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Publications (10 of 32) Show all publications
Huang, P., Fan, C., Zhang, X. & Wang, J. (2019). A hierarchical coordinated demand response control for buildings with improved performances at building group. Applied Energy, 242, 684-694
Open this publication in new window or tab >>A hierarchical coordinated demand response control for buildings with improved performances at building group
2019 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 242, p. 684-694Article in journal (Refereed) Published
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-29729 (URN)10.1016/j.apenergy.2019.03.148 (DOI)
Available from: 2019-03-20 Created: 2019-03-20 Last updated: 2019-03-21Bibliographically approved
Pan, S., Du, S., Wang, X., Zhang, X., Xia, L., Liu, J., . . . Wei, Y. (2019). Analysis and interpretation of the particulate matter (PM10 and PM2.5) concentrations at the subway stations in Beijing, China. Sustainable cities and society, 45, 366-377
Open this publication in new window or tab >>Analysis and interpretation of the particulate matter (PM10 and PM2.5) concentrations at the subway stations in Beijing, China
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2019 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 45, p. 366-377Article in journal (Refereed) Published
Abstract [en]

The particulate matters (PM10 and PM2.5) inside urban subway stations greatly influence indoor air quality and passenger comfort. This study aims to analyze and interpret the concentrations of PM10 and PM2.5, measured in several subway stations from October 9th to 22nd, 2016 in Beijing, China. The overall methodology was based on the Statistical Package for Social Science (SPSS) software while General linear model (GLM) and correlation analysis were further applied to examine the sensitivities of different variables to the particle concentrations. The data analysis showed the average overall mass ratio of PM concentrations inside subway station is about 68.7%, much lower than outdoor condition (79.6%). In the areas of the station hall and platform, the real-time PM10 and PM2.5 concentrations varied periodically. In working and operation offices, all rooms had much higher PM concentrations than the outdoor environment when its pollution level was level 3, in which the facility room reached the highest level, while the closed meeting room had the lowest. Correlation analysis results indicated that PM10 and PM2.5 concentrations were mutually correlated (average R2 = 0.854), and a strong linear correlation (R2 = 0.897) of the subway-station PM concentrations to the outdoor PM conditions, regardless of the outdoor atmospheric PM concentrations pollution level was. Nevertheless, the impact of passenger number and temperature & humidity on the station PM concentrations was less, when compared to the outdoor environment. This paper is expected to provide useful information for further research and design of effective prevention measures on PM in local subway stations, towards a more sustainable and healthier built environment in the city underground. 

Keywords
Correlation analysis, Influencing factors, PM10, PM2.5, Subway station
National Category
Energy Engineering Energy Systems
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-28908 (URN)10.1016/j.scs.2018.11.020 (DOI)000455274500032 ()2-s2.0-85057734557 (Scopus ID)
Available from: 2018-11-19 Created: 2018-11-19 Last updated: 2019-01-24Bibliographically approved
Wei, Y., Xia, L., Pan, S., Wu, J., Zhang, X., Han, M., . . . Li, Q. (2019). Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks. Applied Energy, 240, 276-294
Open this publication in new window or tab >>Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks
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2019 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 240, p. 276-294Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Elsevier, 2019
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-29562 (URN)10.1016/j.apenergy.2019.02.056 (DOI)
Available from: 2019-02-24 Created: 2019-02-24 Last updated: 2019-02-25Bibliographically approved
Wei, Y., Zhang, X., Shi, Y., Xia, L., Pan, S., Wu, J., . . . Zhao, X. (2018). A review of data-driven approaches for prediction and classification of building energy consumption. Renewable & sustainable energy reviews, 82(1), 1027-1047
Open this publication in new window or tab >>A review of data-driven approaches for prediction and classification of building energy consumption
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2018 (English)In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 82, no 1, p. 1027-1047Article in journal (Refereed) Published
Abstract [en]

