Dynamic thermal simulation of advanced natural ventilation in buildings : current and future usage, UK exemplar

This paper evaluates the use of advanced natural ventilation (ANV) strategies in a range of climatic conditions from four cities in the UK. A prototype ANV system was proposed to determine the most effective case in mitigating overheating. The case was then assessed under identical simulation conditions for all four ANV strategies. The overheating criteria used in the research include the single temperature criterion from CIBSE Guide A and the adaptive thermal comfort overheating criteria from BS EN 15251. Both the current and future ‘Design Summer Year (DSY)’ weather data were used to examine the thermal performances of the proposed design. The findings show that shading, night cooling and heavy weight structures (ceiling) were all useful in mitigating overheating, with night cooling being identified as the most effective measure. The work assessed the use of ANV in both current and future scenarios to quantify the limits of outdoor environmental conditions under which natural ventilation is an effective strategy for achieving thermal comfort. The adaptive thermal comfort overheating criteria were proved to be easier to meet compared with the CIBSE single temperature criterion. With the adaptive overheating criteria, the given design is predicted to not overheat until 2050 in London Heathrow; and for other places evaluated in the UK (Edinburgh, Manchester & Birmingham), the design passes these criteria. The Centre-in ANV strategies proved to be more effective than the Edge-in strategies for space cooling due to the extended structure thermal mass

London's urban heat island: Impact on current and future energy consumption in office buildings

This article is available open access and shared under a Creative Commons license: (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2011 Elsevier B.V.This paper presents the results of a computational study on the energy consumption and related CO2 emissions for heating and cooling of an office building within the Urban Heat Island of London, currently and in the future. The study developed twenty weather files in an East-West axis through London; the weather files were constructed according to future climate change scenario for 2050 suitable for the UK which have been modified to represent specific locations within the London UHI based on measurements and predictions from a program developed for this purpose (LSSAT). The study simulated an office with typical construction, heat gains and operational patterns with an advanced thermal simulation program (IESVE). The predictions confirm that heating load decreases, cooling load and overheating hours increase as the office location moves from rural to urban sites and from present to future years. It is shown that internal heat gains are an important factor affecting energy performance and that night cooling using natural ventilation will have a beneficial effect at rural and city locations. As overheating will increase in the future, more buildings will use cooling; it is shown that this might lead to a five-fold increase of CO2 emission for city centre offices in London in 2050. The paper presents detailed results of the typical office placed on the East-West axis of the city, arguing the necessity to consider using weather files based on climate projections and urbanheat island for the design of currentbuildings to safeguard their efficiency in the future.EPSR

Thermal responses of single zone offices on existing near-extreme summer weather data

There have been a number of attempts in the past to define “near extreme” weather for facilitating overheating analysis in free running buildings. The most recently efforts include CIBSE latest release of Design Summer Year (DSY) weather using multiple complete weather years and a newly proposed composite DSY. This research aims to assess how various single zone offices respond to these new definitions of near extreme weathers. Parametric studies were carried out on single zone offices through which four sampling sets of models were employed to examine the thermal responses of dry bulb temperature, global solar radiation & wind speed collectively. London weather data from 1976 to 1995 were used and the overheating assessments were made based on CIBSE Guide A & BS EN 15251. The research discovers that solar radiation and wind both influence the predicted indoor warmth with solar radiation has obvious stronger impacts than wind. No perfect correlation was found from observation and Spearman’s rank order analysis on the ranks between the weather warmth and the predicted indoor warmth. The ranks made using multiple weather parameters show better correlation than some of the dry bulb temperature only metrics. The research also discovers that the Test Reference Year weather behaves warmer than expected. It is also found that a single complete year can not represent the near-extreme consistently and there is no evidence a composite DSY is better statistically. These findings support the notion of using multiple complete warm weather years for overheating assessments

Building dynamic thermal model calibration using the Energy House facility at Salford

Thermal modelling tools have widely been used in the construction industry at the design stage, either for new build or retrofitting existing buildings, providing data for informed decision-making. The accuracy of thermal models has been subject of much research in recent decades due to the potential large difference between predicted and ‘in-use’ performance – the so called ‘performance gap’. A number of studies suggested that better representation of building physics and operation details in thermal models can improve the accuracy of predictions. However, full-scale model calibration has always been challenging as it is difficult to measure all the necessary boundary conditions in an open environment. Thus, the Energy House facility at the University of Salford – a full-sized end terrace house constructed within an environmental chamber – presents a unique opportunity to conduct full-scale model calibration. The aim of this research is to calibrate Energy House thermal models using various full-scale measurements. The measurements used in this research include the co-heating tests for a whole house retrofit case study, and thermal resistance from window coverings and heating controls with thermostatic radiator valves (TRVs). Thermal models were created using an IESVE (Integrated Environment Solutions Virtual Environment). IESVE is a well-established dynamic thermal simulation tool widely used in analysing the dynamic response of a building based on the hourly input of weather data. The evidence from this study suggests that thermal models using measured U-values and infiltration rates do perform better than the models using calculated thermal properties and assumed infiltration rates. The research suggests that better representations of building physics help thermal models reduce the performance gap. However, discrepancies still exist due to various other underlying uncertainties which need to be considered individually with each case. In relative terms, i.e., variations in percentage, the predictions from thermal models tend to be more reliable than predicting the absolute numbers

