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

Comparing district heating options under uncertainty using stochastic ordering