Energy, cost and emission saving potential of demand response and peak power limiting in the German district heating system

Figures & data

Figure 1. Flow chart of the entire simulation process. Modified from Ju et al. (2021).

Figure 2. Building simulation process flow chart.

Figure 3. Measured outdoor temperature in Hamburg in 2018.

Table 1. General building information.

General building information	Apartment building	Cultural centre	Office building
Construction year	1930s	1980s	1966
Latest renovation year	–	2010s	1980s
Number of floors	4	3	4
Heated net floor area [m^2]	4885	3937	2383
Building volume (ext. dimension) [m^3]	12000	16314	8556
Envelope area [m^2]	4780	6921	3855
Window to envelope ratio [%]	7.6	8.8	9.5

Table 2. Building model parameters used in the IDA ICE simulations.

Building model parameter		Apartment building	Cultural centre	Office building
U-value	External wall	1.7	0.2	0.2
	Roof	1.4	0.19	0.19
	Ground slab	1.0	0.28	0.28
	Window	3.0	3.0	4.5
Air leakage rate, n50 [1/h]		7.0	3.0	4.5
Occupancy	Weekly time	Continuous	Every day 8 am to 9 pm	Workdays 8 am to 4 pm
	Annual hours [h]	8760	4498	2000
Annual internal heat gains of equipment [kWh/m^2,a]		11	9	2
Annual internal heat gains of lighting [kWh/m^2,a]		16	17	11
Design power of space heating and ventilation heating at design temperature [kW] (Without internal and solar heat gains)		225	304	292
Specific heating power of space heating and ventilation at design temperature [W/m^2]		46	77	123

Figure 4. Heating inlet water temperatures used in the building simulations.

Table 3. Ventilation systems’ input parameters.

Building type	Ventilation system	Air change rate	Operation time
Apartment building	Natural ventilation	0.24 1/h	Always on
Cultural centre	Mechanical supply and exhaust ventilation (CAV) without heat recovery for kitchen, restaurant, basement, and hall	1.7–2.36 l/s, m2	8 am–10 pm 7 am–10 pm (Basement)
	Mechanical exhaust ventilation (CAV) for toilets	2.5-4.5 l/s, m2	Always on
	Natural ventilation for other spaces	0.2-0.43 l/s, m2	Always on
Office building	Mechanical supply and exhaust ventilation (CAV) without heat recovery	2.1 l/s, m2	6 am–6 pm for workdays

Figure 5. Indoor air temperature setpoint control algorithm flow chart.

Table 4. Generation units and their powers in the used production scenario.

Generation unit	Heat power [MW]	Electricity power [MW]	Heat storage capacity [MWh]
CHP	+0.737	+0.527	–
Gas boiler 1	+1.950	–	–
Gas boiler 2	+1.100	–	–
Heat pump	+1.320	−0.330	–
Solar thermal plant (ST)	+0.483	–	–
Thermal storage	–	–	1.40
Total	5.590

Figure 6. District heating supply temperature and the optimal maximum return temperature of the district heating network of Hamburg.

Table 5. Price structure of the distritct heat.

Cost type	Based on	Price
Construction fee	Design heating water volume flow rate [dm^3/h]	2.98 [€/(dm^3/h)]
Base fee	Maximum heating water volume flow rate [dm^3/h]	8.34 [€/(dm^3/h)]
Energy cost	Heating energy consumption [kWh]	Dynamic DH price signal

Table 6. Main parameters of the dynamic DH consumer price of the studied production scenario.

	Minimum (€/MWh)	Maximum (€/MWh)	Average (€/MWh)	Standard deviation (€/MWh)
Dynamic DH price of the production scenario	8.6	99.9	91.2	5.2

Table 7. Building simulation cases.

Simulation cases		Input settings
Case	Description	Demand response	Peak power limiting
Building type-R-21	Reference case, without DR and PPL	No	No
Building type-DR	With DR	Yes	No
Building type-DR-PPL80	With DR and 80% peak power limiting	Yes	Yes, 80%
Building type-DR-PPL70	With DR and 70% peak power limiting	Yes	Yes, 70%
Building type-DR-PPL60	With DR and 60% peak power limiting	Yes	Yes, 60%

Table 8. District heating network level simulation combinations. Quantity of each building type, demand response and peak power limiting setup.

Simulation cases		Input for buildings
Case	Description	Apartment			Cultural centre			Office
		Qty.	DR	PPL	Qty.	DR	PPL	Qty.	DR	PPL
Reference	No demand response or peak power limiting	7	No	No	2	No	No	13	No	No
DR	Only demand response	7	Yes	No	2	Yes	No	13	Yes	No
DR and PPL	Demand response and peak power limiting	7	Yes	80%	2	Yes	70%	13	Yes	70%

Figure 7. Duration curves of the space heating power in apartment building cases in the heating season.

Figure 8. Hourly space heating demand in apartment building on one of the coldest days of the simulation year.

Table 9. Annual power and energy results of the apartment building cases. Power limit time indicates the occupied hours that the peak limit takes place, and the time percentage indicates the share of the occupied hours.

