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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
Abstract [en]

Demand response control is one of the common means used for building peak demand limiting. Most of the existing demand response controls focused on single building’s performance optimization, and thus may cause new undesirable peak demands at building group, imposing stress on the grid power balance and limiting the economic savings. A few latest studies have demonstrated the potential benefits of demand response coordination, but the proposed methods cannot be applied in large scales. The main reason is that, for demand response coordination of multiple buildings, associated computational load and coordination complexity, increasing exponentially with building number, are challenges to be solved. This study, therefore, proposes a hierarchical demand response control to optimize operations of a large scale of buildings for group-level peak demand reduction. The hierarchical control first considers the building group as a ‘virtual’ building and searches the optimal performance that can be achieved at building group using genetic algorithm. To realize such optimal performance, it then coordinates each single building’s operation using non-linear programming. For validations, the proposed method has been applied on a case building group, and the study results show that the hierarchical control can overcome the challenges of excessive computational load and complexity. Moreover, in comparison with conventional independent control, it can achieve better performances in aspects of peak demand reduction and economic savings. This study provides a coordinated control for application in large scales, which can improve the effectiveness and efficiency in relieving the grid stress, and reduce the end-users’ electricity bills.

Keywords
Peak demand limiting, Demand response, Building group coordination, Economic cost, Grid interaction
National Category
Energy Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-29729 (URN)10.1016/j.apenergy.2019.03.148 (DOI)000470045800054 ()2-s2.0-85063025035 (Scopus ID)
Available from: 2019-03-20 Created: 2019-03-20 Last updated: 2019-07-22Bibliographically approved
Li, G., Tang, L., Zhang, X. & Dong, J. (2019). A review of factors affecting the efficiency of clean-in-place procedures in closed processing systems. Energy, 178, 57-71
Open this publication in new window or tab >>A review of factors affecting the efficiency of clean-in-place procedures in closed processing systems
2019 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 178, p. 57-71Article in journal (Refereed) Published
Abstract [en]

This paper reviews the current state of researches on improvement of Clean-In-Place (CIP) procedures in closed processing system thus saving energy, with a special attention paid to the hydrodynamic effects of cleaning fluid and the numerical and experimental approaches to investigate the identified controlling factors. The paper discussed the fouling problems of processing plants and the importance of sufficient CIP procedures, the forces contributing to cleaning with a special focus on the hydrodynamic effects. In general, it is possible to enhance hydrodynamic removal forces by local introduction of, among others, high wall shear stress and fluctuation rate of wall shear stress without consuming more energy. A theoretical model of particle removal in flow was also reviewed which supports the factors identified. The paper therefore further reviewed and compared the current state of modelling and experimental techniques on CIP improvement. To simulation the CIP process, it is necessary to consider 3D time-resolved Large Eddy Simulation with a Hybrid RANS-LES WMLES as Sub-Grid-Scale model because it captures both the mean and fluctuation rate of flow variables, while affordable for industrial flows. The wall shear stress measurement techniques and cleanablity test methods were also discussed and suggested.

Keywords
Clean-in-place, Efficiency, Hydraulic factors, Wall shear stress, CFD
National Category
Environmental Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-30009 (URN)10.1016/j.energy.2019.04.123 (DOI)000472686300005 ()2-s2.0-85065074591 (Scopus ID)
Available from: 2019-05-10 Created: 2019-05-10 Last updated: 2019-07-22Bibliographically approved
Han, M., May, R., Zhang, X., Wang, X., Pan, S., Yan, D., . . . Xu, L. (2019). A review of reinforcement learning methodologies for controlling occupant comfort in buildings. Sustainable cities and society
Open this publication in new window or tab >>A review of reinforcement learning methodologies for controlling occupant comfort in buildings
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2019 (English)In: Sustainable cities and society, ISSN 2210-6707Article in journal, News item (Refereed) In press
National Category
Building Technologies
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-30601 (URN)
Available from: 2019-08-08 Created: 2019-08-08 Last updated: 2019-08-08Bibliographically 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
Zhang, X., Xiao, M., He, W., Qiu, Z. & Zhao, X. (2019). Heat Pump Technologies and Their Applications in Solar Systems. In: Xudong Zhao, Xiaoli Ma (Ed.), Advanced Energy Efficiency Technologies for Solar Heating, Cooling and Power Generation: (pp. 311-339). Springer
Open this publication in new window or tab >>Heat Pump Technologies and Their Applications in Solar Systems
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2019 (English)In: Advanced Energy Efficiency Technologies for Solar Heating, Cooling and Power Generation / [ed] Xudong Zhao, Xiaoli Ma, Springer, 2019, p. 311-339Chapter in book (Refereed)
Abstract [en]

