  District heating is a network of pipes through which heat is delivered from a
centralised source. It is expected to play an important role in the
decarbonisation of the energy sector in the coming years. In district heating,
heat is traditionally generated through fossil fuels, often with combined heat
and power (CHP) units. However, increasingly, waste heat is being used as a low
carbon alternative, either directly or, for low temperature sources, via a heat
pump. The design of district heating often has competing objectives: the need
for inexpensive energy and meeting low carbon targets. In addition, the
planning of district heating schemes is subject to multiple sources of
uncertainty such as variability in heat demand and energy prices. This paper
proposes a decision support tool to analyse and compare system designs for
district heating under uncertainty using stochastic ordering (dominance).
Contrary to traditional uncertainty metrics that provide statistical summaries
and impose total ordering, stochastic ordering is a partial ordering and
operates with full probability distributions. In our analysis, we apply the
orderings in the mean and dispersion to the waste heat recovery problem in
Brunswick, Germany.
