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Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption.

In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects.

The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation.

The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria.

The amount of energy consumption of buildings has obtained international concern so the concept of zero energy building becomes a target for building designers. There are various definitions and evaluation methods for efficient buildings. However, detailed research about the critical parameters that have a major effect through the operational time to reduce the energy consumption is not emphasized as this paper represents. The main aim of this study is to identify the effect of applicable interventions on energy consumption parameters with their sensitivity to each other to reach zero energy building. Relatedly, the cost of energy reduction is also determined.

Energy consumption parameters were defined as area lightings, space heating, space cooling, ventilation fans, pumps, auxiliary equipment and related miscellaneous equipment. The effect of each applied intervention on energy consumption was classified as high, medium, low, very low, no effect and negative effect by utilizing a sensitivity analysis. The base case's energy model is created by utilizing energy performance software such as e-Quest. Accordingly, energy performance improvement scenarios are developed by applying interventions such as lamp replacements, sensors, heat pumps and photovoltaic panels’ integration. Furthermore, sensitivity analyses of each intervention were developed for consumed energy and its cost.

Results indicated the electric consumption is more effective than gas consumption on primary energy and energy cost. Solar systems decline primary energy by 78.53%, lighting systems by 13.47% and heat pump by 5.48% in this building; therefore, integrating mentioned strategies could rise the improvement rate to 100%, in other words, zero amount of energy is using from the grid that means saving $ 5,750.39 in one year.

The study can be applied to similar buildings. It is worthwhile to investigate suggested methods in diverse buildings with different functions and climates in future works.

This study aims to investigate of energy consumption of an educational building in the Mediterranean climate to convert an existing building into a zero energy building by saving energy and renewable sources. Subsequent purposes are analyzing the effect of each strategy on energy consumption and cost.

The novelty of this study is filling gaps in sensitivity analysis of energy consumption parameters by not only identifying their effect on overall energy consumption but also identifying their effect on each other. Some interventions may have a positive effect on overall consumption while having a negative effect on each other. Identifying this critical effect in detail not only further improves the energy performance, but also may affect the decision-making of the interventions.

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.