HOT|COOL NO. 2/2019 - "Smart Heating System Integration"

P27

CASE STUDY: THE CLUSTER-DENSITY APPROACH Figure 1

As shown in Figure 3, the cluster density model also has higher diversity of heat load, reducing average costs. At 20% the cluster density model connects around 40% more households than the internal approach; below 20% the ratio is even higher.

Figure 3

Area/Demand 0.9 2.0 2.8 1.7

Demand 6.2 6.0 4.1 10.3

Area 5.6 12.1 11.4 17.0

Zone A B C A+C

HOUSEHOLDS IN FUEL POVERTY BENEFIT FROM CLUSTER DENSITY MODEL: Reducing fuel poverty is often a DH policy goal. The cluster density analysis suggests however that areas with highest heat density are often some distance from areas with high levels of fuel poverty, including electrically heated social housing. Most social housing in our cluster-density analysis was selected based on proximity to heat dense clusters. This highlights the additional social benefit of the cluster density model. DH POLICY AND REGULATORY FRAMEWORKS IN NORWAY AND NETHERLANDS Our research also investigated how countries similar to the UK are supporting DH development . Like the UK, Norway and Netherlands have limited DH and were early in liberalising energy markets. Both countries have, however, had greater DH success, including clustering developments. Local and central governments have managed cooperation between business, public and housing sectors, using forms of licensing, planning and regulation to support an effective heat market, using large heat sources such as waste industrial heat.

By combining Zones A and C, the cluster density model enables economic connection of lower heat density Zone A, where the required cost threshold would not otherwise be met. The result is better economies of scale and cost savings, including efficient use of a single heat source to supply both areas (Figure 2).

Figure 2

www.dbdh.dk

J O U R N A L N 0 . 2 / 2 0 1 9

Made with FlippingBook Ebook Creator