Generating test reference years from the UKCP09 projections and their application in building energy simulations

2011 ◽  
Vol 33 (4) ◽  
pp. 387-406 ◽  
Author(s):  
H Du ◽  
CP Underwood ◽  
JS Edge
Keyword(s):  
Climate Change ◽  
Carbon Emission ◽  
Building Energy ◽  
Weather Data ◽  
Research Groups ◽  
Future Time ◽  
Climate Change Projections ◽  
Time Horizons ◽  
Energy Simulations ◽  
Operative Temperatures

In this study, test reference year (TRY) data for three UK cities are generated from the new UKCP09 climate change projections 1 for a variety of future time horizons and carbon emission scenario assumptions. The data are applied to the energy simulation of three commercial buildings and one house for the three city locations (London, Manchester and Edinburgh), three future time horizons in this century and three carbon emission scenarios. Results are compared with those generated using alternative TRYs from two other research groups who used UKCP09 1 as well as with the existing TRY data sets which form the CIBSE Future Weather Years 2 in order to produce robust results. Results of future simulations of peak summer operative temperatures, peak cooling demand, annual cooling energy, peak heating demand and annual heating energy are presented for the four building case studies benchmarked against control weather data for the period 1960–1989. The results show increasing internal operative temperatures (non-air-conditioned) and increasing air-conditioning demands (air-conditioned) throughout this century and though peak heating demands remain similar to control data, annual heating energy consumptions can be expected to fall sharply. Practical applications: Currently, practitioners can use Test Reference Years for use in building energy simulations. In 2009, the CIBSE released Future Weather Years, which go further by allowing practitioners to explore the thermal and comfort behaviour of buildings at future time horizons thus helping to ‘future proof’ a design. In 2009, the United Kingdom Climate Impacts Programme released a new generation of climate change scenario data (the UKCP09 climate change projections) using probabilistic methods. These are the most comprehensive data yet and provides a greater degree of detail than was available to generate the CIBSE Future Weather Years. It is therefore likely that the new data will gradually become the normal basis for investigating future building thermal and comfort response. In this study, a sample of TRY is generated from the UKCP09 data and applied to the simulation of a sample of ‘real’ buildings. The results are compared with both the existing CIBSE Future Weather Years as well as with Test Reference Years generated using UKCP09 by two other research groups. The results provide a robust way forward for simulating building thermal and comfort response using future weather data.

scholarly journals Linking urban scenarios with energy simulations for dense urban planning under climate change

2021 ◽  
Vol 2042 (1) ◽  
pp. 012054
Author(s):  
J Felkner ◽  
B Marshall ◽  
S Richter ◽  
E Mbata ◽  
S Zigmund ◽  
...  
Keyword(s):  
Climate Change ◽  
Urban Planning ◽  
Energy Demand ◽  
Carbon Emission ◽  
Energy Use ◽  
Climate Change Scenarios ◽  
Climate Change Projections ◽  
Computational Tools ◽  
Energy Simulations ◽  
Scale Design

Abstract This research aims at linking Urban Planning, Energy Simulations and Climate Change projections into the year 2100 for hot climates. The workflow of going back and forth between urban and city scale plans and individual neighborhood parcels to building scale, for the sake of simulating energy demand for a given city into the future is complex. It is prone to rely on many assumptions and simplifications in order to aid the simulations. In this work, we streamline the process with new computational tools, with the goal of communicating a more precise impact of building scale and neighborhood morphological scale design and retrofit strategies in order to meet energy reduction and carbon emission targets focusing on 2030, 2050 and 2100. Urban scenarios are developed using Envision Tomorrow. The building archetypes used therein are associated with energy demand profiles which we simulate using EnergyPlus for various climate change scenarios to improve the forecasting ability of Envision Tomorrow. Denser developments yield far lower neighborhood energy use.

scholarly journals Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4115 ◽  
Author(s):  
Vincenzo Costanzo ◽  
Gianpiero Evola ◽  
Marco Infantone ◽  
Luigi Marletta
Keyword(s):  
Residential Building ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Weather Station ◽  
Simulation Tools ◽  
The Difference ◽  
Energy Simulations

Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.

scholarly journals Influence of the Meteorological Record Length on the Generation of Representative Weather Files

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2103
Author(s):  
Michele Libralato ◽  
Giovanni Murano ◽  
Alessandra De Angelis ◽  
Onorio Saro ◽  
Vincenzo Corrado
Keyword(s):  
Strong Dependence ◽  
Building Energy ◽  
Weather Data ◽  
Air Temperatures ◽  
Change Effect ◽  
Climate Change Effect ◽  
The Common ◽  
Energy Simulations ◽  
Heat And Moisture ◽  
Weather Record