A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, including those methods for prediction (artificial neural networks, support vector machines, statistical regression, decision tree and genetic algorithm) and those methods for classification (K-mean clustering, self-organizing map and hierarchy clustering). The review results demonstrate that the data-driven approaches have well addressed a large variety of building energy related applications, such as load forecasting and prediction, energy pattern profiling, regional energy-consumption mapping, benchmarking for building stocks, global retrofit strategies and guideline making etc. Significantly, this review refines a few key tasks for modification of the data-driven approaches in the context of application to building energy analysis. The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies. It also paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands. All these will be useful to establish a better long-term strategy for urban sustainability.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Data driven approach, Building, Energy consumption, Prediction, Classification
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-26385 (URN)10.1016/j.rser.2017.09.108 (DOI)2-s2.0-85030703701 (Scopus ID)
Available from: 2017-10-09 Created: 2017-10-09 Last updated: 2017-11-15Bibliographically approved
Han, M., Zhang, X., Xu, L., May, R., Pan, S. & Wu, J. (2018). A review of reinforcement learning methodologies on control systems for building energy. Borlänge: Högskolan Dalarna
Open this publication in new window or tab >>A review of reinforcement learning methodologies on control systems for building energy
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2018 (English)Report (Other academic)
Abstract [en]

The usage of energy directly leads to a great amount of consumption of the non-renewable fossil resources. Exploiting fossil resources energy can influence both climate and health via ineluctable emissions. Raising awareness, choosing alternative energy and developing energy efficient equipment contributes to reducing the demand for fossil resources energy, but the implementation of them usually takes a long time. Since building energy amounts to around one-third of global energy consumption, and systems in buildings, e.g. HVAC, can be intervened by individual building management, advanced and reliable control techniques for buildings are expected to have a substantial contribution to reducing global energy consumptions. Among those control techniques, the model-free, data-driven reinforcement learning method seems distinctive and applicable. The success of the reinforcement learning method in many artificial intelligence applications has brought us an explicit indication of implementing the method on building energy control. Fruitful algorithms complement each other and guarantee the quality of the optimisation. As a central brain of smart building automation systems, the control technique directly affects the performance of buildings. However, the examination of previous works based on reinforcement learning methodologies are not available and, moreover, how the algorithms can be developed is still vague. Therefore, this paper briefly analyses the empirical applications from the methodology point of view and proposes the future research direction.

Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna, 2018. p. 26
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2018:02
Keywords
Reinforcement learning; Markov decision processes; building energy; control; multi-agent system
National Category
Control Engineering
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - methods
Identifiers
urn:nbn:se:du-27956 (URN)
Available from: 2018-06-19 Created: 2018-06-19 Last updated: 2018-06-20Bibliographically approved
Zhang, X., Lovati, M., Vigna, I., Widén, J., Han, M., Gál, C. V. & Feng, T. (2018). A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions. Applied Energy, 230, 1034-1056
Open this publication in new window or tab >>A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions
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2018 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 230, p. 1034-1056Article in journal (Refereed) Published
Abstract [en]

The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed energy management—will deliver the breakthrough to these challenges. Thus, this paper aims to critically review urban energy systems at the cluster level that incorporate building integrated RES solutions. We begin with defining cluster approach and the associated boundaries. Several factors influencing energy planning at cluster scale are identified, while the most important ones are discussed in detail. The closely reviewed factors include RES envelope solutions, solar energy potential, density of buildings, energy demand, integrated cluster-scale energy systems and energy hub. The examined categories of RES envelope solutions are (i) the solar power, (ii) the solar thermal and (iii) the energy-efficient ones, out of which solar energy is the most prevalent RES. As a result, methods assessing the solar energy potentials of building envelopes are reviewed in detail. Building density and the associated energy use are also identified as key factors since they affect the type and the energy harvesting potentials of RES envelopes. Modelling techniques for building energy demand at cluster level and their coupling with complex integrated energy systems or an energy hub are reviewed in a comprehensive way. In addition, the paper discusses control and operational methods as well as related optimization algorithms for the energy hub concept. Based on the findings of the review, we put forward a matrix of recommendations for cluster-level energy system simulations aiming to maximize the direct and indirect benefits of RES envelope solutions. By reviewing key factors and modelling approaches for characterizing RES-envelope-solutions-based urban energy systems at cluster level, this paper hopes to foster the transition towards more sustainable urban energy systems.

