1. Flexible space heating demand for district heating systems
– Case study of Gothenburg, Sweden
Dmytro Romanchenko
July 3rd, 2018
03/07/2018
Chalmers University of Technology

2. Chalmers University of Technology
Main findings
Using the thermal mass of buildings as energy storage, i,.e. active demand response, has a significant potential to smoothen heat load variations in District Heating (DH) systems
The space heating demand response potential of buildings via 1°C indoor temperature variations is sufficient to significantly effect the heat load of a DH system
Reduced variations in the heat load result in improved efficiency of heat generation in DH systems
Higher utilization factor of base-load heat generators
Decreased number of starts and stops of peak-load heat generators
03/07/2018
Chalmers University of Technology

3. Chalmers University of Technology
Background
Energy used for space heating and hot water in single-family, multi-dwelling and non-residential buildings in 2015
03/07/2018
Chalmers University of Technology

4. Chalmers University of Technology
Motivation for the research
Requirement for the peaking heat generation (usually fossil fuels-based heat-only boilers HOBs)
High number of starts and stops
Part-load operation
Scheduling challenges (HPs and CHP plants)
Thermal energy storage, e.g.:
Hot water tanks and boreholes
Thermochemical storage
Active demand response from buildings
03/07/2018
Chalmers University of Technology

5. Chalmers University of Technology
Aim of the research
Increase an understanding of how flexible heat demand from buildings can affect the supply side, i.e., operation of DH systems
Objective of the research
Develop a modelling method, which integrates the calculation of the space heating demand from buildings, by this allowing for demand response, with the dispatch of the investigated DH system
Estimate the effects of the ´space heating demand response on the total energy demand and operation of the DH system
03/07/2018
Chalmers University of Technology

6. Chalmers University of Technology
Model development
03/07/2018
Chalmers University of Technology

7. Chalmers University of Technology
Building stock of Gothenburg, Sweden
The building stock of Gothenburg is represented by:
28 sample single-family houses (SFHs)
~ extrapolated to 9,700 real SFHs
(1.5 mln m2)
66 sample multi-family houses (MFHs)
~ extrapolated to 5,300 real MFHs
(15.8 mln m2)
40 sample non-residential buildings (NRBs)
~ extrapolated to 3,600 real NRBs
(6.2 mln m2)
Description of the sample buildings is extracted from the BETSI study, which comprises 1800 buildings selected to represent the total Swedish buildings stock
NRBs are further divided in 5 sub-categories (based on the purpose of the building)
03/07/2018
Chalmers University of Technology

8. Chalmers University of Technology
District heating system of Gothenburg, Sweden
Second largest district heating system in Sweden
28 heat generation units
3,300 GWh of heat delivered yearly
1000 km trench length of the network
56% of generated heat stems from industrial excess heat and waste incineration
18% of generated heat stems from renewable energy sources
Supplies heat to 90% of all MFHs and 20% of all SFHs in the city
03/07/2018
Chalmers University of Technology

9. Chalmers University of Technology
Results – Heating load with flexible demand response in buildings
“Reference” – indoor temperature is fixed – no DR
“Tvar 1(ºC)” – DR via upward temperature deviations of up to 1ºC
“Tvar 3(ºC)” – DR via upward temperature deviations of up to 3ºC
03/07/2018
Chalmers University of Technology

10. Chalmers University of Technology
Results – Effects of demand response on the heat load variations
RDLV
a) spring-autumn
b) winter
“Reference” – indoor temperature is fixed – no DR
“Tvar 1(ºC)” – DR via upward temperature deviations of up to 1ºC
“Tvar 3(ºC)” – DR via upward temperature deviations of up to 3ºC c)
03/07/2018
Chalmers University of Technology

11. Chalmers University of Technology
Results – Effects of demand response on the operation of units
drop by 85%
“Reference” – indoor temperature is fixed – no DR
“Tvar 1(ºC)” – DR via upward temperature deviations of up to 1ºC
“Tvar 3(ºC)” – DR via upward temperature deviations of up to 3ºC
03/07/2018
Chalmers University of Technology

12. Chalmers University of Technology
Conclusions and remarks
The potential of demand response from buildings is investigated by means of the overheating of buildings by 1ºC and 3ºC
The demand response from buildings has a significant impact on the total system heat load:
Decreased number and amplitude of heat load variations
Improved operation of heat generation units
Decreased cost of heat generation
Developed optimisation modelling is generic and applicable to other DH systems and building stocks
03/07/2018
Chalmers University of Technology

13. Chalmers University of Technology
Remarks and future work
Improve representation of the hot water and industrial loads in the modelling
Apply both upward and downward temperature deviations for studying the potential of DR
To study future development of the building stock
e.g. implementation of energy conservation measures
Test developed modelling on other systems/cities and upscale to the national level
Expand heat-oriented research to the total energy load in buildings
03/07/2018
Chalmers University of Technology

14. Chalmers University of Technology
Thank you for your attention!
03/07/2018
Chalmers University of Technology