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\n  \n 2023\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n The challenges of using live-streamed data in a predictive digital twin.\n \n \n \n \n\n\n \n Ward, R., Choudary, R., Jans-Singh, M., Roumpani, F., Lazauskas, T., Yong, M., Barlow, N., & Hauru, M.\n\n\n \n\n\n\n Journal of Building Performance Simulation, 0(0): 1-22. 2023.\n \n\n\n\n
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@article{doi:10.1080/19401493.2023.2187463,\nauthor = {Ward, Rebecca and Choudary, Ruchi and Jans-Singh, Melanie and Roumpani, Flora and Lazauskas, Tomas and Yong, May and Barlow, Nicholas and Hauru, Markus},\ntitle = {The challenges of using live-streamed data in a predictive digital twin},\njournal = {Journal of Building Performance Simulation},\nvolume = {0},\nnumber = {0},\npages = {1-22},\nyear  = {2023},\npublisher = {Taylor & Francis},\ndoi = {10.1080/19401493.2023.2187463},\nURL = {https://doi.org/10.1080/19401493.2023.2187463}\n}\n
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\n \n\n \n \n \n \n \n \n A study on the transferability of computational models of building electricity load patterns across climatic zones.\n \n \n \n \n\n\n \n Ward, R., Wong, C. S. Y., Chong, A., Choudhary, R., & Ramasamy, S.\n\n\n \n\n\n\n Energy and Buildings, 237: 110826. 2021.\n \n\n\n\n
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@article{ward_transferability_2021,\ntitle = {A study on the transferability of computational models of building electricity load patterns across climatic zones},\njournal = {Energy and Buildings},\nvolume = {237},\npages = {110826},\nyear = {2021},\nissn = {0378-7788},\ndoi = {https://doi.org/10.1016/j.enbuild.2021.110826},\nurl = {https://www.sciencedirect.com/science/article/pii/S0378778821001109},\nauthor = {Rebecca Ward and Cheryl Sze Yin Wong and Adrian Chong and Ruchi Choudhary and Savitha Ramasamy},\nkeywords = {Electricity demand, Plug loads, Stochastic model, Machine learning, Transferability, Autoencoder (AE), Functional Data Analysis (FDA)},\nabstract = {Significant reduction in energy demand from non-domestic buildings is required if greenhouse emission reduction targets are to be met worldwide. Increasing monitoring of electricity consumption generates a real opportunity for gaining an in-depth understanding of the nature of occupant-related internal loads and the connection between activity and demand. The stochastic nature of the demand is well-known but as yet there is no accepted methodology for generating stochastic loads for building energy simulation. This paper presents evidence that it is feasible to generate stochastic models of activity-related electricity demand based on monitored data. Two machine learning approaches are used to develop stochastic models of plug loads; an autoencoder (AE) and a Functional Data Analysis (FDA) model. Using data from two office buildings located in different countries, the transferability of models is explored by training the models on data from one building and using the trained models to predict demand for the other building. The results show that both models predict plug loads satisfactorily, with a good agreement with the mean demand and quantification of the uncertainty.}\n}\n\n
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\n Significant reduction in energy demand from non-domestic buildings is required if greenhouse emission reduction targets are to be met worldwide. Increasing monitoring of electricity consumption generates a real opportunity for gaining an in-depth understanding of the nature of occupant-related internal loads and the connection between activity and demand. The stochastic nature of the demand is well-known but as yet there is no accepted methodology for generating stochastic loads for building energy simulation. This paper presents evidence that it is feasible to generate stochastic models of activity-related electricity demand based on monitored data. Two machine learning approaches are used to develop stochastic models of plug loads; an autoencoder (AE) and a Functional Data Analysis (FDA) model. Using data from two office buildings located in different countries, the transferability of models is explored by training the models on data from one building and using the trained models to predict demand for the other building. The results show that both models predict plug loads satisfactorily, with a good agreement with the mean demand and quantification of the uncertainty.\n
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\n \n\n \n \n \n \n \n A tool for generation of stochastic occupant-based internal loads using a functional data analysis approach to re-define ‘activity’.\n \n \n \n\n\n \n Ward, R. M., & Choudhary, R.\n\n\n \n\n\n\n Journal of Building Performance Simulation, 14(3): 303-327. 2021.\n \n\n\n\n
