Price model analysis for district heating systems
Examensarbete för masterexamen
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Bibliographical item details
|Type: ||Examensarbete för masterexamen|
|Title: ||Price model analysis for district heating systems|
|Authors: ||Gudnadóttir, Aníta Hlín|
|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.|
|Keywords: ||District heating, price models, revenues, KPI, heat pumps|
|Issue Date: ||2022|
|Publisher: ||Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE)|
|Collection:||Examensarbeten för masterexamen // Master Theses|
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