• Energy Research

Benchmarking is a method that can be used to measure progress and create awareness about the performance of organisations. Benchmarking the housing stock energy performance of Dutch housing associations can be used to measure and assess progress towards the decarbonisation of the housing stock. A new national climate agreement was signed in 2019, and in 2021 a new method to determine the theoretical energy performance of dwellings came into force in the Netherlands. To benchmark energy performance, a set of indicators is created that adequately represents the performance of Dutch housing associations according to the changed policies. A process involving key stakeholders is presented here to identify, assess and combine possible indicators. These were then integrated into four integrated models, which led to a final benchmark model. A model was chosen that consists of three indicators covering the energy performance of Dutch housing associations. The process and arguments that led to this final model are presented. While applicable within the Dutch context, the method and research results provide generalisable insights for the creation of energy performance benchmarks for building stocks. 'Practice relevance' This paper provides both researchers and policymakers with a practical approach to monitor and benchmark the energy performance of dwellings owned by organisations. An analysis of the Dutch policy context is presented. Examples of possible benchmark indicators are described and evaluated. A method is created to assess indicators and it is shown how to integrate indicators in different benchmark models. The final model consists of three indicators: (1) the average theoretical primary fossil energy consumption (energy label value); (2) the difference between the theoretical heating demand (quality building envelope) and the theoretical maximum heating demand of dwellings; and (3) the average actual CO2 emissions from gas consumption. Researchers and policymakers from other countries can adapt both the process and the final benchmark model to create similar benchmark models across housing stocks.

The Energy Performance of Buildings Directive (EPBD) enhanced the sustainable improvement of dwellings in the European Union. Member states formulated measurable goals to improve the housing stock, and monitoring systems were developed to give insights into the improvements. In the Netherlands, non-profit housing associations agreed to improve the quality of their housing stock to an average Dutch energy label B (energy index (EI NV) = 1.40) by 2020. Research assessing this progress over time is presented using an annual monitoring system based on 2.0 million energy performance calculations of 264 Dutch non-profit housing associations between 2017 and 2020. The assessment includes: a detailed description of the development of the state of the stock over time; the effect of changes to the stock (construction and demolition) and changes within the stock (different types of retrofit measures); and the different characteristics of non-profit housing associations. Insights from this research show which specific retrofit and other measures are adopted and have substantial impact over time. This provides a useful frame of reference for building stock analysis and accelerating the improvement of the building stock. It also creates a baseline of information for the future sustainable development of this particular stock. 'Practice relevance' This research reveals which energy saving measures are most and least employed over time in Dutch non-profit housing associations sector. Large urban housing associations own a large share of the Dutch non-profit housing stock, and their dwellings have on average a lower energy rating. However, the improvement of their dwellings between 2017 and 2020 is higher than for smaller housing associations, which already have on average a higher energy rating. While the construction and demolition of dwellings contribute to 15.6% of the annual improvement, most of the improvement of the energy performance depends on retrofitting the existing stock. The trends are found to rely most on traditional measures ('e.g'. the installation of high-efficiency gas boilers and improved insulation). However, the rate of adding photovoltaic (PV) solar systems has increased rapidly in recent years, while futureproof systems ('e.g'. heat pumps and district heating) only have a steady adoption rate in this sector.

In Europe, the energy performance of dwellings is measured using theoretical building energy models based on the Energy Performance of Buildings Directive (EPBD), which estimates the energy consumption of dwellings. However, literature shows large performance gaps between the theoretically predicted energy consumption and the actual energy consumption of dwellings. The goal of this paper is to investigate the extent to which empirical models provide more accurate estimations of actual energy consumption when compared to a theoretical building energy model, in order to estimate average actual energy savings of renovations. We used the Dutch non-profit housing stock to demonstrate the results. We examined three empirical models to predict the actual energy consumption of dwellings: a linear regression model, a non-linear regression model, and a machine learning model (GBM). This paper shows that these three models alleviate the performance gap by giving a good prediction of actual energy consumption on sectoral cross-sections. However, these models still have shortcomings when predicting the effects of specific renovation interventions, for example newly introduced heat pumps. The non-linear and machine learning model (GBM) outperform the theoretical model in terms of estimating energy savings through renovation interventions.

Achieving energy efficiency in the built environment requires extensive efforts in the renovation and adaptation of housing stock. A promising design solution is the heat pump. While gas boiler systems are commonly used in Dutch non-profit housing stock, the share of dwellings with a heat pump grew from 1.6% in 2017 to 3.2% in 2021. However, building characteristics and the energy consumption of dwellings with a heat pump are unclear. Therefore, a dataset of 69,422 dwellings with different types of heat pumps has been examined and compared to dwellings with a traditional HR107 condensing gas boiler. This research reports average characteristics and the average actual energy consumption of dwellings with all-electric, hybrid and gas absorption heat pump systems. Dwellings with a heat pump system are on average of higher building quality, their gas consumption is lower and their electricity consumption is higher than dwellings with an HR107 condensing gas boiler. Detailed insight is provided for dwellings with different heat pump systems and for dwellings with different building characteristics. Further research to determine the energy performance of dwellings with specific heat pump configurations is recommended in light of the energy transition in the built environment. ; Design & Construction Management ; Building Energy Epidemiology ; Transport and Logistics