مدل نمونه اولیه ساختمان های اداری انگلستان به عنوان رویکرد روش شناختی در توسعه مدل های رگرسیون برای پیش بینی مصرف انرژی ساختمان از تقاضاهای گرمایش و سرمایش
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6346||2013||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy and Buildings, Volume 60, May 2013, Pages 152–162
An archetypal simulation model of office building representing variability in UK office building stock by parameterising built form, construction elements, occupancy/usage and operational/control strategy has been developed thus enabling detailed energy performance simulation to be used for stock modelling and parametric studies. The paper discusses the building characteristics needed to be considered for energy performance simulation, their values, and how they can be used in parametric studies. These parameters include built forms, fabrics (including thermal mass and insulation positioning), glazing percentages and characteristics, daylight and solar control measures and activity and operational related parameters (heating and cooling set points, ventilation rate, occupancy density and metabolic rate, equipment and lighting gain). The default parameter values suggested for the archetypal simulation model reflect typical existing and currently proposed UK office building stock. An archetypal model, combined with parametric studies, can be used in assessing energy performance of building stock and evaluating adaptation/retrofitting strategies.
Energy efficiency of built environment in urban areas is an important factor in mitigating the challenges of climate change, resource depletion and wider environmental issues. In the UK, buildings account for about half of all energy consumption, compared to 41% in Europe and 36% in the USA . Compared to dwellings, non-domestic buildings tend to have higher energy consumption per square meter of floor area. Offices and retail spaces are amongst the most energy intensive typologies in the non-domestic building sector. They alone account for over 50% of total energy consumption for non-domestic buildings . According to Perez-Lombard et al.  it is advisable to start the analysis of energy demand of the non-domestic building stock with office buildings. The reason is not only the energy intensity of the office buildings but their constant increase in total floor area coupled with increase in lighting, IT and air conditioning. The other important reason is that office buildings are quite uniformly distributed across the buildings stocks in developed countries with three key energy end uses, HVAC, lighting and appliances, adding up together to around 85%. In order to develop general understanding of energy issues, and to provide evidence for policy makers in regards to energy consumption reduction, it is often necessary to consider a specific non-domestic typology as whole. For the example of office buildings, a conventional approach is to select/develop a typical or exemplar office building whose energy performance can be analysed in detail and subsequently generalized to similar buildings. This approach has been used by Jenkins et al.  and  to investigate the refurbishment options aiming at 50% reduction in CO2 emission inside the UK office building stock. The investigation was based on an example building which represents ∼20% of the UK office building stock in terms of built from, and 9% of the UK office building stock in terms of construction age. Similarly, Dascalaki and Santamouris  classified European office buildings into five typical types, each located in a different, typical climatic zones in the OFFICE project which investigated passive and active CO2 emission reduction measures.
نتیجه گیری انگلیسی
8. Conclusion This paper presents parameterized archetypal simulation models for the UK office building stock. An archetypal simulation model is an abstract model that generalizes the characteristics of a particular building type, and represents variability in building stock by parameterising construction elements, components, design features, occupancy and activities. By enabling detailed energy performance simulation for stock modelling and parametric studies, this approach enables comprehensive analysis of energy performance of specific non-domestic typologies (e.g. office buildings). Possible applications of archetypal models include: - developing design guidelines of a particular building type, - analysing energy performance and carbon emission issues across the sector, - optimising design or retrofitting strategies for a building stock, - investigating effect or impact of (climate, occupant behaviour, …) changes on the existing building stock, - rapid modelling of individual buildings. We started with a comprehensive literature survey on the parameters influencing buildings’ energy performance. The parameters included office building built forms, construction of building envelope, size and construction of fenestration areas, daylight and solar control measures, indoor environment parameters, occupancy, and activity-related parameters. We identified main parameters (see Fig. 10) from this study; the ranges of parameter values that are applicable to the UK office building stock have also been established. The archetypal simulation model built forms correspond to 67% of the UK total non-domestic building floor area. The default U-values correspond to UK office buildings built in the period after Second World War until present days, thus covering around 75% of the UK office building stock. The archetypal simulation model activity and operational related parameters are based on the UK standards and internationally accepted best practices. Using only the defined default values of the parameters it is possible to create 3840 diverse yet typical office buildings. We will report an application of such archetypal models for investigation energy performance of various HVAC systems in a separate paper. To take this work further, a thorough sensitivity analysis should be carried out, therefore quantifies the relative importance of the parameters.