Indoor Air Quality (IAQ) in Naturally-ventilated Primary Schools in the UK:Occupant-Related Factors

Indoor Air Quality (IAQ) is affected by Context, Occupant and Building (COB) related factors. This paper evaluates IAQ as a function of occupant-related factors including occupants' Adaptive Behaviours (ABs), occupancy patterns, occupant's CO2 generation rates and occupancy density. This study observed occupant-related factors of 805 children in 29 naturally-ventilated (NV) classrooms in UK primary schools during Non-Heating and Heating seasons. Occupant-related factors affecting IAQ include occupants' adaptive behaviours, occupancy patterns, occupants' CO2 generation rate and occupancy densities. Results of this study suggest that a classroom with high potentials for natural ventilation does not necessarily provide adequate IAQ, however, occupants’ good practice of ABs is also required. Average occupancy densities to have CO2 levels of 1000 ± 50 ppm are suggested to be 2.3 ± 0.05m2/p and 7.6 ± 0.25 m3/p. These values correspond to the classroom area of 62.1 ± 1.35 m2 and volume of 205.2 ± 6.75 m3 with a height of 3.3 m. Mean CO2 level is maintained below 900 ppm when all occupant-related factors are in the favour of IAQ, however, it exceeds 1300 ppm when none of the occupant-related factors are in favour of IAQ. It is shown that 17% of CO2 variations are explained by open area (m2), 14% by occupants' generation rates (cm3/s) and 11% by occupancy density (m3/p). IAQ is mostly affected by occupants’ adaptive behaviours than other occupant-related factors in naturally-ventilated classrooms

Investigation into air distribution systems and thermal environment control in chilled food processing facilities

Air flow distribution in chilled food facilities plays a critical role not only in maintaining the required food products temperature but also because of its impact on the facility energy consumption and CO2 emissions. This paper presents an investigation of the thermal environment in existing food manufacturing facilities, with different air distribution systems including supply/return diffusers and fabric ducts, by means of both in-situ measurements and 3D CFD simulations. Measurements and CFD simulations showed that the fabric duct provides a better environment in the processing area in terms of even and low air flow if compared to that with the diffusers. Moreover, temperature stratification was identified as a key factor to be improved to reduce the energy use for the space cooling. Further modelling proved that air temperature stratification improves by relocating the fabric ducts at a medium level. This resulted in a temperature gradient increase up to 4.1 °C in the unoccupied zone

Generating design reference years from the UKCP09 projections and their application to future air-conditioning loads

A method is developed to generate future design reference year (DRY) data from the United Kingdom Climate Impact Programme's 2009 (UKCP09) climate change projections for a variety of future time horizons and carbon emission assumptions. The method selects three near-extreme summer months and three near-extreme winter months and weaves them into an existing test reference year (TRY). Risk levels associated with the 85th percentile (broadly equivalent to existing Chartered Institution of Building Services Engineers [CIBSE] design summer years) of the cumulative distribution function of dry-bulb temperature and, for comparison, the 99th percentile are used. A comparison is made with DRYs generated using alternative methods from other research groups. The data are applied to future air-conditioning (cooling) loads analysis for a wide range of non-domestic case study building types. Simulations using a control DRY set applied to these buildings are used to develop a simplified regression-based calculation method for predicting future air-conditioning loads. The simplified model is shown to be applicable to future weather data without loss of accuracy, which makes it possible to carry out large numbers of future cooling loads predictions without the need to perform extensive and complex energy simulations. Practical applications: It is becoming increasingly necessary to design energy and comfort services for buildings with a whole-life perspective. To assist with this, the CIBSE future weather years can be used for building simulations through to the 2080s. In June 2009, the UK’s Department of the Environment, Food and Rural Affairs (Defra) with the support of the United Kingdom Climate Impacts Programme (UKCIP) published updated climate change projections using a probabilistic method. In future, the responsibility will rest with designers to select design data from a large number of probabilistic outcomes. This work develops a technique to select design weather data called a DRY at two alternative risk levels for use in building simulations through to the 2080s. A simplified method is also proposed to allow practitioners to generate large numbers of probabilistic design cooling loads without the need to perform extensive simulations