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@article{ward_activity_2021,\nauthor = {R. M. Ward and R. Choudhary},\ntitle = {A tool for generation of stochastic occupant-based internal loads using a functional data analysis approach to re-define ‘activity’},\njournal = {Journal of Building Performance Simulation},\nvolume = {14},\nnumber = {3},\npages = {303-327},\nyear  = {2021},\npublisher = {Taylor & Francis},\ndoi = {10.1080/19401493.2021.1919209},\n}\n\n
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\n \n\n \n \n \n \n \n Continuous calibration of a digital twin: Comparison of particle filter and Bayesian calibration approaches.\n \n \n \n\n\n \n Ward, R., Choudhary, R., Gregory, A., Jans-Singh, M., & Girolami, M.\n\n\n \n\n\n\n Data-Centric Engineering, 2: e15. 2021.\n \n\n\n\n
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@article{ward_calibration_2021,\ntitle={Continuous calibration of a digital twin: Comparison of particle filter and Bayesian calibration approaches}, \nvolume={2}, \nDOI={10.1017/dce.2021.12}, \njournal={Data-Centric Engineering}, \npublisher={Cambridge University Press}, \nauthor={Ward, Rebecca and Choudhary, Ruchi and Gregory, Alastair and Jans-Singh, Melanie and Girolami, Mark}, \nyear={2021}, \npages={e15},\n}\n\n
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\n \n\n \n \n \n \n \n \n Co-simulating a greenhouse in a building to quantify co-benefits of different coupled configurations.\n \n \n \n \n\n\n \n Jans-Singh, M., Ward, R., & Choudhary, R.\n\n\n \n\n\n\n Journal of Building Performance Simulation, 14(3): 247-276. 2021.\n \n\n\n\n
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@article{doi:10.1080/19401493.2021.1908426,\nauthor = {Melanie Jans-Singh and Rebecca Ward and Ruchi Choudhary},\ntitle = {Co-simulating a greenhouse in a building to quantify co-benefits of different coupled configurations},\njournal = {Journal of Building Performance Simulation},\nvolume = {14},\nnumber = {3},\npages = {247-276},\nyear  = {2021},\npublisher = {Taylor & Francis},\ndoi = {10.1080/19401493.2021.1908426},\n\nURL = { \n        https://doi.org/10.1080/19401493.2021.1908426\n    \n},\neprint = { \n        https://doi.org/10.1080/19401493.2021.1908426\n    \n}\n\n}\n\n\n
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\n \n\n \n \n \n \n \n A data-centric stochastic model for simulation of occupant-related energy demand in buildings.\n \n \n \n\n\n \n Ward, R. M.\n\n\n \n\n\n\n Ph.D. Thesis, University of Cambridge, 2021.\n \n\n\n\n
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@phdthesis{ward_phdthesis_2021,\nauthor = {R. M. Ward},\ntitle = {A data-centric stochastic model for simulation of occupant-related energy demand in buildings},\nschool = {University of Cambridge},\nyear  = {2021},\ndoi = {10.17863/CAM.75927},\n}\n
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\n \n\n \n \n \n \n \n Re-defining 'activity' in buildings to reflect stochastic energy demand: a functional data analysis approach.\n \n \n \n\n\n \n Ward, R., & Choudhary, R.\n\n\n \n\n\n\n In Building Simulation and Optimisation 2020, 2020. \n \n\n\n\n
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@inproceedings{ward_activity_2020,\n\ttitle = {Re-defining 'activity' in buildings to reflect stochastic energy demand: a functional data analysis approach},\n\tbooktitle = {Building {Simulation} and {Optimisation} 2020},\n\tauthor = {Ward, Rebecca and Choudhary, Ruchi },\n\tyear = {2020},\n}\n\n
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\n \n\n \n \n \n \n \n \n A data-centric bottom-up model for generation of stochastic internal load profiles based on space-use type.\n \n \n \n \n\n\n \n Ward, R. M., Choudhary, R., Heo, Y., & Aston, J. A. D.\n\n\n \n\n\n\n Journal of Building Performance Simulation, 12(5): 620-636. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{doi:10.1080/19401493.2019.1583287,\nauthor = {R. M. Ward and R. Choudhary and Y. Heo and J. A. D. Aston},\ntitle = {A data-centric bottom-up model for generation of stochastic internal load profiles based on space-use type},\njournal = {Journal of Building Performance Simulation},\nvolume = {12},\nnumber = {5},\npages = {620-636},\nyear  = {2019},\npublisher = {Taylor &amp; Francis},\ndoi = {10.1080/19401493.2019.1583287},\n\nURL = { \n        https://doi.org/10.1080/19401493.2019.1583287\n    \n},\neprint = { \n        https://doi.org/10.1080/19401493.2019.1583287\n    \n}\n\n}\n\n
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\n \n\n \n \n \n \n \n A structured stochastic model for specification of occupant related end-use energy demands in building energy simulation.\n \n \n \n\n\n \n Ward, R., Choudhary, R., & Aston, J.\n\n\n \n\n\n\n In Technical Symposium, 2019. CIBSE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{ward_cibsets_2019,\n\ttitle = {A structured stochastic model for specification of occupant related end-use energy demands in building energy simulation},\n\tauthor = {Ward, Rebecca and Choudhary, Ruchi and Aston, John},\n\tyear = {2019},\n\tpublisher = {{CIBSE}},\n\tbooktitle = {{Technical Symposium}},\n\tlocation = {Sheffield, UK}\n}\n\n
