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In the context of sustainable development, energy-saving renovation of existing buildings can not only effectively reduce energy consumption but also improvement the residential comfort and office environments. This study proposes an optimization method for building energy-saving renovation based on automated machine learning and the NSGA-III algorithm, aiming at efficiently and accurately identifying the best energy-saving renovation schemes. The results showed that automated machine learning could provide a predictive model for multi-objective optimization analysis in a relatively short training time, with an average prediction accuracy of over 95%. And the Stacked Ensemble algorithm and Gradient Boosting Machine algorithm perform the best among all the algorithms considered in this study. Additionally, climate change significantly affects the energy-saving benefits and thermal comfort performance of renovation measures, thereby altering the choice of optimal schemes. The final renovation schemes obtained through the NSGA-III and entropy weight TOPSIS method can achieve an energy saving rate of 22.06% to 26.48% under typical climate scenarios, while also improving thermal comfort time by 31.87% to 43.73%. In future climate scenarios, an energy saving rate of 32.73% to 33.02% and a thermal comfort time of 40.20% to 42.29% can be achieved. Combining these two technologies can quickly and effectively find the best balance among energy consumption, whole life cycle cost, and thermal comfort time. The method proposed in this paper offers new perspectives and tools for researchers in the field of building energy conservation, demonstrating the application potential of automated machine learning and the NSGA-III algorithm in the energy-saving renovation of hospital buildings. [ABSTRACT FROM AUTHOR]

• Smaller/lighter materials which dominate retrofit are poorly characterised in datasets. • Materials are poorly named, described, or are absent in LCA datasets. • LCA for retrofit may not yield reliable information for design decisions. • Embodied energy coefficients may be more reliable than embodied carbon ones. • Reporting only carbon could lead to externalisation of impacts, not avoidance. Low energy domestic retrofit consumes materials, such as insulation, membranes and glazing, with smaller quantities of structural timber, steel or concrete, which have associated embodied impacts from resource extraction, manufacture and end-of-life treatments. In retrofit design, coefficients for material embodied impacts vary widely between sources and can lead to different results in a life cycle energy or carbon analysis, and perhaps different material choices in retrofit implementation. This paper considers how and why results differ between sources, and whether such data is suitable for making climate-beneficial design decisions. Embodied energy and carbon coefficients for 18 key retrofit materials were obtained from two widely used LCA databases and their similarity was quantified. The data collected illustrates that 70% embodied energy and embodied carbon data is within 20%, but that 30% of data was more than 20% different. Consistency of product naming and the absence in the datasets of key retrofit materials are factors identified contributing to variation, and present real constraints in practice. Furthermore, this exercise showed that embodied impacts for the types of materials most prominent in retrofits are less-well characterised than other major construction materials, and presents another layer of uncertainty. The data showed embodied energy was more consistent between sources than embodied carbon. This raises doubts about the predominant use of embodied carbon over energy for such analyses and establishes that a focus on embodied carbon over embodied energy has less power to reduce greenhouse gas emissions than considering both metrics together. It is concluded that obtaining such data with confidence is challenging and requires expertise in LCA, and is therefore unlikely to be accessible to most retrofit designers. Datasets need to be more complete and offer higher confidence to ensure delivery of high quality and meaningful results for climate-beneficial design decisions. [ABSTRACT FROM AUTHOR]

[Display omitted] The rising global energy use in buildings, driven by climate change and economic expansion, is a major concern. In Algeria, the residential sector is a significant contributor, accounting for roughly 40 % of total energy consumption and 32 % of greenhouse gas emissions. This paper aims to Modeling and forecasting energy consumption in Algerian residential buildings. In this study, a bottom-up methodology was combined with Geographic Information System (GIS) analysis to quantify and project energy consumption patterns in Algerian residential buildings until 2100, as well as identify climate zones, which will help develop thermal standards. Commencing with the collection of pivotal data such as temperature and global horizontal irradiation (GHI), the research proceeds to ascertain the annual heating and cooling needs for residential houses across Algeria (at 906 uniformly dispersed spots) using the degree-days method. Besides, the energy consumption for other residential appliances, including lighting, refrigerators, and freezers are also evaluated. Utilizing a GIS software (ArcGIS 10.x), the obtained results for various building energy usage at 906 points are therefore interpolated to generate high resolution maps representing different regions in Algeria. The analysis predicts a significant rise in energy consumption from 47.54 TWh in 2022 to 74.4 TWh in 2100, underscoring the diverse energy requirements across nine identified climatic zones. Zone 5 emerges as the highest energy-consuming zone per household, attributed to its elevated Heating Degree Days (HDD) and Cooling Degree Days (CDD) values. Additionally, cooking emerges as the primary energy consumer nationally, accounting for 30.61 % of total consumption, with variations observed in the usage of appliances like air conditioners and fans, influenced by local climate conditions. Zones with high heating energy needs, such as Zone 5, could benefit from energy-efficient heating systems, while zones with substantial cooling energy requirements, like Zone 9, may require targeted cooling strategies. These findings emphasize the necessity of tailored energy policies to address the distinct demands of each climatic zone rather than setting standard strategies for all regions. Despite few limitations of this study, useful insights are gained that can aid policymakers and urban planners in crafting sustainable energy policies to address evolving residential energy demand in Algeria and beyond. [ABSTRACT FROM AUTHOR]

• Climate change's impact on retrofitting was tested on Le Corbusier's apartment. • Climate change scenarios project up to 70% increase in summer overheating. • Adaptive natural ventilation can reduce warm discomfort of 50–60%. • Adaptive setpoints can reduce total energy consumption of 20–30%. • Adaptive strategies are particularly favourable in historic buildings. Historic buildings, often exempt from retrofits to preserve originality, require retrofitting due to potential future climate-related indoor issues. For Modern Architecture constructions, there is a need to find solutions that help address the discomfort and heat losses caused by the extensive use of glazing. By analysing Le Corbusier's studio-apartment this paper aims to inspect: (i) Solutions for energy, Indoor Environmental Quality, and preservation; (ii) Climate change impact on them; (iii) Possible adaptation strategies to cope with climate change. Spectrally selective glazing reduced summer overheating by 15%; high-performance glazing lowers cold discomfort (24%) and heating (22%) but increased warm discomfort; shadings maintained energy use and reduced summer discomfort by up to 44%; thermal insulation can reduce winter discomfort and halves energy use but raised summer discomfort by up to 41%. Tests on 2050–2100 climate change scenarios reveal up to 70% more warm discomfort hours. Adaptive strategies can help, with natural ventilation cutting warm discomfort by 50–60%, and adaptive setpoints reducing cooling demand by about 35%. Adaptive strategies can complement traditional retrofitting in addressing current and future climate conditions, especially in historic buildings that require minimal interventions to preserve their historical characteristics and enhance resilience. [ABSTRACT FROM AUTHOR]