To demonstrate and verify our method in more detail, we apply it to a small region well known to us. In the first step, we determine the theoretical potential, that is, the overall heat demand and its geographic location, continuing with the distribution of the total heat demand of different building types and their geographic location. In the second step, we estimate the practical potential, searching out the small geographic clusters, e. g. 500 x 500 m2, where the heat demand exceeds for example 0.5 GWh. Those clusters can be the starting points for small-scale district heating and CHPs.

The 36 x 48 km2 region is located in the middle of the county of Kalmar, southeast Sweden. It is a rural district with 8000 inhabitants, thus only 5 inhabitants per km2. There are 2000 people living in the largest urban agglomeration, and seven villages with populations between 300 and 600 inhabitants. This small region is mostly forested with an abundant supply of wood waste. In addition, there is a small agricultural district around the largest center and some of the other villages, which can provide biomass in the form of agricultural residues. There are ten hydropower stations in the two main rivers of the region, producing approximately 25 GWh annually. Solar and wind energy is very marginal. There is one new, small district­heating system of 0.8 GWh using wood pellets.

The theoretical heat demand potential found for this region is 102 GWh, based on estimates for every single building, and implying an average heat demand per inhabitant near the national average lOMWh. Figure 8.3 shows the geographic distribution of the theoretical potential in the region, where relevant concentration is found in less than ten places. Obviously, there is a strong correlation between the distribution of population and activities performed in the region and what is observed in this figure.

Of the total 102GWh, 77GWh is the demand of one — and two-family houses, 7 GWh from multidwellings, 13 GWh from industrial, 2 GWh from commercial and 3GWh from public buildings. This distribution was anticipated as small houses dominate in rural districts. Thus 75 per cent of the theoretical potential comes from single dwellings. Multidwellings are found in only eight places with at least 300 inhabitants, and industrial and public buildings are more scattered. As much as 25 per cent of the heat demand is found in the larger buildings, which facilitates the search for starting points for the district-heating grids.

Stepping from the theoretical to the practical potential, we focus our interest on small geographic clusters where the heat demand exceeds a certain limit. We have used a quadratic shape, the four cluster sizes 250 x 250 m2,500 x 500 m2,750 x 750 m2 and 1000 x 1000 m2, and a minimum heat demand of 0.5 GWh. Table 8.1 shows the number of clusters found for each range of heat demand. Obviously, when the cluster area increases, more clusters reach the minimum stipulated limit of 0.5 GWh. At the same time, adjacent clusters merge.

Focusing on single dwellings, the share of the heat consumption included in the clusters in relation to the total 77 GWh increases as the clusters are enlarged, going from 16 per cent for the 250 x 250 m2 clusters to 65 per cent for the 1000 x 1000 m2 clusters. Consequently, the average heat consumption per cluster increases from 0.6 GWh in the smallest cluster size to 1.6 for the largest cluster size. At the same

time, the average heat consumption per km2 in a cluster decreases from 9.9 GWh per km2 in the 250×250 m2 clusters to 1.6 in the 1000 x 1000 m2 clusters (see also Figure 8.4).

Before leaving our small region, we will also summarize the heat demand for all building types. We limit the analysis to 500 x 500 m2 clusters and a minimum heat demand of 0.5 GWh per cluster. In this case, we arrive at 53 clusters, which together account for 64 of the total 102 GWh heat demand in this small region. Table 8.1 indicates the number of clusters found for each range of heat demand and allows an easy comparison with the case where only single houses are considered. The inclusion of all building types results in a larger number of clusters with enough heat demand to justify combined heat and power already today. Moreover, the nonresidential buildings with their larger average heat demand can serve as crystallization points for the heat grid. Many of them also have production facilities that can be of some

use. Figure 8.5 shows the distribution of the clusters found, and their heat demand in more detail.

A good half of the heat demand from single houses in the area, and some 85 per cent of all heat demand from other buildings are captured in the clusters found. Continued technical development and increased taxation of external costs of nonsustainable energy sources can make more clusters rapidly ready for CHP, while also attracting investors to build the necessary infrastructure.