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\n \n\n \n \n \n \n \n A stochastic data-centric model for quantification of end-use energy demand in buildings.\n \n \n \n\n\n \n Ward, R., Choudhary, R., & Aston, J.\n\n\n \n\n\n\n In Building Simulation and Optimisation 2018, 2018. \n \n\n\n\n
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@inproceedings{ward_end-use_2018,\n\ttitle = {A stochastic data-centric model for quantification of end-use energy demand in buildings},\n\tbooktitle = {Building {Simulation} and {Optimisation} 2018},\n\tauthor = {Ward, Rebecca and Choudhary, Ruchi and Aston, John},\n\tyear = {2018},\n}\n\n
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\n \n\n \n \n \n \n \n A functional principal components model for internal loads in building energy simulation.\n \n \n \n\n\n \n Ward, R. M., Choudhary, R., Heo, Y., & Aston, J. A.\n\n\n \n\n\n\n In Building Simulation 2017, August 2017. International Building Performance Simulation Association\n \n\n\n\n
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@inproceedings{ward_functional_2017,\n\ttitle = {A functional principal components model for internal loads in building energy simulation},\n\tabstract = {There is currently no established methodology for quantifying uncertainty in occupant-related building internal loads. In this paper, we propose that distinct spaces within a building may be assigned an opera- tional signature comprising the daily base load, load range and diversity profile. A Functional Data Anal- ysis (FDA) approach has been used to analyse moni- tored electricity consumption data for the derivation of such signatures. This approach enables simula- tion of the inherent stochasticity. It represents a step forward towards an ability to propagate uncertainty through a building energy simulation and to quantify the change in electricity consumption associated with a change in building operation.},\n\tbooktitle = {Building {Simulation} 2017},\n\tpublisher = {International Building Performance Simulation Association},\n\tauthor = {Ward, Rebecca Mary and Choudhary, Ruchi and Heo, Yeonsook and Aston, John AD},\n\tmonth = aug,\n\tyear = {2017},\n\tfile = {BS2017_032.pdf:/Users/Bex/Zotero/storage/XMGIY7KD/BS2017_032.pdf:application/pdf}\n}\n\n
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\n There is currently no established methodology for quantifying uncertainty in occupant-related building internal loads. In this paper, we propose that distinct spaces within a building may be assigned an opera- tional signature comprising the daily base load, load range and diversity profile. A Functional Data Anal- ysis (FDA) approach has been used to analyse moni- tored electricity consumption data for the derivation of such signatures. This approach enables simula- tion of the inherent stochasticity. It represents a step forward towards an ability to propagate uncertainty through a building energy simulation and to quantify the change in electricity consumption associated with a change in building operation.\n
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\n \n\n \n \n \n \n \n \n Exploring the impact of different parameterisations of occupant-related internal loads in building energy simulation.\n \n \n \n \n\n\n \n Ward, R. M., Choudhary, R., Heo, Y., & Rysanek, A.\n\n\n \n\n\n\n Energy and Buildings , 123: 92 - 105. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ExploringPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Ward201692,\ntitle = "Exploring the impact of different parameterisations of occupant-related internal loads in building energy simulation",\njournal = "Energy and Buildings ",\nvolume = "123",\nnumber = "",\npages = "92 - 105",\nyear = "2016",\nnote = "",\nissn = "0378-7788",\ndoi = "http://dx.doi.org/10.1016/j.enbuild.2016.04.050",\nurl = "http://www.sciencedirect.com/science/article/pii/S037877881630305X",\nauthor = "Rebecca Mary Ward and Ruchi Choudhary and Yeonsook Heo and Adam Rysanek",\nkeywords = "Building energy simulation",\nkeywords = "Occupancy-related internal loads",\nkeywords = "Electricity consumption",\nkeywords = "Plug loads",\nkeywords = "Uncertainty quantification",\nkeywords = "Non-domestic buildings",\nkeywords = "Stochastic analysis ",\nabstract = "A building energy simulation relies on accurate parameterisation of occupant-related internal loads to simulate a realistic energy balance within a building. The internal loads are inextricably linked to occupant behaviour, both directly through the contribution of occupant heat output to thermal energy balance and indirectly via the interactions between occupants, appliances and building services. While occupancy itself is difficult to measure directly, most buildings possess a wealth of data in the form of monitored electricity consumption in varying degrees of resolution. These data, particularly plug loads, may be used to inform the model of occupant-related internal loads. Different approaches to parameterisation of plug loads have been investigated, with the purpose of exploring the conditions that might lead to preference of one approach over another. The models have been tested through a case study and simulation results have been compared against a range of response variables. Conclusions have been drawn as to the most important features of plug load parameterisation for a model to be used for forecasting future demand.",\nproject={b-bem}\n}\n\n
