Improved methods for evaluating base temperature for use in building energy performance lines

Day, A.R.; Knight, Ian Paul; Dunn, Gavin; Gaddas, R

doi:10.1191/0143624403bt073oa

Cited by 38 publications

(24 citation statements)

References 4 publications

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“…The internal air temperature, (ºC), of a typical unheated English house is, on average, approximately 3ºC higher than ; the difference is attributable to solar and casual heat gains and fabric properties that affect heat transfer and thermal inertia. Therefore, the heating system is assumed to function only when is at least 3ºC below [29][30][31]. Equation (3) is integrated over the entire heating season to estimate the total heat loss, (kWh) via exfiltration.…”

Section: Modelling Infiltration and Exfiltration Heat Lossmentioning

confidence: 99%

Assessing uncertainty in housing stock infiltration rates and associated heat loss: English and UK case studies

Jones

Das

Chalabi

et al. 2015

Building and Environment

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Strategies to reduce domestic heating loads by minimizing the infiltration of cold air through adventitious openings located in the thermal envelopes of houses are highlighted by the building codes of many countries. Consequent reductions of energy demand and CO 2 e emission are often unquantified by empirical evidence. Instead, a mean heating season infiltration rate is commonly inferred from an air leakage rate using a simple ratio scaled to account for the physical and environmental properties of a dwelling. The scaling does not take account of the permeability of party walls in conjoined dwellings and so cannot differentiate between the infiltration of unconditioned ambient air that requires heating, and conditioned air from adjacent dwellings that does not.A stochastic method is presented that applies a theoretical model of adventitious infiltration to predict distributions of mean infiltration rates and the associated total heat loss in any stock of dwellings during heating hours. The method is applied to the English and UK housing stocks and provides probability distribution functions of stock infiltration rates and total heat loss during the heating season for two extremes of party wall permeability. The distributions predict that up to 79% of the current English stock could require additional purpose-provided ventilation to limit negative health consequences. National models predict that fewer dwellings are under-ventilated. The distributions are also used to predict that infiltration is responsible for 3-5% of total UK energy demand, 11-15% of UK housing stock energy demand, and 10-14% of UK housing stock carbon emissions.3 HIGHLIGHTS  Heating season infiltration and heat loss distributions for English housing stock. Up to 79% of English dwellings may be under ventilated. Exfiltration estimated to be responsible for 3-5% of total UK energy demand. Exfiltration estimated to be responsible for 11-15% UK housing stock energy demand. Exfiltration estimated to be responsible for 10-14% UK housing stock CO 2 emissions.

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Section: Modelling Infiltration and Exfiltration Heat Lossmentioning

confidence: 99%

Assessing uncertainty in housing stock infiltration rates and associated heat loss: English and UK case studies

Jones

Das

Chalabi

et al. 2015

Building and Environment

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“…for the particular region [17]. The use of building specific base temperature is, therefore, important for correct energy/degree-days correlations and should take into account the correct (and practical) energy balance of the building [27]. For this reason degree-days are calculated in this research at variable base temperatures ranging from 10°C to 20°C for heating and 10°C to 28°C for cooling degree-days at an interval of 0.5°C.…”

Section: Determining the Base Temperaturementioning

confidence: 99%

“…For this reason degree-days are calculated in this research at variable base temperatures ranging from 10°C to 20°C for heating and 10°C to 28°C for cooling degree-days at an interval of 0.5°C. The determination of building specific base temperature is out of scope of this paper; however, discussions on methods such as the use of building performance lines can be found in [16,27].…”

Section: Determining the Base Temperaturementioning

confidence: 99%

The impact of the projected changes in temperature on heating and cooling requirements in buildings in Dhaka, Bangladesh

Mourshed

2011

Applied Energy

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Dhaka, the capital of Bangladesh, is a fast growing megacity with a population of 12.8 million. Due to its tropical location, dense urban morphology and higher than average density of population, buildings in Dhaka are likely to be adversely affected by the projected changes in climate, in particular by the increases in temperature. Buildings play a vital role in most aspects of our lives and their energy consumption patterns affect climate change mitigation and adaptation strategies. It is important to understand the likely impact of the projected increases in temperature on cooling and heating requirements in buildings in future climates. In this research, global projections on changes in temperature are temporally downscaled using a statistically averaged baseline present-day hourly weather data to generate future weather data in three timeslices: 2020s, 2050s and 2080s. Time series data for the present-day and future climates are analyzed as well as heating and cooling degree-days are calculated. Analysis shows that heating degree-days decrease whereas cooling degree-days continue to increase in future climates. The magnitude of change in monthly cooling degree-days is uneven and is greater in winter months than in summer and monsoon. Increased occurrences of temperatures above comfort threshold throughout the year are likely to have significant consequences for human health and wellbeing. The severity and duration of outdoor temperatures in the form of increased cooling degree-days in future climates will result in a surge in demand for energy for comfort cooling, which will add further stress to the already stressed energy infrastructure in the country. Prompt actions from stakeholders are, therefore, essential to enhance the resilience of Dhaka's buildings to climate change.

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“…It is found that this variance is not always strictly random: it is likely to be caused by many other unmeasured disturbances or, for degree-days, a poor choice of base temperature [4]. Improved methods of modelling this consumption variance will be illustrated, with the purpose of improving Nomenclature B…”

Section: Introductionmentioning

confidence: 99%

Seasonal autoregressive modelling of water and fuel consumptions in buildings

2007

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Improved methods for evaluating base temperature for use in building energy performance lines

Cited by 38 publications

References 4 publications

Assessing uncertainty in housing stock infiltration rates and associated heat loss: English and UK case studies

Assessing uncertainty in housing stock infiltration rates and associated heat loss: English and UK case studies

The impact of the projected changes in temperature on heating and cooling requirements in buildings in Dhaka, Bangladesh

Seasonal autoregressive modelling of water and fuel consumptions in buildings

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