Simple future weather files for estimating heating and cooling demand

Cox, Rimante Andrasiunaite; Drews, Martin; Rode, Carsten; Nielsen, Susanne Balslev

doi:10.1016/j.buildenv.2014.04.006

Cited by 63 publications

(33 citation statements)

References 18 publications

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“…For example, an R 2 value for the relationship between CDH23.3 and the cooling energy consumption in Seoul was 0.96 (F (1,22) = 475, p < 0.01). Previous studies [31,32] on the impacts of climate change on building energy consumption have mainly focused on the use of cooling degree days. The application of cooling degree-hours adopted herein may be further used for extreme weather situations in different parts of the world.…”

Section: Discussionmentioning

confidence: 99%

Cooling Energy Implications of Occupant Factor in Buildings under Climate Change

Lim

Yun

2017

Sustainability

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Occupant factor is a critical element in the overall energy consumption of buildings. This study aims to reveal how occupant factors influence the energy consumption of example buildings in Seoul, Tokyo, and Hong Kong under climate change projections, and to prioritize factors with energy saving potential for buildings in consideration of future climate change. The study finds that the cooling degree-hours base of 23.3 • C in the three cities sharply increases with future climate change by analyzing future hourly weather data produced herein. Simulations are made with EnergyPlus Runtime Language (Erl) for modeling occupant behavior. The simulation results reveal that a dynamic thermostat control based on an adaptive comfort model is an effective method to reduce cooling energy consumption under future climate change, reducing cooling energy consumption by up to 18% in some instances. In particular, we reveal that a combined application of the adaptive comfort control, nighttime ventilation, and the use of occupancy-based lighting and equipment result in reducing cooling energy consumption by 28%. The outcomes of this study are potentially useful in providing cost-effective solutions to adapt buildings for future climate change with simple modifications to occupant behavior. Also, the roles of renewable energy are briefly discussed.

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Section: Discussionmentioning

confidence: 99%

Cooling Energy Implications of Occupant Factor in Buildings under Climate Change

Lim

Yun

2017

Sustainability

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“…This is a problem, as summers such as 2003 which resulted in so many deaths across Europe are not ranked highly in the base dataset when considering average summertime temperature. Various attempts have been made to address such concerns, largely by creating new reference years based on warmer periods or on predictions of climate change (see, for example: [18][19][20][21][22][23]). …”

Section: Accepted Manuscriptmentioning

confidence: 99%

Probabilistic adaptive thermal comfort for resilient design

Coley

Herrera

Fosas

et al. 2017

Building and Environment

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Adaptive thermal comfort theory has become the bedrock of much thinking about how to judge if a free-running environment is suitable for human occupation. In design work, the conditions predicted by a thermal model, when the model is presented with one possible annual weather time series (a reference year), are compared to the limits of human comfort. If the temperatures are within the comfort limits, the building is judged to be suitable. However, the weather in many locations can vary year-on-year by a considerable margin, and this begs the question, how robust are the predictions of adaptive comfort theory likely to be over the many years a building might be in use? We answer this question using weather data recorded for up to 30 years for locations within each of the five major Köppen climate classifications.We find that the variation in the annual time series is so great that the predicted comfort temperature frequently lies outside the acceptable range given by the reference year. Return periods for the excursions of the time series are calculated for each location. The results for one location are then validated using the world's longest temperature record. These results suggest that industry and academia would be best advised to move to a probabilistic methodology, like the proposed one, when using adaptive comfort theory to judge the likely conditions within a building. Extra pertinence is provided by concerns over increases in mortality and morbidity in buildings due to a rapidly warming climate. • A new probabilistic adaptive comfort theory introduced.• New comfort equations for resilient building design presented.

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“…Thresholds were selected based on information from actual GSHP applications and the technical and scientific literature [37,38].…”

Section: Resultsmentioning

confidence: 99%

Suitability Evaluation of Specific Shallow Geothermal Technologies Using a GIS-Based Multi Criteria Decision Analysis Implementing the Analytic Hierarchic Process

et al. 2018

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Abstract:The exploitation potential of shallow geothermal energy is usually defined in terms of site-specific ground thermal characteristics. While true, this assumption limits the complexity of the analysis, since feasibility studies involve many other components that must be taken into account when calculating the effective market viability of a geothermal technology or the economic value of a shallow geothermal project. In addition, the results of a feasibility study are not simply the sum of the various factors since some components may be conflicting while others will be of a qualitative nature only. Different approaches are therefore needed to evaluate the suitability of an area for shallow geothermal installation. This paper introduces a new GIS platform-based multicriteria decision analysis method aimed at comparing as many different shallow geothermal relevant factors as possible. Using the Analytic Hierarchic Process Tool, a geolocalized Suitability Index was obtained for a specific technological case: the integrated technologies developed within the GEOTeCH Project. A suitability map for the technologies in question was drawn up for Europe.

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Simple future weather files for estimating heating and cooling demand

Cited by 63 publications

References 18 publications

Cooling Energy Implications of Occupant Factor in Buildings under Climate Change

Cooling Energy Implications of Occupant Factor in Buildings under Climate Change

Probabilistic adaptive thermal comfort for resilient design

Suitability Evaluation of Specific Shallow Geothermal Technologies Using a GIS-Based Multi Criteria Decision Analysis Implementing the Analytic Hierarchic Process

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