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\n A building energy simulation relies on accurate parameterisation of occupant-related internal loads to simulate a realistic energy balance within a building. The internal loads are inextricably linked to occupant behaviour, both directly through the contribution of occupant heat output to thermal energy balance and indirectly via the interactions between occupants, appliances and building services. While occupancy itself is difficult to measure directly, most buildings possess a wealth of data in the form of monitored electricity consumption in varying degrees of resolution. These data, particularly plug loads, may be used to inform the model of occupant-related internal loads. Different approaches to parameterisation of plug loads have been investigated, with the purpose of exploring the conditions that might lead to preference of one approach over another. The models have been tested through a case study and simulation results have been compared against a range of response variables. Conclusions have been drawn as to the most important features of plug load parameterisation for a model to be used for forecasting future demand.\n
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\n \n\n \n \n \n \n \n Data-driven bottom-up approach for modelling internal loads in building energy simulation using functional principal components.\n \n \n \n\n\n \n Ward, R., Choudhary, R., Heo, Y., & Guillas, S.\n\n\n \n\n\n\n 09 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@conference{Ward2016Data-drivenbottom-up,\nauthor = {Rebecca Ward and Ruchi Choudhary and Yeonsook Heo and Serge Guillas},\nbooktitle = {Building Simulation and Optimisation 2016},\naddress = {Newcastle},\ntitle = {Data-driven bottom-up approach for modelling internal loads in building energy simulation using functional principal components},\nyear = {2016},\nmonth = {09},\nabstract = {Internal loads in a building are difficult to quantify efficiently in a way which envelopes existing demand yet permits estimation of the impact of changes in building operation. The standard characterisation by energy-use intensity and diversity profile is well established; while quantification of energy-use intensity is achievable using monitored data, there is no standard approach for quantification of diversity profiles. This paper investigates an efficient method for the representation of the shape of the diversity profile using a functional data analysis approach together with electricity consumption data monitored at a spatial resolution that permits correlation of consumption with space use type. The approach has been applied to a case study building and has been shown to give a good agreement with monitored electricity consumption data.\n},\nproject = {b-bem}\n}\n\n\n
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\n Internal loads in a building are difficult to quantify efficiently in a way which envelopes existing demand yet permits estimation of the impact of changes in building operation. The standard characterisation by energy-use intensity and diversity profile is well established; while quantification of energy-use intensity is achievable using monitored data, there is no standard approach for quantification of diversity profiles. This paper investigates an efficient method for the representation of the shape of the diversity profile using a functional data analysis approach together with electricity consumption data monitored at a spatial resolution that permits correlation of consumption with space use type. The approach has been applied to a case study building and has been shown to give a good agreement with monitored electricity consumption data. \n
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\n \n\n \n \n \n \n \n \n Parameterisation of internal loads in assessment of building energy performance.\n \n \n \n \n\n\n \n Ward, R. M., Choudhary, R., Heo, Y., & Rysanek, A.\n\n\n \n\n\n\n In 14th International Conference of IBPSA, Building Simulation 2015, pages 2881–2888, Hyderabad, 2015. IBPSA\n \n\n\n\n