Keywords
Building cluster, Energy hub, Energy system, Modelling, Optimization, RES
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-28479 (URN)10.1016/j.apenergy.2018.09.041 (DOI)000448226600077 ()2-s2.0-85053078388 (Scopus ID)
Available from: 2018-09-11 Created: 2018-09-11 Last updated: 2018-11-08Bibliographically approved
Xiao, M., Tang, L., Zhang, X., Lun, I. Y. & Yuan, Y. (2018). A Review on Recent Development of Cooling Technologies for Concentrated Photovoltaics (CPV) Systems. Energies, 11(12), Article ID 3416.
Open this publication in new window or tab >>A Review on Recent Development of Cooling Technologies for Concentrated Photovoltaics (CPV) Systems
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2018 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 11, no 12, article id 3416Article in journal (Refereed) Published
Abstract [en]

Concentrated Photovoltaics (CPV) technology, as an energy saving method which can directly generate electricity from the Sun, has attracted an ever-increasing attention with the deepening worldwide energy crisis. However, operating temperature is one of the main concerns that affect the CPV system. Excess cell temperature causes electrical conversion efficiency loss and cell lifespan decrease. Thus, reasonable cooling methods should decrease the operating temperature and balance the flare inhomogeneity. They also need to display high reliability, low power consumption, and convenient installation. This paper presented the architectural, commercial, and industrial usage of CPV system, reviewed the recent research developments of different cooling techniques of CPV systems during last few years, including the spectral beam splitting technology, cogeneration power technology, commonly used and promising cooling techniques, active and passive cooling methods. It also analysed the design considerations of the cooling methods in CPV systems, introduced the classification and basic working principles and provided a thorough compilation of different cooling techniques with their advantages, current research limitations, challenges, and possible further research directions. The aim of this work is to find the research gap and recommend feasible research direction of cooling technologies for CPV systems. 

Place, publisher, year, edition, pages
MDPI, 2018
Keywords
Active cooling technologies, Cell temperature, Concentrated photovoltaics system, Efficiency, Passive cooling technologies
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-29019 (URN)10.3390/en11123416 (DOI)000455358300177 ()2-s2.0-85059253186 (Scopus ID)
Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-02-01Bibliographically approved
Pan, S., Xiong, Y., Han, Y., Zhang, X., Xia, L., Wei, S., . . . Han, M. (2018). A study on influential factors of occupant window-opening behavior in an office building in China. Building and Environment, 133, 41-50
Open this publication in new window or tab >>A study on influential factors of occupant window-opening behavior in an office building in China
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2018 (English)In: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 133, p. 41-50Article in journal (Refereed) Published
Abstract [en]

Occupants often perform many types of behavior in buildings to adjust the indoor thermal environment. In these types, opening/closing the windows, often regarded as window-opening behavior, is more commonly observed because of its convenience. It not only improves indoor air quality to satisfy occupants' requirement for indoor thermal comfort but also influences building energy consumption. To learn more about potential factors having effects on occupants' window-opening behavior, a field study was carried out in an office building within a university in Beijing. Window state (open/closed) for a total of 5 windows in 5 offices on the second floor in 285 days (9.5 months) were recorded daily. Potential factors, categorized as environmental and non-environmental ones, were subsequently identified with their impact on window-opening behavior through logistic regression and Pearson correlation approaches. The analytical results show that occupants' window-opening behavior is more strongly correlated to environmental factors, such as indoor and outdoor air temperatures, wind speed, relative humidity, outdoor FM2.5 concentrations, solar radiation, sunshine hours, in which air temperatures dominate the influence. While the non-environmental factors, i.e. seasonal change, time of day and personal preference, also affects the patterns of window-opening probability. This paper provides solid field data on occupant window opening behavior in China, with high resolutions and demonstrates the way in analyzing and predicting the probability of window-opening behavior. Its discussion into the potential impact factors shall be useful for further investigation of the relationship between building energy consumption and window-opening behavior.

