Monitoring energy efficient cities
In PLEEC’s work package 2 an indicator model (‘Energy-Smart Cities-Model’) to monitor the energy performance of cities was developed. The work was led by researchers at the Vienna University of Technology, with contributions of other partners in PLEEC (Giffinger, Hemis, Weninger, & Haindlmaier, 2014).
Based on that methodology an analysis and benchmark of the energy situation of Danish municipalities was conducted. This spin-off project was financed by the Danish energy service company NRGi and their affiliated company Kuben Management, who have an interest in exploring the operationalization of the smart city, a term which is widely used in current city development strategies.
The model is hierarchically structured, aggregating indicators into 16 domains and further into 6 key fields related to different aspects energy. When aggregated, the indicators are not weighted in particular. However, as some domains have more indicators than others, some indicators account for a higher share of a domain’s result (and subsequently the related key field) than others.
The application of the model to all 98 Danish municipalities shows that energy consumption is closely related to urban development. Urban municipalities show a much better performance in Green buildings and land-use and in Mobility and transport, while the patterns seems turned around for Energy supply. The other three key fields are not the clearly related and urban-rural typology. Looking at the level of domains reveals further relations of energy and urban areas. District heating is clearly more used in urban areas, while heat pumps are more used in rural areas.
As the aggregated key fields and domains only give a very general picture of the energy situation, a closer look at selected indicators is worthwhile. As far as possible we also included the six PLEEC case cities as references. Looking for example at the average annual energy demand in households we can see considerable differences, where households in the municipality with the highest average use double the energy than in those with the lowest average. All six PLEEC cities are in the lower end of energy demand in households. However, one has to consider that the PLEEC cities typically only cover the core municipality of the urban area they form. We have no data on their surrounding municipalities.
The focus on selected indicators can sharpen the picture of certain patterns in energy demand and supply, avoiding the aggregation of sometimes opposing indicators (e.g. the share of district heating and the share of heat pumps). Also patterns to other factors can be identified. E.g. the share of energy-efficient dwellings (those with an Energy Label C or better) is highest in the areas with high economic and population growth, which mirrors the high investment in renovation and new construction in these areas compared to less dynamic areas.
As every model, also the Enery-Smart Cities-Model is simplifying reality. A selection of indicators are aggregated to benchmark the performance in particular key fields related to energy, while case specific contexts and developments can only be marginally accounted for. The model should therefore be used as a screening tool to base further analysis on. Also, the current model only illustrates the status at a specific point in time. Any progress or development is not mirrored. However, that might be possible in future analysis, because most data used in this report is available for several years. A benchmark evaluating on the one hand the status of energy use and on the other hand the progress of getting more efficient, more sustainable, is feasible and would be an important contribution.
You can find the background report here.