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability. Energy. 2017; 118 ():489-501.

Chicago/Turabian Style

Qi Cheng; Shengwei Wang; Chengchu Yan. 2017. "Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability." Energy 118, no. : 489-501.

Research article
Published: 24 September 2016 in Building Services Engineering Research and Technology
Reads 0
Downloads 0

Peak demand cost usually contributes a large proportion of the total electricity bills in buildings. Using existing building facilities for power demand limiting has been verified as effective measures to reduce monthly peak demands and associated costs. Fire service water tanks exist in most commercial buildings. This paper presents a comprehensive study on how to effectively retrofit existing building fire service water tanks as chilled water storage for power demand limiting. Important technical and economic factors that may affect the implementation of the proposed retrofitting are addressed. Two retrofitting schemes, i.e. a small ΔT (storage temperature difference) scheme and a large ΔT scheme are proposed for integrating the chilled water storage system into an existing all-air system and an existing air-water air conditioning system, respectively. Two optimal demand limiting control strategies, i.e. time-based control and demand-based control, are proposed for maximizing the monthly peak demand reduction of buildings with regular and variable peak occurring time, respectively. The cost-effectiveness of different retrofitting schemes in three real buildings in Hong Kong is analysed. Results show that substantial cost savings can be achieved with short payback periods (0.7–2.6 years) for the retrofits in these three buildings. Practical application: This paper presents a techno-economic analysis on retrofitting existing building fire service water tanks as chilled water storage for power demand limiting and operational cost saving. The proposed retrofitting schemes and demand limiting control strategies enable chilled water storage systems to be readily applied to most existing buildings. Building owners can benefit from the peak demand cost saving as the monthly peak demand can be significantly reduced by using chilled water storage. The extra costs involved in tank retrofits and system integrations can be paid back within three years.

ACS Style

Chengchu Yan; Shengwei Wang; Cheng Fan; Fu Xiao. Retrofitting building fire service water tanks as chilled water storage for power demand limiting. Building Services Engineering Research and Technology 2016, 38, 47 -63.

AMA Style

Chengchu Yan, Shengwei Wang, Cheng Fan, Fu Xiao. Retrofitting building fire service water tanks as chilled water storage for power demand limiting. Building Services Engineering Research and Technology. 2016; 38 (1):47-63.

Chicago/Turabian Style

Chengchu Yan; Shengwei Wang; Cheng Fan; Fu Xiao. 2016. "Retrofitting building fire service water tanks as chilled water storage for power demand limiting." Building Services Engineering Research and Technology 38, no. 1: 47-63.

Journal article
Published: 01 August 2016 in Energy and Buildings
Reads 0
Downloads 0

Conventional design of chilled water systems is typically based on the peak cooling loads of buildings, while the cooling load reaches its peak level for only a small proportion of time in a year. This results in that design flow of chilled water system could be significantly oversized in actual operation and it thus causes significant energy wastes. In this paper, a robust optimal design based on minimized life-cycle cost is proposed to optimize the design of chilled water pump systems while concerning the uncertainties of design inputs and models as well as the component reliability in operation. Monte Carlo simulation is used to generate the cooling load distribution and hydraulic resistance distribution by quantifying the uncertainties. Markov method is used to obtain the probability distribution of the system state. Under different control methods, this proposed design method minimizes the annual total cost. A case study on a building in Hong Kong is conducted to demonstrate the design process and validate the robust optimal design method. Results show that the system could operate at a relatively high efficiency and the minimum total life-cycle cost could be achieved.

ACS Style

Qi Cheng; Shengwei Wang; Chengchu Yan. Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost. Energy and Buildings 2016, 126, 159 -169.

AMA Style

Qi Cheng, Shengwei Wang, Chengchu Yan. Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost. Energy and Buildings. 2016; 126 ():159-169.

Chicago/Turabian Style

Qi Cheng; Shengwei Wang; Chengchu Yan. 2016. "Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost." Energy and Buildings 126, no. : 159-169.