1. “Towards more sustainable heating system in the
City of Niš, Serbia"
Bojan Gajić
Marija Živković

2. The goal of "participatory
backcasting 'project in Nis
was to develop a long-term
strategy aimed to ensure
the thermal comfort
(heating and cooling) for
the citizens of Nis up to
2030.

3. Why the city needs long-term planning
of energy consumption?
• energy insecurity (import
dependency)
• negative impact on the
environment;
• low efficiency (direct usage
of electricity for heating)2010 2030
+40%
BAU (‘business-as-usual’) scenario
Increased energy demand
Increase of C02, CO, Nox emissions
Increased electricity consumption for heating
The reason for the project s realization was dissatisfaction with the possible
development of heating systems, which would led to continuation of existing
practices (presented BAU scenario), which is characterized by:

4. Stakeholders
involved City Council of Nis
Division for Sustainability of the Department for
Commerce, Sustainable Development and Environment
Department of City Planning
Division for Energy of the
Department of Energy
Department for Planning and Construction
Energy Efficiency
Council of the City of Nis
City Municipality
Palilula
City Municipality
Pantelej
City Municipality
Crveni Krst
Faculty of Mechanical
Engineering, University of Niš
University of Kragujevac
University
of Belgrade
Organization of citizens
consumers of district
heating system
Center for
Consumer
Protection
Citizens representatives
Yugo-impexNIS company
Public District Heating Company
Arhus centar Južne i Istočne Srbije
ELDI Nis

5. Workshop #3
20. February 2015.
Workshop #2
27. June 2015.
Workshop #1
4. April 2014.
Final Report
May 2015.
Interviews
March2014
Time frame

6. Without fossil fuels in the
district heating system 2030
//Getenburg
Without using oil for heating
dervivata to 2030//Danska
Decreased heat demand 30-50% until
2030
//Heat Roadmap Europe
Reduction of fosil fuel
consumption in buildings:
• 80% in 2020
• 90% in 2025
• CO2 neutral in 2030
//Architecture 2030
“Affordable, comfortable and
environmentally friendly heating and
cooling in the city of Nis by 2030”

7. Criteria 4
Comfort

8. Criteria 1
Reliability and
availability
Reliabilityandavailability
Subcriteria Assessment Value in 2014 General target
Reliability The number of
days (hours) in the
heating season
without heating
n/a Reducing the
number of days
(hours) without
heating
The number of
failures during the
year
n/a Reducing the
number of failures
during the year
Availability of
cooling system
% of households
that has the ability
of cooling
n/a Increase of %
Energy security Number and
structure of fuel
used
5 (coal, wood, oil,
natural gas,
electricity)
Introduction of
new energy
sources for heating
Energy security The percentage of
fuel from domestic
sources in the
energy mix
63.6% Decrease of import
dependency
Energy security The percentage of
locally available
energy sources in
26.3% Increased use of
locally available
energy sources

9. Criteria 2
Affordability
Affordability
Subcriteria Assessment Value in 2014
General
targetEnergy sources Wood Electricit
y
District
heating
for consumers
heating
% of the average
revenue from the
region required
for heating, per
month
10,7% 7,5% 13,3% Costs
reduction
for consumers
cooling
% of the average
revenue from the
region required
for cooling, per
month
3,7% Costs
reduction
Producers and
distributors
Normalized
percentage of
profitable
companies
n/a Increase of
% of
profitable
companies

10. Criteria 3
Environmentally
acceptable
Environmentallyacceptable
Subcriteria Assessment Value in 2014 General target
Relative
emissions
CО2
kg CO2/kWht
0,3623 Reduction of 27%
compared to the BAU
kg CO2/m2
34,13 Reduction of 27%
compared to the BAU
Emissions
CO kg CO/kWht
0,0055 Reduction of 20%
compared to the BAU
Emissions
NOx kg NOx/kWht
0,355*10-3 Reduction of 20%
compared to the BAU
Emissions
SOx kg SOx/ kWht
0,305*10-3 Reduction of 20%
compared to the BAU

11. Comfort
Subcriteria
Assesment Value in 2014 General
target
Thermal comfort
Survey 80% To improve
the level of
comfort
Safety
Survey 78% To improve
the level of
comfort
Easy to operate
Survey 68% To improve
the level of
comfort
Criteria 4
Comfort