Keywords
Window-opening behavior; Influential factors; Window state; Office building
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-27168 (URN)10.1016/j.buildenv.2018.02.008 (DOI)000429631100005 ()
Available from: 2018-02-08 Created: 2018-02-08 Last updated: 2018-04-26Bibliographically approved
Pan, S., Pei, F., Wang, H., Liu, J., Wei, Y., Zhang, X., . . . Gu, Y. (2018). Design and experimental study of a novel air conditioning system using evaporative condenser at a subway station in Beijing, China. Sustainable cities and society, 43, 550-562
Open this publication in new window or tab >>Design and experimental study of a novel air conditioning system using evaporative condenser at a subway station in Beijing, China
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2018 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 43, p. 550-562Article in journal (Refereed) Published
Abstract [en]

Air conditioning system (AC) contributes significantly to the energy consumption of underground metros. In China, most metro stations are designed with water-cooling centralized air conditioning (WC-AC) system, it has been found that several serious problems are brought by this conventional system, such as large space occupying, water leaking, cooling tower noise and low system efficiency. In order to solve these problems, a novel energy-efficient AC system incorporating an independent evaporative condenser (EC) has been proposed and installed at Futong metro station in Beijing, China. A series of pilot measurements were conducted to analyze the cooling performance and energy consumption of this novel EC-AC system. During the testing period, the average refrigeration efficiency of COP, SCOP and ACOP in A and B side is up to 3.8/3.9, 3.4/3.4 and 2.5/2.3. At the same time, some operation problems such as unbalanced working condition have been identified during measurement. The research indicates that such EC-AC system could be a feasible solution to enhance the energy efficiency and reduce the operational costs and carbon emission in metro stations.

Keywords
Air conditioning, Performance Evaluation, Energy Conservation, Evaporative condenser, Metro station
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-28491 (URN)10.1016/j.scs.2018.09.013 (DOI)000448613300048 ()2-s2.0-85054301839 (Scopus ID)
Available from: 2018-09-20 Created: 2018-09-20 Last updated: 2018-11-22Bibliographically approved
Hu, J., Chen, W., Yin, Y., Li, Y., Yang, D., Wang, H. & Zhang, X. (2018). Electrical-thermal-mechanical properties of multifunctional OPV-ETFE foils for transparent membrane buildings. Polymer testing, 66, 394-402
Open this publication in new window or tab >>Electrical-thermal-mechanical properties of multifunctional OPV-ETFE foils for transparent membrane buildings
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2018 (English)In: Polymer testing, ISSN 0142-9418, E-ISSN 1873-2348, Vol. 66, p. 394-402Article in journal (Refereed) Published
Abstract [en]

ETFE (ethylene tetrafluoroethylene) foils integrated organic photovoltaic cells (OPV) have attracted considerable attention in recent years due to the achievement of sustainability. As building materials, multifunctional OPV-ETFE foils could produce electricity, store thermal energy and possess structural capability. In this case, electrical, thermal and mechanical properties coexist and influence each other due to photovoltaic/thermal effects. Understanding the fundamental mechanism is significant to analyze and design corresponding structures. This paper concerns coupled properties of OPV-ETFE specimens with controlled experiments. One-parameter and two-parameter analysis of two typical specimens are performed to investigate essential properties. Experimental observations show that within normal working conditions, electrical properties are relatively independent but that thermal-mechanical properties are related to each other. Yield stress, yield strain and elastic modulus are calculated from stress-strain curves; these mechanical properties are comparable with those of original ETFE foils at the same temperature. It is concluded from temperature-stress curves that yield point has a critical effect on temperature-stress correlation and that mechanical properties of double OPV specimens are better than those of single OPV specimens. Generally, these mechanical properties could provide basic insights into evaluation of energetic performance and structural behavior of transparent membrane buildings.

Keywords
ETFE foil; Large-span membrane structures; Building integrated photovoltaics; Electrical properties; Mechanical properties; Organic photovoltaic cells; Sustainable buildings; Thermal properties
National Category
Energy Engineering
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-27080 (URN)10.1016/j.polymertesting.2018.01.036 (DOI)000428824000046 ()
Available from: 2018-02-04 Created: 2018-02-04 Last updated: 2018-04-24Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2369-0169

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