Simulation case	Power limit of space heating			Total DH peak power			The total DH energy consumption
	Peak [kW]	t[h]	t-%	Peak [kW]	ΔkW	Δ%	Energy [MWh/a]	ΔMWh	Δ%
AB-R-21				203			480.2
AB-DR	–	–	–	194	−8.4	−4.1	466.8	−13.2	−2.8
AB-DR-PPL80	145	119	1.4	169	−33.4	−16.5	465.8	−14.2	−3.0
AB-DR-PPL70	127	268	3.1	151	−51.4	−25.3	463.6	−16.4	−3.4
AB-DR-PPL60	109	727	8.3	134	−69.3	−34.2	458.4	−21.6	−4.5

Figure 9. Duration curves of the space and ventilation heating power of occupied hours in the cultural centre case in the heating season.

Figure 10. Hourly space and ventilation heating demand in cultural centre on one of the coldest days of the simulation year.

Table 10. Annual power and energy results of the cultural centre cases. Power limit time indicates the occupied hours that the peak limit takes place, and the time percentage indicates the share of the occupied hours.

Simulation case	Power limit of space and ventilation heating			Total DH peak power			The total DH energy consumption
	Peak [kW]	t[h]	t-%	Peak [kW]	ΔkW	Δ%	Energy [MWh/a]	ΔMWh	Δ%
CC-R-21				269			457.0
CC-DR	-			262	−6.7	−2.5	438.9	−18.1	−4.0
CC-DR-PPL80	210	21	0.2	232	−37.0	−13.8	438.6	−18.4	−4.0
CC-DR-PPL70	184	65	0.7	210	−59.2	−22	438.4	−18.6	−4.1
CC-DR-PPL60	159	238	2.7	196	−73.3	−27.3	437.2	−19.8	−4.3

Figure 11. Duration curves of the space and ventilation heating power of occupied hours in the office building cases in the heating season.

Table 11. Annual power and energy results of the office building cases. Power limit time indicates the occupied hours that the peak limit takes place, and the time percentage indicates the share of the occupied hours.

Simulation case	Power limit of space and ventilation heating			Total DH peak power			The total DH energy consumption
	Peak [kW]	t [h]	t-%	Peak [kW]	Δ kW	Δ %	Energy [MWh/a]	Δ MWh	Δ %
OB-R-21				277			280.1
OB-DR	–			272	−5.1	−1.8	266.9	−13.2	−4.7
OB-DR-PPL80	223	12	0.1	231	−46.1	−16.6	267.0	−13.1	−4.7
OB-DR-PPL70	195	37	0.4	204	−73.4	−26.5	267.2	−12.9	−4.6
OB-DR-PPL60	166	105	1.2	206	−70.6	−25.5	267.2	−12.9	−4.6

Figure 12. Hourly space and ventilation heating demand in office building on one of the coldest days of the simulation year.

Figure 13. Hourly indoor air temperature in office building simulation in one of the coldest days of the year.

Table 12. Annual district heating energy, base and total DH cost savings in apartment building cases.

Simulation case	Energy cost			Base cost			Total cost
	Cost [€/a]	Δ€/a	Δ%/a	Cost [€/a]	Δ€/a	Δ%/a	Total [€/a]	Δ€/a	Δ%/a
AB-R-21	44 115			30 547			74 662
AB-DR	42 858	−1257	−2.8	29 280	−1267	−4.1	72 138	−2524	−3.4
AB-DR-PPL80	42 768	−1347	−3.1	25 514	−5033	−16.5	68 282	−6380	−8.5
AB-DR-PPL70	42 559	−1556	−3.5	22 807	−7740	−25.3	65 365	−9296	−12.5
AB-DR-PPL60	42 076	−2039	−4.6	20 130	−10417	−34.1	62 179	−12 456	−16.7

Table 13. Annual district heating energy, base and total DH cost savings in cultural centre cases.

Simulation case	Energy cost			Base cost			Total cost
	Cost [€/a]	Δ€/a	Δ%/a	Cost [€/a]	Δ€/a	Δ%/a	Total [€/a]	Δ€/a	Δ%/a
CC-R-21	42 087			40 501			82 588
CC-DR	40 371	−1716	−4.1	39 489	−1012	−2.5	79 860	−2728	−3.3
CC-DR-PPL80	40 340	−1747	−4.2	34 924	−5577	−13.8	75 264	−7324	−8.9
CC-DR-PPL70	40 319	−1768	−4.2	31 583	−8918	−22.0	71 902	−10 686	−12.9
CC-DR-PPL60	40 207	−1880	−4.5	29 462	−11039	−27.3	69 668	−12 920	−15.6

Table 14. Annual district heating energy, base and total DH cost savings in office building cases.