12. Energyefficiency
Subcriteria Assesment
Value in
2014
General target
Efficiency of production
and distribution
Production efficiency in the
district heating system%
Losses in the distribution
network,%
85%
14%
To achieve
optimal value
Efficiency of
transformation
kWh of primary energy
/ KWh of thermal energy
1,515
Reduction of
20%
Specific annual energy
consumption in buildings
kWht/м2 per annum 94,19
Reduction of
20%
Criteria 5
Energy efficiency

14. S1. “Advanced
nature-based”
S2. “Advanced
renewable-based”
S3. “DH expansion +
building efficiency”
S4. “DH expansion
based on renewables”
S5. “Nature focused
individuals”
Selected scenario
Developed scenarios
Developed scenarios
are based on the
outcomes of the 1st
and 2nd workshops
with stakeholders
(solutions testing
against criteria and
robustness test) and
results of the
modelling in LEAP
software, performed
by the researchers.

15. Urban energy system modelling in the
PB project in Nis

17. S1. “Advanced nature-
based”
• Improving the energy
efficiency of existing buildings
to C class
• Class B for new facilities to
the year 2030.
• The application of SMART
technology.
• Insisting on individual
solutions.
• Limited expansion of district
heating network
• The application of green
architecture, wherever
possible

18. S2. “Napredni – zasnovan na
obnovljivim izvorima”
• Improving the energy efficiency of
existing buildings to C class
• Class B for new facilities to the
year 2030.
• The application of SMART
technology.
• Insisting on individual solutions.
• Limited expansion of district
heating network
Scenario 2=
Scenario 1-
Green architecture

19. S3. “DH expansion + building
efficiency”
• Improving the energy efficiency of existing
buildings to C class
• Class B for new facilities to the year 2030.
• The expansion of district heating network
• Connecting new consumers.
• Substitution of electric energy
• Without the application of SMART technology

20. S4. “DH expansion based on
renewables”
• Minor improvement of energy
efficiency of existing buildings to
D class
• The expansion of district heating
network
• Connection of new consumers
• Substitution of electricity for
direct heating
Scenario 4=
Scenario 3-
Significant energy efficiency improvement

21. S5. “Fokus na primeni zelene
arhitekrure i individualnim
rešenjima za grejanje”
• Improving the energy efficiency of
existing buildings to C class
• Class B for new facilities to the
year 2030.
• The application of SMART
technology.
• Insisting on individual solutions.
• Without the district heating
system in 2030
• The application of green
architecture
Scenario 5=
Scenario 1-
Centralized heat supply system

22. Izabrani scenario
Efficiency for green future

24. Selected
scenario
0
100
200
300
400
500
600
700
800
Wood
Heavy oil
Natural gas
Heat
Geothermal
Electricity
Subbitumenous
coal
Biomass
Izabrani scenario
GWh/annumi
Final energy for heating
• Combination of scenarios 3 +
5
• Improving the energy
efficiency of existing
buildings to Class C
• The new facilities Class B
• Expansion of heating network
and connection of new
consumers (multistorey
buildings)
• Natural gas for peak loads

25. 0
50
100
150
200
250
300
C02 emissions, by source
Emission related to electricty generation used for heat pumps
Emission related to electricty generation used for direc
heating
Final energy consumption
Combustion in DH system
0
100
200
300
400
500
600
District heating, by fuel
Residual fuel oil Natural gas
Biomass Electricity (for heat pumps)
Geothermal Municipal solid waste
Gigawatt-
hours/year
In the base year, 29.7% of the energy required for heating is
provided by district heating systems. In 2030 it is envisaged that 53%
of the energy needed for heating provided by district heating
systems.
The base year in the district heating system is not used for the
production of renewable heat. In 2030 it could 63% of energy could
be produced by using RES.
Gigawatt-
hours/year Selected scenario
.

