Price model analysis for district heating systems: How should district heating companies charge their customers?

Abstract

A district heating (DH) price model is referred to as the way DH companies charge their customers for supplied heat. In Sweden, the price models of DH have been moving towards being cost-based rather than market-based as it reduces the economic risks for DH companies. However, a challenge for the DH companies is to know what works when setting up a price model as different customers want different things. In general, the customers want a price model that is understandable, predictable and simple. Therefore, analysis and evaluation of different price models in three different DH networks are performed to see how the components of the price models behave and perform between years and networks. A heat pump (HP) can be used as an alternative for DH. HPs are the biggest competitor of DH in Sweden today, which is why the competitiveness of HPs against DH is analyzed. The reasons why choosing HP over DH is problematic are firstly, that the DH companies lose customers. Secondly, if the electricity mix in the network is not 100% renewable, the HP might be increasing the demand for non-renewables as it runs on electricity and would increase the peaks in the system which are typically covered with non-renewables. The results indicated how different networks benefit differently from including different cost components in the price model, depending on the system’s behaviour. Inefficient systems with high return temperatures (RTs) would, for example, benefit from charging for too high RTs with the use of a RT component as part of the price model. To avoid significant fluctuations in the fixed costs of the revenues, using a power signature for the power cost component, where the capacity is sized based on a cold day, results on average in 2.5-3% less fluctuations compared to the other price models. The fixed costs will vary more if the cost is based on previous, measured usage, making the revenues less predictable. Using power signature also showed the best performance during warm year, the year when the companies are at the most significant risk of getting lower revenues than expected as the heat demand decreases. The HP results showed that it depended on the HP size if the investment was profitable or not, as a larger size will substantially increase the investment cost. All the small residential buildings included showed prominent results while all the industrial buildings were not profitable. However, the assumed interest rate and the lifetime of the HPs and electricity prices have a significant impact on the results, which is essential to keep in mind.