As the well known that global energy demand is on a trend of continuous growth, reducing energy demand and making good use of renewable energy are thought to be the major routes toward low carbon and sustainable future, in particular for the building sector. Compared to traditional gas-fired heating systems, heat pumps have been proved to be an energy-efficient heating technology which can save fossil fuel energy and consequently reduce CO2 emission. However, the most outstanding challenges for the application of heat pumps lie in their high demand for electrical power, and the insufficient heat transfer between the heat source and the refrigerant. To overcome these difficulties, a solar-assisted heat pump has been proposed to tackle these challenges. A solar-assisted heat pump combines a heat pump with a solar collector, enabling the use of solar energy to provide space heating and hot water for buildings. This chapter introduces heat pump technologies and their applications in solar systems. Two types of solar-assisted heat pump, direct and indirect expansion, are illustrated in details. This work has provided the fundamental research and experience for developing a solar heat pump system and contributing to a significant fossil fuel saving and carbon reduction in the global extent.

Place, publisher, year, edition, pages
Springer, 2019
Series
Green Energy and Technology
Keywords
Heat pump, PV, Loop heat pipe, Micro-channels-evaporator, Performance
National Category
Energy Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-30577 (URN)10.1007/978-3-030-17283-1_9 (DOI)2-s2.0-85068761593 (Scopus ID)978-3-030-17282-4 (ISBN)978-3-030-17283-1 (ISBN)
Available from: 2019-07-24 Created: 2019-07-24 Last updated: 2019-07-24Bibliographically approved
Petrovic, B., Myhren, J. A., Zhang, X., Wallhagen, M. & Eriksson, O. (2019). Life cycle assessment of a wooden single-family house in Sweden. Applied Energy, 251, 113-253, Article ID 113253.
Open this publication in new window or tab >>Life cycle assessment of a wooden single-family house in Sweden
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2019 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 251, p. 113-253, article id 113253Article in journal (Refereed) Published
Abstract [en]

To understand the reasons behind the large environmental impact from buildings the whole life cycle needs to be considered. Therefore, this study evaluates the carbon dioxide emissions in all stages of a single-family house in Sweden from the production of building materials, followed by construction and user stages until the end-of-life of the building in a life cycle assessment (LCA). The methodology applied is attributional life cycle assessment (LCA) based on ‘One Click LCA’ tool and a calculated life span of 100 years. Global warming potential (GWP) and primary energy (PE) are calculated by using specific data from the case study, furthermore the data regarding building materials are based on Environmental Product Declarations (EPDs). The results show that the selection of wood-based materials has a significantly lower impact on the carbon dioxide emissions in comparison with non-wood based materials. The total emissions for this single-family house in Sweden are 6 kg CO 2 e/m 2 /year. The production stage of building materials, including building systems and installations represent 30% of the total carbon dioxide equivalent emissions, while the maintenance and replacement part represents 37%. However, energy use during the in-use stage of the house recorded lower environmental impact (21%) due to the Swedish electricity mix that is mostly based on energy sources with low carbon dioxide emissions. The water consumption, construction and the end-of-life stages have shown minor contribution to the buildings total greenhouse gas (GHG) emissions (12%). The primary energy indicator shows the largest share in the operational phase of the house.