\n\n\n\n \n \n \"ParameterisationPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{ward_parameterisation_2015,\n\taddress = {Hyderabad},\n\ttitle = {Parameterisation of internal loads in assessment of building energy performance},\n\turl = {http://www.bs2015.in/files/BS2015_Proceeding.pdf},\n\tabstract = {In a computational building energy model internal loads are characterized by user-defined peak values, multiplied by diversity factors that simulate the typical daily change in use. For an existing building, while a detailed energy audit may be undertaken, attaining accurate internal load profiles for every space of the building can be prohibitive. In reality, the variation of internal loads over time is inherently stochastic. In order to develop a stochastic model of building operations, a number of studies have proposed parameterisations that incorporate some estimation of variability, with different assumptions and levels of complexity. This paper aims to examine potential models and thereby identify possible parameterisations for a stochastic model of internal loads in a building with quantification of uncertainties in inputs.},\n\tbooktitle = {14th {International} {Conference} of {IBPSA}, {Building} {Simulation} 2015},\n\tpublisher = {IBPSA},\n\tauthor = {Rebecca Mary Ward and Ruchi Choudhary and Yeonsook Heo and Adam Rysanek},\n\tyear = {2015},\n\tpages = {2881--2888},\nproject={b-bem}\n}\n\n
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\n In a computational building energy model internal loads are characterized by user-defined peak values, multiplied by diversity factors that simulate the typical daily change in use. For an existing building, while a detailed energy audit may be undertaken, attaining accurate internal load profiles for every space of the building can be prohibitive. In reality, the variation of internal loads over time is inherently stochastic. In order to develop a stochastic model of building operations, a number of studies have proposed parameterisations that incorporate some estimation of variability, with different assumptions and levels of complexity. This paper aims to examine potential models and thereby identify possible parameterisations for a stochastic model of internal loads in a building with quantification of uncertainties in inputs.\n
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\n \n\n \n \n \n \n \n Simulation of plants in buildings; incorporating plant-air interactions in building energy simulation.\n \n \n \n\n\n \n Ward, R. M., Choudhary, R., Cundy, C., Johnson, G., & McRobie, A.\n\n\n \n\n\n\n 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@conference{Ward2015Simulationof,\nauthor = {Rebecca Mary Ward and Ruchi Choudhary and Christopher Cundy and George Johnson and Allan McRobie},\nbooktitle = {Building Simulation 2015, 14th IBPSA },\naddress = {Hyderabad, India},\ntitle = {Simulation of plants in buildings; incorporating plant-air interactions in building energy simulation},\nyear = {2015},\nabstract = {The energy consumption of buildings within which vegetation growth forms a significant function cannot at present be adequately simulated using typical building energy simulation analysis packages as they do not include the ability to simulate the potentially significant heat and mass transfer between plants and the internal air. On the other hand, tools developed for the simulation of climate-controlled greenhouses do not allow multi-zone energy simulation of standard buildings. Within this paper, a model developed for simulating plant growth and crop development within a commercial greenhouse and the corresponding heat, mass and CO2 exchanges is described. A TRNSYS component to facilitate simulation of a building-integrated greenhouse in an urban environment is outlined and a case study of a simple composite office/greenhouse building is presented as a preliminary illustrative example.},\nproject = {b-bem}\n}\n\n\n
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\n The energy consumption of buildings within which vegetation growth forms a significant function cannot at present be adequately simulated using typical building energy simulation analysis packages as they do not include the ability to simulate the potentially significant heat and mass transfer between plants and the internal air. On the other hand, tools developed for the simulation of climate-controlled greenhouses do not allow multi-zone energy simulation of standard buildings. Within this paper, a model developed for simulating plant growth and crop development within a commercial greenhouse and the corresponding heat, mass and CO2 exchanges is described. A TRNSYS component to facilitate simulation of a building-integrated greenhouse in an urban environment is outlined and a case study of a simple composite office/greenhouse building is presented as a preliminary illustrative example.\n