Simulation case	Energy cost			Base cost			Total cost
	Cost [€/a]	Δ €/a	Δ %	Cost [€/a]	Δ €/a	Δ %	Total [€/a]	Δ €/a	Δ %
OB-R-21	25 937			41 596			67 533
OB-DR	24 686	−1251	−4.8	40 934	−662	−1.6	65 620	−1913	−2.8
OB-DR-PPL80	24 692	−1245	−4.8	34 764	−6832	−16.4	59 457	−8076	−12.0
OB-DR-PPL70	24 708	−1229	−4.7	30 656	−10940	−26.3	55 364	−12 169	−18.0
OB-DR-PPL60	24 711	−1226	−4.7	31 075	−10521	−25.3	55 786	−11 747	−17.4

Table 15. Indoor air setpoint variation in hours

Simulation case	Indoor temperature setpoint, [°C]
	20	21	23
Annual hours [h]	5659	3101	0

Table 16. The effect of demand response and peak power limiting to indoor air temperature in the coldest occupied room in the apartment building simulation.

Simulation case	Limit and annual affected hours			Occupied hours below [h]				Degree hours below[°Ch]
	Peak [kW]	t[h]	t-%	21°C	20°C	19°C	18 °C	21°C	20°C	19°C	18°C
AB-R-21				109	0	0	0	10	0	0	0
AB-DR	–			3275	8	0	0	1512	1	0	0
AB-DR-PPL80	144	119	1.4	3288	82	15	0	1602	47	6	0
AB-DR-PPL70	126	268	3.1	3342	189	108	62	1856	256	123	38
AB-DR-PPL60	108	727	8.3	3547	310	194	143	2407	639	400	226

Figure 14. Duration curves of the indoor air temperature in the coldest occupied room during the coldest 800 h in the apartment simulation cases.

Table 17. The effect of demand response and peak power limiting to indoor air temperature in the coldest occupied room in the cultural centre simulation.

Simulation case	Limit and annual affected hours			Occupied hours below [h]				Degree hours below [°Ch]
	Peak [kW]	t[h]	t-%	21°C	20°C	19°C	18°C	21°Ch	20°Ch	19°Ch	18°Ch
CC-R-21
CC-DR	-			1342	0	0	0	523	0	0	0
CC-DR-PPL80	209	21	0.2	1343	2	0	0	526	0	0	0
CC-DR-PPL70	183	65	0.7	1346	4	1	0	534	3	0	0
CC-DR-PPL60	157	238	2.7	1363	20	4	2	564	11	3	0

Figure 15. Duration curves of the indoor air temperature in the coldest occupied room during the coldest 100 h in the cultural centre simulation cases.

Table 18. The effect of demand response and peak power limiting to indoor air temperature in the coldest room of the office building simulation.

Simulation case	Limit and annual affected hours			Occupied hours below [h]				Degree hours below [°Ch]
	Peak [kW]	AH [h]	ΔAH [%]	21 °C	20 °C	19 °C	18 °C	21 °C	20 °C	19 °C	18 °C
OB-R-21				20	0	0	0	2	0	0	0
OB-DR	–			1005	0	0	0	491	0	0	0
OB-DR-PPL80	217	12	0.1	1005	7	0	0	497	3	0	0
OB-DR-PPL70	190	37	0.4	1007	21	10	0	517	18	4	0
OB-DR-PPL60	163	105	1.2	1015	40	26	17	574	62	30	6

Figure 16. Duration curves of the indoor air temperature in the coldest occupied room during the coldest 100 h in the office building simulation cases.

Figure 17. Annual hourly community district heating power demand of the simulated year.

Figure 18. Duration curve of the district heating system’s total power demand of the highest demand hours. The effect of the peak power limiting is illustrated by hatched area.

Table 19. Network level demand response and peak power limiting results. Difference is stated relative to the reference case for DR and DR&PPL cases separately.

Case	Total heat [MWh/a]	Total generation cost [€/a]	CO2 emissions [t-CO2/a]	Specific generation cost [€/MWh]	Average generation cost [€/MWh]
Reference	7919	−83 801	133.0	−10.6	−18.5
DR	7616	−88 718	90.0	−11.6	−18.6
Δ-abs.	−303	−4917	−43	−1.0	−0.1
Δ%	−3.8	−5.9	−32.3	−10	−0.5
DR and PPL	7611	−88 891	88.2	−11.7	−18.6
Δ-abs.	−308	−5090	−44.8	−1.1	−0.1
Δ%	−3.9	−6.1	−33.7	−10.3	−0.5

Table

AB	apartment building
CC	cultural centre
CHP	combined heat and power plant
CO2	carbon dioxide
CS	control signal
DH	district heating
DHW	domestic hot water
DR	demand response
DSM	demand side management
EU	European union
GHG	Greenhouse gas
HEP	hourly energy price
HGSO	heat generation schedule optimiser
HOB	heat-only boiler
OB	office building
PPL	peak power limiting
ST	solar thermal

Ju, Y., J. Lindholm, M. Verbeck, J. Jokisalo, R. Kosonen, P. Janßen, Y. Li, H. Schäfers, and N. Nord. 2021. “Cost Savings and CO2 Emissions Reduction Potential in the German District Heating System with Demand Response.” Science & Technology for the Built Environment 28 (2): 1–27. https://doi.org/10.1080/23744731.2021.2018875.

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