Keywords
Carbon dioxide equivalent emission, Environmental product declaration, Global warming potential, Life cycle assessment, Primary energy, Single-family house
National Category
Energy Systems
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-30118 (URN)10.1016/j.apenergy.2019.05.056 (DOI)2-s2.0-85065788114 (Scopus ID)
Available from: 2019-05-31 Created: 2019-05-31 Last updated: 2019-06-03Bibliographically approved
Petrovic, B., Myhren, J. A., Zhang, X., Wallhagen, M. & Eriksson, O. (2019). Life cycle assessment of building materials for a single-family house in Sweden. Paper presented at 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China. Energy Procedia, 158, 3547-3552
Open this publication in new window or tab >>Life cycle assessment of building materials for a single-family house in Sweden
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2019 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 158, p. 3547-3552Article in journal (Refereed) Published
Abstract [en]

The Nordic countries have shown great interest in using Life Cycle Assessment (LCA) in the building sector compared to the past years. Sweden has set up an objective to be carbon neutral (no greenhouse gas emissions to the atmosphere) by 2045. This paper presents a case study of a single-family house “Dalarnas Villa” in the region Dalarna, Sweden within a 100-year perspective. The assessment is implemented using a new software based on hard data agreed by Environmental Product Declarations (EPDs). It focuses on building materials, transport distances of the materials, and replacement of essential construction materials. The LCA in this study demonstrates the environmental impact related to building materials from production and construction phase including transport, replacement and deconstruction phase. The study does not cover energy use and water consumption. The results show that the building slab made by concrete is the part of the construction most contributing to CO2e, while the wood frame and cellulose insulation have low environmental impact. Replacement of materials takes nearly half of total environmental impact over 100 years. Having a large share of wood-based products, make greenhouse gas emissions remains low.

Keywords
carbon dioxide equivalent (CO2e; global warming potential (GWP); life cycle assessment (LCA); One Click LCA
National Category
Civil Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-29913 (URN)10.1016/j.egypro.2019.01.913 (DOI)000471031703144 ()2-s2.0-85063874633 (Scopus ID)
Conference
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-07-04Bibliographically approved
Zhang, N., Chen, X., Su, Y., Zheng, H., Ramandan, O., Zhang, X., . . . Riffat, S. (2019). Numerical investigations and performance comparisons of a novel cross-flow hollow fiber integrated liquid desiccant dehumidification system. Energy, 182, 1115-1131
Open this publication in new window or tab >>Numerical investigations and performance comparisons of a novel cross-flow hollow fiber integrated liquid desiccant dehumidification system
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2019 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 182, p. 1115-1131Article in journal (Refereed) Published
Abstract [en]

The heat and mass transfer process of a novel cross-flow hollow fiber integrated liquid desiccant dehumidification system is analysed numerically. Compared with other porous media or packing towers in dehumidification applications, hollow fibre membranes have significant advantages including low weight, corrosion resistant and no liquid droplet carryover. A novel air-KCOOH cross-flow dehumidification system was designed and manufactured, with 5500 hollow fibres formed into a circular module. The variations of the dehumidification effectiveness and moisture removal rates were studied numerically and validated against experimental results under the incoming air mass flow rates of 0.08-0.26kg/s and relative humidity from 55% to 75%. The dehumidification performance comparisons for the proposed system using CaCl2, LiCl and KCOOH as the desiccants have been conducted as well. The results demonstrated that under the same m*(ratio between solution mass flow rate to the air mass flow rate), the proposed system using 62% KCOOH could achieve approximately the same latent effectiveness compared with 40% CaCl2 and 32% LiCl, with the at least 3.1% sensible effectiveness increased by. Therefore, it could be concluded that the proposed system using KCOOH as desiccant could be more applicable for dehumidification purpose compared with other systems using conventional liquid desiccants.