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\n \n\n \n \n \n \n \n Simulation of plants in buildings; incorporating plant-air interactions in building energy simulation.\n \n \n \n\n\n \n Ward, R., Choudhary, R., Cundy, C., Johnson, G., & McRobie, A.\n\n\n \n\n\n\n 12 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@conference{Ward2015Simulationof,\nauthor = {Rebecca Ward and Ruchi Choudhary and Christopher Cundy and George Johnson and Allan McRobie},\nbooktitle = {Building Simulation 2015},\naddress = {Hyderabad},\ntitle = {Simulation of plants in buildings; incorporating plant-air interactions in building energy simulation},\nyear = {2015},\nmonth = {12},\nabstract = {The energy consumption of buildings within which vegetation growth forms a significant function cannot at present be adequately simulated using typical building energy simulation analysis packages as they do not include the ability to simulate the potentially significant heat and mass transfer between plants and the internal air. On the other hand, tools developed for the simulation of climate-controlled greenhouses do not allow multi-zone energy simulation of standard buildings. Within this paper, a model developed for simulating plant growth and crop development within a commercial greenhouse and the corresponding heat, mass and CO2 exchanges is described. A TRNSYS component to facilitate simulation of a building-integrated greenhouse in an urban environment is outlined and a case study of a simple composite office/greenhouse building is presented as a preliminary illustrative ex- ample.},\nproject = {GES}\n}\n\n\n
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\n The energy consumption of buildings within which vegetation growth forms a significant function cannot at present be adequately simulated using typical building energy simulation analysis packages as they do not include the ability to simulate the potentially significant heat and mass transfer between plants and the internal air. On the other hand, tools developed for the simulation of climate-controlled greenhouses do not allow multi-zone energy simulation of standard buildings. Within this paper, a model developed for simulating plant growth and crop development within a commercial greenhouse and the corresponding heat, mass and CO2 exchanges is described. A TRNSYS component to facilitate simulation of a building-integrated greenhouse in an urban environment is outlined and a case study of a simple composite office/greenhouse building is presented as a preliminary illustrative ex- ample.\n
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\n  \n 2013\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Analysis and optimisation of retrofit energy supply strategy across a diverse urban building portfolio.\n \n \n \n\n\n \n Ward, R. M., Mortada, A., Omu, K., Rysanek, A. M., Rainsford, C., & Choudhary, R.\n\n\n \n\n\n\n In Building Simulation 2013, pages 1256–1263, 2013. http://www.ibpsa.org\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{ward2013analysis,\n  title={Analysis and optimisation of retrofit energy supply strategy across a diverse urban building portfolio},\n  author={Rebecca Mary Ward and Adnan Mortada and Keno Omu and Adam Martin Rysanek and Clare Rainsford and Ruchi Choudhary},\n  booktitle={Building Simulation 2013},\n  pages={1256--1263},\n  year={2013},\n  organization={http://www.ibpsa.org}\n,\nabstract = { This paper presents a study in support of decision making for building retrofit and energy supply strategy at the Royal Botanic Gardens, Kew in southwest London, England. The study considers the issues that affect simulation at the building scale specific to this site, in particular simulation of heat flow in botanical glasshouses, retrofit of heritage structures and simulation of power load for buildings with high equipment density. In addition, the study considers the potential benefits to be gained from energy microgeneration and supply at the district scale, investigating supply optimisation for a cluster of buildings within the Kew site. }\n\n}\n\n\n
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\n This paper presents a study in support of decision making for building retrofit and energy supply strategy at the Royal Botanic Gardens, Kew in southwest London, England. The study considers the issues that affect simulation at the building scale specific to this site, in particular simulation of heat flow in botanical glasshouses, retrofit of heritage structures and simulation of power load for buildings with high equipment density. In addition, the study considers the potential benefits to be gained from energy microgeneration and supply at the district scale, investigating supply optimisation for a cluster of buildings within the Kew site. \n
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\n \n\n \n \n \n \n \n Simulation of thermal performance and retrofit of a historic greenhouse.\n \n \n \n\n\n \n Ward, R. M., Mortada, A., & Choudhary, R.\n\n\n \n\n\n\n CONTRIBUTIONS TO BUILDING PHYSICS,245–252. 