Heat and moisture (HM) transfer simulations of building envelopes and whole building energy simulations require adequate weather files. The common approach is to use weather data of reference years constructed from meteorological records. The weather record affects the capability of representing the real weather of the resulting reference years. In this paper the problem of the influence of the length of the records on the representativeness of the reference years is addressed and its effects are evaluated also for the applicative case of the moisture accumulation risk analysis with the Glaser Method and with DELPHIN 6, confirming that records shorter than 10 years could lead to less representative reference years. On the other hand, it is shown that reference years obtained from longer periods are not representative of the most recent years, which present higher dry-bulb air temperatures due to a short-term climate change effect observed in all the considered weather records. An alternative representative year (Moisture Representative Year) to be used in building energy simulations with a strong dependence on moisture is presented.

scholarly journals Seamless climate change projections and seasonal predictions for bushfires in Australia

2020 ◽  
Vol 70 (1) ◽  
pp. 120
Author(s):  
Andrew J. Dowdy
Keyword(s):  
Climate Change ◽  
Long Range ◽  
Time Scales ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Data Sets ◽  
Fire Weather ◽  
Climate Change Projections ◽  
Different Time Scales

Spatio-temporal variations in fire weather conditions are presented based on various data sets, with consistent approaches applied to help enable seamless services over different time scales. Recent research on this is shown here, covering climate change projections for future years throughout this century, predictions at multi-week to seasonal lead times and historical climate records based on observations. Climate projections are presented based on extreme metrics with results shown for individual seasons. A seasonal prediction system for fire weather conditions is demonstrated here as a new capability development for Australia. To produce a more seamless set of predictions, the data sets are calibrated based on quantile-quantile matching for consistency with observations-based data sets, including to help provide details around extreme values for the model predictions (demonstrating the quantile matching for extremes method). Factors influencing the predictability of conditions are discussed, including pre-existing fuel moisture, large-scale modes of variability, sudden stratospheric warmings and climate trends. The extreme 2019–2020 summer fire season is discussed, with examples provided on how this suite of calibrated fire weather data sets was used, including long-range predictions several months ahead provided to fire agencies. These fire weather data sets are now available in a consistent form covering historical records back to 1950, long-range predictions out to several months ahead and future climate change projections throughout this century. A seamless service across different time scales is intended to enhance long-range planning capabilities and climate adaptation efforts, leading to enhanced resilience and disaster risk reduction in relation to natural hazards.

scholarly journals Evaluation of Multiyear Weather Data Effects on Hygrothermal Building Energy Simulations Using WUFI Plus

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7157
Author(s):  
Michele Libralato ◽  
Alessandra De Angelis ◽  
Giulia Tornello ◽  
Onorio Saro ◽  
Paola D’Agaro ◽  
...  
Keyword(s):  
Building Materials ◽  
Moisture Transfer ◽  
Weather Conditions ◽  
Building Energy ◽  
Building Envelope ◽  
Weather Data ◽  
Building Simulations ◽  
Coupled Heat And Moisture ◽  
Single Number ◽  
Energy Simulations

Transient building energy simulations are powerful design tools that are used for the estimation of HVAC demands and internal hygrothermal conditions of buildings. These calculations are commonly performed using a (often dated) typical meteorological year, generated from past weather measurements excluding extreme weather conditions. In this paper the results of multiyear building simulations performed considering coupled Heat and Moisture Transfer (HMT) in building materials are presented. A simple building is simulated in the city of Udine (Italy) using a weather record of 25 years. Performing a multiyear simulation allows to obtain a distribution of results instead of a single number for each variable. The small therm climate change is shown to influence thermal demands and internal conditions with multiyear effects. From this results it is possible to conclude that weather records used as weather files have to be periodically updated and that moisture transfer is relevant in energy and comfort calculations. Moreover, the simulations are performed using the software WUFI Plus and it is shown that using a thermal model for the building envelope could be a non negligible simplification for the comfort related calculations.

scholarly journals Modelling the Impacts of Climate Change on Building Heating and Cooling Energy Use in Toronto

2021 ◽  
Author(s):  
Pouriya Jafarpur
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Dynamical Downscaling ◽  
Ghg Emissions ◽  
Building Energy ◽  
Weather Data ◽  
Existing Building ◽  
Average Decrease ◽  
The Future

The study describes the results of climate change impact assessment on building energy use in Toronto, Canada. Accordingly, three future weather data sets are generated and applied to the energy simulation of 16 building prototypes. Both statistical and dynamical downscaling techniques are used to generate the future weather files. The results indicate an average decrease for the future in the range of 18-33% in heating EUI, and an average increase of 16-126% in cooling EUI, depending on the baseline climate and building type. In addition, the GHG emissions for each building model are presented. It is concluded that the application of future weather files for building performance simulation leads to a better quantification of building energy demand in the future than a historical weather file. Furthermore, the results demonstrate the need to modify and adapt existing building modelling regulations and to plan future building according to the future climate.

Sign in / Sign up

Export Citation Format

Share Document