Keywords
heat and mass transfer, dehumidification, liquid desiccant, hollow fiber, potassium formate
National Category
Energy Systems
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-30136 (URN)10.1016/j.energy.2019.06.036 (DOI)2-s2.0-85067675978 (Scopus ID)
Available from: 2019-06-06 Created: 2019-06-06 Last updated: 2019-07-08Bibliographically approved
Lei, S., Shi, Y., Yan, Y. & Zhang, X. (2019). Numerical study on inertial effects on liquid-vapor flow using lattice Boltzmann method. Paper presented at 2nd International Conference on Energy and Power, ICEP2018, 13–15 December 2018, Sydney, Australia. Energy Procedia, 160, 428-435
Open this publication in new window or tab >>Numerical study on inertial effects on liquid-vapor flow using lattice Boltzmann method
2019 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 160, p. 428-435Article in journal (Refereed) Published
Abstract [en]

Liquid-vapor flow in porous media is studied in this article. To fulfill this goal, a double-distribution-function lattice Boltzmann (LB) model is proposed based on the separate-phase governing equations at the representative elementary volume (REV) scale. Importantly, besides the Darcy force and capillary force, which were commonly included in previous studies, the LB model in this article also considers the inertial force characterized by the Forchheimer term. This feature enables the model to offer an effective description of liquid-vapor flow in porous media at low, intermediate and even high flow rates. We validated the LB model by simulating a single-phase flow in porous media driven by a pressure difference and found its results are in good agreement with the available analytical solutions. We then applied the model to study water-vapor flow in a semi-infinite porous region bounded by an impermeable and heated wall. The numerical simulation reveals the flow and mass transfer characteristics under the compounding effects of inertial, Darcy and capillary forces. Through a comparison with the results given by the generalized Darcy's law, our numerical results directly evidence that the inertial force is a dominating factor when a fluid passes through porous media at an intermediate or high flow rate.

Keywords
Inertial effects, Lattice Botlzmann method, Liquid-vapor flow, Porous media
National Category
Civil Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-29914 (URN)10.1016/j.egypro.2019.02.177 (DOI)000471294000056 ()2-s2.0-85063774363 (Scopus ID)
Conference
2nd International Conference on Energy and Power, ICEP2018, 13–15 December 2018, Sydney, Australia
Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-06-27Bibliographically 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
Abstract [en]

Occupancy behaviour plays an important role in energy consumption in buildings. Currently, the shallow understanding of occupancy has led to a considerable performance gap between predicted and measured energy use. This paper presents an approach to estimate the occupancy based on blind system identification (BSI), and a prediction model of electricity consumption by an air-conditioning system is developed and reported based on an artificial neural network with the BSI estimation of the number of occupants as an input. This starts from the identification of indoor CO2 dynamics derived from the mass-conservation law and venting levels. The unknown parameters, including the occupancy and model parameters, are estimated by using a frequentist maximum-likelihood algorithm and Bayesian estimation. The second phase is to establish the prediction model of the electricity consumption of the air-conditioning system by using a feed-forward neural network (FFNN) and extreme learning machine (ELM), as well as ensemble models. To analyse some aspects of the benchmark test for identifying the effect of structure parameters and input-selection alternatives, three studies are conducted on (1) the effect of predictor selection based on principal component analysis, (2) the effect of the estimated occupancy as the supplementary input, and (3) the effect of the neural network ensemble. The result shows that the occupancy number, as the input, is able to improve the accuracy in predicting energy consumption using a neural network model.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Occupancy estimation; Blind system identification (BSI); Prediction model for energy consumption; Feedforward neural network; Extreme learning machine
National Category
Energy Engineering
Research subject
Energy and Built Environments
Identifiers
urn:nbn:se:du-29562 (URN)10.1016/j.apenergy.2019.02.056 (DOI)000468714300020 ()
Available from: 2019-02-24 Created: 2019-02-24 Last updated: 2019-06-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2369-0169

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