Energy Efficiency in Building Performance

Energy efficiency in building performance encompasses strategies to minimise energy consumption while maintaining occupant comfort and functionality. Central to this effort are improvements in the building envelope, advanced control of heating, ventilation and air conditioning (HVAC) systems, and the integration of renewable energy sources. Detailed modelling and simulation tools enable prediction of thermal loads and facilitate the assessment of retrofit measures such as insulation, glazing upgrades and onsite photovoltaic systems. Digitalisation—including sensor networks, data analytics and machine-learning algorithms—has enhanced real-time monitoring and demand-response capabilities. Retrofits of existing stock and optimized design of new buildings both contribute to decarbonisation targets, with potential reductions in energy use of over 50 per cent in many climates. As urban populations grow and climate change alters heating and cooling demands, scalable models and robust control strategies are vital to achieving net-zero carbon goals and ensuring global resilience.

Research from Nature Portfolio

Recent studies introduce a global hourly model for space heating and cooling demand that operates across multiple spatial scales and requires minimal input data. Validated against thousands of buildings and dozens of regions, this framework demonstrates improved agreement with measured demand compared with legacy models and quantifies the impact of modest thermostat adjustments on energy savings. Projections reveal that cooling demand is rising by up to 5 per cent annually in some regions, driven by climate change, with billions of people experiencing significantly more cooling degree days than previous generations. Another investigation with eight international cities defines tailored shallow and deep retrofit packages alongside onsite solar generation potential. Implementation of these packages could reduce building energy use by up to 66 per cent and carbon emissions by 84 per cent, enabling several municipalities to meet 2030 and 2050 climate targets when combined with projected grid decarbonisation.

Energy Efficiency in Building Performance publication trend

The graph below shows the total number of articles in energy efficiency in building performance across all publications each year (not limited to Nature Index journals).

Technical terms

Heating, ventilation and air conditioning (HVAC): Systems that regulate indoor temperature, humidity and air quality.

Cooling degree days: A metric of cooling demand calculated as the sum of daily temperature deviations above a baseline.

Retrofit: The process of upgrading existing buildings with new technologies or materials to improve energy performance.

Deep reinforcement learning (DRL): An AI approach in which agents learn optimal control policies through trial and error.

Model predictive control (MPC): A control technique that uses a dynamic model to optimise future system behaviour under constraints.

Response surface methodology (RSM): A statistical method for modelling and analysing the influence of multiple variables on performance.

References

1. A global model of hourly space heating and cooling demand at multiple spatial scales. Nature Energy (2023).
2. Carbon reduction technology pathways for existing buildings in eight cities. Nature Communications (2023).
3. An experimental evaluation of deep reinforcement learning algorithms for HVAC control. Artificial Intelligence Review (2024).
4. Optimizing smart building energy management systems through industry 4.0: A response surface methodology approach. Green Technologies and Sustainability (2024).
5. All you need to know about model predictive control for buildings. Annual Reviews in Control (2020).