Using data and local weather forecasts instead of drawings of the supply network and simulations to control supply temperature can save the district heating sector money and reduce CO2.
In Denmark, 1.7 million households (about 64 per cent) are heated by district heating running through 60,000 kilometres of district heating networks. The journey from the district heating plant to the radiators typically takes several hours, which is why the heating requirement must be predictable.
Increasing heat production above requirement levels is undesirable, as it costs money and wastes energy—just as the temperature loss in the pipes is greater at higher temperatures. At the same time, the water must be sufficiently hot at the so-called critical points on the periphery of the supply network. Managing district heating production optimally is thus a science.
At DTU Compute, Professor Henrik Madsen and his colleagues are working on data-driven energy and temperature optimization. Several research projects show that digitalization improves the forecast for heat demand and even helps to achieve Denmark’s 2030 climate goals.
A study carried out by Damvad Analytics together with Denmark’s largest smart city project—CITIES (led by Henrik Madsen)—and the Green Energy Association think tank established by the Danish District Heating Association shows that the district heating sector can save between DKK 240 and 790 million by introducing data-driven temperature control of the flow temperature, as the temperature can be lowered three to ten degrees. Lower temperature also reduces CO2, as well as heat loss in the supply network.