26. Comparison of developed scenarios by fuels used in 2030
0 100 200 300 400 500 600 700 800 900 1000
BAU scenario
Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Selected
scenario
Gigawatt-Hours
Biomass Coal Sub bituminous Electricity Geothermal Heat Natural Gas Residual Fuel Oil Wood
Selected
scenario
BAU
scenario

27. 0
100
200
300
400
500
600
700
BAU scenario Scenario 1
Scenario 2 Scenario 3
Scenario 4 Scenario 5
Selected scenario
Comparison of
developed scenarios
by fuels used in 2030Selected scenario
Gigawatt-
hours/year

28. 0
20
40
60
80
100
120
140
Nitrogen Oxides (NOx)
BAU Solution 1
Solution 2 Solution 3
Solution 4 Solution 5
Izabrani scenario
0
1000
2000
3000
4000
5000
6000
Carbon Monoxide (CO)
BAU Solution 1
Solution 2 Solution 3
Solution 4 Solution 5
Izabrani scenario
Tonnes Tonnes

29. 21%
6%
7%
16%
20%
37%
10%
BAU
Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Izabrani
Import dependence of the
heating system in the city
of Nis in 2030

30. Reliabilityandavailability
Reliability for consumers
number of days (hours) in
the heating season without
heat
Reliability
Number of failures per
year
Availability of cooling
% of households that have
cooling
Energy security
Number and structure of
fuel used
5 (coal, wood, oil, natural
gas, electricity)
Introduction of new energy
sources for heating
+ geothermal, waste
heat and municipal
solid waste
The percentage of fuel
from domestic production
in the energy mix
63.6% Decrease of import
dependency 83,7%
The percentage of locally
available energy sources in
the energy mix
26.3 Increased use of locally
available energy sources 71,4%
Targets
Subcriteria Assessment Value 2014 General target Selected scenario
No data

31. Affordability
For consumers
heating
% of the average revenue
from the region required
for heating, per month
Wood 10,7 7% Europe
Electricity 7,46 7% Europe
DH 13,3 7% Europe
For consumers
cooling
% of the average revenue
from the region required
for cooling, per month
3,7%
For producers and
distributers
Normalized percentage
of profitable companies
Targets
No data
Subcriteria Assessment Value 2014 General target Selected scenario

32. Environmentally
acceptable
kg CO2/kWht 0,3623 Reduction of 27%
compared to the BAU
0,201
Reduction 45%
kg CO2/m2 34,13 Reduction of 27%
compared to the BAU
11,58
Reduction 66%
kg of CO/kWht 0,0055 Reduction of 20%
compared to the BAU
0,0047
kg of NOx/kWht 0,355*10-3 Reduction of 20%
compared to the BAU
0,106*10-3
kg of SOx/ kWht 0,181*10-3 Reduction of 20%
compared to the BAU 0,039*10-3
Targets
Subcriteria Assessment Value 2014 General target Selected scenario

33. Comfort
Thermal
comfort
Survey 80% 80%
Safety Survey 65% 80%
Easy to operate Survey 74,2% 80%
Targets
Subcriteria Assessment Value 2014 General target Selected scenario

34. Energyefficiency
Efficiency of
production and
distribution
Efficiency of DH
production % 85% Optimal value
Distribution losses, % 14% Optimal value
Efficiency of
transformation
kWh primary/ kWh
thermal 1,585 Reduction 20% 0,632
Efficiency of Buildings kWh t/m2 annualy 94,19 Reduction 20% 62,75
Targets
Subcriteria Assessment Value 2014 General target Selected scenario

35. BAU vs selected scenario in context of
European energy policy
Specific heat demand in the EU-EE scenario for the residential and service
sectors, as well as for the space heating, hot water and total heat demand.
selected scenario
(62.75 kWh/m2)
BAU scenario
(94.2 kWh/m2)
//Figure is adopted from ‘Heat Roadmap Europe. Second pre-study for the EU27’ report (2013)
selected scenario
PEF: 0,632
C02: 201 g/kWh
BAU scenario
PEF: 1,585
C02: 393 g/kWh
//Figure is adopted from ‘District Heating in Buildings’ report, Euroheat & Power (2011)
Correlation of Primary energy factors (PEF) and CO2 emissions
for different heating solutions and cities in whole
PEF
kWh/m2

38. Thank you!
Dr Marija A. Živković, assistant professor
University of Belgrade-Faculty of Mining and Geology
marija.zivkovic@rgf.bg.ac.rs