The CIBS example weather year

Hitchin, E. R.; Holmes, Marlin; Hutt, B. C.; Irving, Shane; Nevrala, D.

doi:10.1177/014362448300400306

Cited by 20 publications

(11 citation statements)

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“…9 In the UK, hourly weather data series for a full year were first introduced in the early 1980s in the format of the Example Weather Year (EWY). 1,13 The EWY files were generated using a method proposed by Holmes and Hitchin in 1978, 14 where a whole meteorological year starting on the 1st of October, i.e. the beginning of the heating season, is selected from a multi-year data set.…”

Section: Introductionmentioning

confidence: 99%

“…The selection procedure is based on the standard deviation of the monthly mean values of a set of climate parameters from their long-term means. 1 However, as discussed previously, 6 the approach of selecting a complete sequence of 12 consecutive months may lead to the selection of a 'best fit' year, even though no year of the underlying [15][16][17][18][19][20] year data set can be considered as being satisfactory 'typical' across all months. Therefore, the method of selecting an entire year has been superseded by approaches that derive a 'representative' weather year from the most 'typical' months in a multi-year data set.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Limitations of the CIBSE design summer year approach for delivering representative near-extreme summer weather conditions

Jentsch

Levermore

Parkinson

et al. 2013

Building Services Engineering Research and Technology

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Representative, site-specific weather data is a key requirement for building performance simulation. In the UK, such data is available in two formats, Test Reference Years for analysing building services loads under 'typical' year conditions and Design Summer Years for estimating summer discomfort of naturally ventilated and free-running buildings. Currently, Design Summer Years are determined as a complete year based on the rank of the average dry bulb temperature from April to September. The simplicity of this approach does not take into account extreme temperature values in individual months or the incident solar radiation, both of which are however of great significance for the summer overheating performance of a building. This paper analyses the implications of this simplified approach for the resulting data. It is shown that there is no consistent relation between the Design Summer Years and the corresponding Test Reference Years and that, for some sites, building performance simulations using Design Summer Year files deliver unreliable results. Practical application: This paper demonstrates that the current approach for deriving Design Summer Years (DSYs) can lead to data series that are not representative for near-extreme summer conditions at a given location. It highlights that a new approach for deriving near-extreme summer years for building performance simulation is needed in order to overcome the inherent shortfalls of the current DSY data.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Limitations of the CIBSE design summer year approach for delivering representative near-extreme summer weather conditions

Jentsch

Levermore

Parkinson

et al. 2013

Building Services Engineering Research and Technology

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“…This was selected to represent the range of weather patterns that would typically be found in a dataset covering the Nottingham weather station over the last 25 years. The basis for developing Example Weather Years was formulated by the Chartered Institution of Building Services Engineers [23]. The intention of using this format was to allow a more practical simulation than using multi-year datasets, and also to create an equitable basis for comparisons of predicted energy consumption in different building designs.…”

Section: Methodsmentioning

confidence: 99%

Minimising Excessive Energy Consumption in Schools While Maintaining Optimal Air Quality

Hallin¹

2017

OJOp

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This paper presents an assessment of how to minimise excessive energy consumption in a case study school classroom while maintaining optimal indoor air quality. Using mixed method research with qualitative interview data supporting quantitative key data measurements, essential primary data was extracted from temperature and carbon dioxide monitoring equipment in the classroom. This was then used, along with other ancillary data, to develop an IES computer model of the classroom as a "base case" reflecting existing energy consumption, temperatures and CO 2 levels. Eight different interventions were then developed and modelled which reflected improved energy supply and a variety of ventilation strategies. The results show that adequate control and design of energy supply systems is critical to minimising excessive energy consumption, and that adequate internal air quality is achievable through a variety of low cost strategies.

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“…The example weather year selection process is based on the objective of choosing a year in which the monthly mean values of a number of pertinent parameters do not differ by more than a specific number of standard deviations from their long-term mean [34]. The pertinent parameters for selection include the mean, maximum and minimum values of dry-bulb temperature, the mean relative humidity, the mean wind speed, as well as the total daily solar radiation and infiltration number.…”

Section: Methodsmentioning

confidence: 99%