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{ward2013simulation,\n  title={Simulation of thermal performance and retrofit of a historic greenhouse},\n  author={Rebecca Mary Ward and Adnan Mortada and Ruchi Choudhary},\n  journal={CONTRIBUTIONS TO BUILDING PHYSICS},\n  pages={245--252},\n  year={2013}\n,\n    abstract = { Typical building energy simulation programs do not adequately describe the physical processes of heat and mass transfer which occur in a greenhouse, primarily because they do not include the interaction of the plants with their environment. This is of concern when simulation studies are required in order to assess different options for improving the greenhouse thermal performance. A previous paper (Brown et al 2012) has described the development of a model for simulation of ornamental glasshouses. Further development, in order to represent more accurately the physical processes and assess their significance, is described in this paper. The development has been undertaken in support of retrofit analysis for the glasshouses at the Royal Botanic Gardens, Kew, in London, which present unique challenges in terms of their historic nature, construction details and design and have provided an opportunity to investigate the relative importance of different physical effects on the energy consumption. Within this context, the simulation has been used to explore options for improving greenhouse thermal performance. },\nproject={GES}\n}\n\n\n
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\n Typical building energy simulation programs do not adequately describe the physical processes of heat and mass transfer which occur in a greenhouse, primarily because they do not include the interaction of the plants with their environment. This is of concern when simulation studies are required in order to assess different options for improving the greenhouse thermal performance. A previous paper (Brown et al 2012) has described the development of a model for simulation of ornamental glasshouses. Further development, in order to represent more accurately the physical processes and assess their significance, is described in this paper. The development has been undertaken in support of retrofit analysis for the glasshouses at the Royal Botanic Gardens, Kew, in London, which present unique challenges in terms of their historic nature, construction details and design and have provided an opportunity to investigate the relative importance of different physical effects on the energy consumption. Within this context, the simulation has been used to explore options for improving greenhouse thermal performance. \n
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\n \n\n \n \n \n \n \n \n A Bottom-up Energy Analysis across a Diverse Urban Building Portfolio: Retrofits for the Buildings at the Royal Botanic Gardens, Kew, UK.\n \n \n \n \n\n\n \n Ward, R. M., & Choudhary, R.\n\n\n \n\n\n\n Building and Environment. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{ward_bottom-up_2013,\n\ttitle = {A {Bottom}-up {Energy} {Analysis} across a {Diverse} {Urban} {Building} {Portfolio}: {Retrofits} for the {Buildings} at the {Royal} {Botanic} {Gardens}, {Kew}, {UK}},\n\tissn = {0360-1323},\n\tshorttitle = {A {Bottom}-up {Energy} {Analysis} across a {Diverse} {Urban} {Building} {Portfolio}},\n\turl = {http://www.sciencedirect.com/science/article/pii/S0360132313003740},\n\tdoi = {10.1016/j.buildenv.2013.12.018},\n\tabstract = {A methodology for the analysis of building energy retrofits has been developed for a diverse set of buildings at the Royal Botanic Gardens (RBG), Kew in southwest London, UK. The methodology requires selection of appropriate building simulation tools dependent on the nature of the principal energy demand. This has involved the development of a stand-alone model to simulate the heat flow in botanical glasshouses, as well as stochastic simulation of electricity demand for buildings with high equipment density and occupancy-led operation. Application of the methodology to the buildings at RBG Kew illustrates the potential reduction in energy consumption at the building scale achievable from the application of retrofit measures deemed appropriate for heritage buildings and the potential benefit to be gained from onsite generation and supply of energy.},\n\turldate = {2014-01-10TZ},\n\tjournal = {Building and Environment},\n\tyear={2013},\n\tauthor = {Rebecca Mary Ward and Ruchi Choudhary},\n\tkeywords = {district energy optimization, greenhouse simulation, retrofit analysis of buildings, stochastic electricity demand},\nproject={GES}\n}\n\n
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\n A methodology for the analysis of building energy retrofits has been developed for a diverse set of buildings at the Royal Botanic Gardens (RBG), Kew in southwest London, UK. The methodology requires selection of appropriate building simulation tools dependent on the nature of the principal energy demand. This has involved the development of a stand-alone model to simulate the heat flow in botanical glasshouses, as well as stochastic simulation of electricity demand for buildings with high equipment density and occupancy-led operation. Application of the methodology to the buildings at RBG Kew illustrates the potential reduction in energy consumption at the building scale achievable from the application of retrofit measures deemed appropriate for heritage buildings and the potential benefit to be gained from onsite generation and supply of energy.\n
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