A method is developed to generate future design reference year (DRY) data from the United Kingdom Climate Impact Programme's 2009 (UKCP09) climate change projections for a variety of future time horizons and carbon emission assumptions. The method selects three near-extreme summer months and three near-extreme winter months and weaves them into an existing test reference year (TRY). Risk levels associated with the 85th percentile (broadly equivalent to existing Chartered Institution of Building Services Engineers [CIBSE] design summer years) of the cumulative distribution function of dry-bulb temperature and, for comparison, the 99th percentile are used. A comparison is made with DRYs generated using alternative methods from other research groups. The data are applied to future airconditioning (cooling) loads analysis for a wide range of non-domestic case study building types. Simulations using a control DRY set applied to these buildings are used to develop a simplified regression-based calculation method for predicting future air-conditioning loads. The simplified model is shown to be applicable to future weather data without loss of accuracy, which makes it possible to carry out large numbers of future cooling loads predictions without the need to perform extensive and complex energy simulations. Practical applications: It is becoming increasingly necessary to design energy and comfort services for buildings with a whole-life perspective. To assist with this, the CIBSE future weather years can be used for building simulations through to the 2080s. In June 2009, the UK's Department of the Environment, Food and Rural Affairs (Defra) with the support of the United Kingdom Climate Impacts Programme (UKCIP) published updated climate change projections using a probabilistic method. In future, the responsibility will rest with designers to select design data from a large number of probabilistic outcomes. This work develops a technique to select design weather data called a DRY at two alternative risk levels for use in building simulations through to the 2080s. A simplified method is also proposed to allow practitioners to generate large numbers of probabilistic design cooling loads without the need to perform extensive simulations.

Solar energy building applications are attracting increasing attention from researchers, engineers, businessmen and officials due to their significant benefits in sustainable development, such as energy saving, cost reduction and environmental protection. Trombe wall, as a classical passive solar heating technique, has been studied for many years. A variety of concepts, methodologies and experiences have been developed during relevant research. Especially in recent years, numerous studies on Trombe wall have been published, which implies a rising attention to this technique. This review focuses on the classification, experimental assessment, modeling methods, and evaluation metrics for Trombe wall. In detail, nine types of Trombe walls are introduced according to their materials, structures and functions. Four experimental methods and two modeling methods of Trombe wall are discussed based on their functions, advantages, disadvantages, and applicability. Three aspects of evaluation metrics for Trombe wall are summarized in terms of technique, economy and environment. Moreover, the current and future research of Trombe wall are discussed at the end. The authors consider this article would be useful for their peers and can facilitate the technical development of Trombe wall.

Over the last decade, a number of research and innovation projects have started developing modular facade retrofit solutions which integrate on-site renewable energy technologies. Although there are a growing number of academic articles and demonstration projects showcasing their achievements, the overview of current status and development trend are missing. It is difficult for policymakers, the public and fellow researchers to understand the evolution of modular facade retrofit technologies and who are the important players in the field. As a part of the ongoing European Commission Horizon 2020 project team, the authors decided to write this review article that meets the above needs. Due to the lack of clarification in previous studies, this article firstly introduced and defined the term of Modular Facade Retrofit with Renewable energy technologies (MFRRn), then provided its classification and the review of recent evolution. The MFRRn refer to the retrofitting process that thermal insulation, solar and wind harvest technologies are integrated with the exterior finish of building using modular approach. According to our definition, the MFRRn should fulfil four basic aspects: work to be conducted on existing buildings, work to be undertaken on the facade, using a modular approach, and integrating renewable energy technologies during the retrofit. This study then reviewed 173 research projects funded under the European Commission the seventh Framework, the Horizon 2020's Energy Efficient Buildings programme, the International Energy Agency Energy in Buildings and Communities (IEA EBC) Annex 50 'Prefab Systems for Low Energy/High Comfort Building Renewal' project, the European Cooperation in Science and Technology (COST) Action TU1403 'Adaptive facades network'. The review shows that at least 14 European Commission research projects and 4 case studies mentioned in COST TU1403 and IEA Annex 50 have involved in certain of level of MFRRn development. Their research progress, timeframe, funding scale and funding flow to nations and contributions from key institutes are analysed. Finally, the current challenges regarding the MFRRn developments and implementations are discussed, and future research focus is proposed.

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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.