1. University of Belgrade-Faculty of mining and geology
Participatory Backcasting Approach in Energy Planning –An Experience from the City of Niš
Marija Zivkovic
Assistant professor
University of Belgrade-Faculty of mining and geology
The 7th International Scientific Conference on Energy and Climate Change,
Athens, 8-10 October, 2014.

2. Three classes of scenarios
What will happen?
What could happen?
What should happen?

4. Participatory backcasting project for the heating system of Nis
Figure 1. Heating system interpretation according to process-based approach (Kordas et al., 2013)
Figure 2. Algorithm of the Participatory backcasting project for the heating system of the city of Nis

5. Participatory backcasting project for the heating system of Nis
WORKSHOP I
Current state overview
Problem analyses,
Visioning (consensus among stakeholders)- qualitative description
Criteria determination and ranking (consensus within groups)
Inventory of drivers and their influence to the future system,
Determination of key uncertainties,
Stories of the future, by groups that consists from stakeholders with the same roles (for example: consumers, local authorities, producers, etc…)
WORKSHOP II
Weighting of criteria,
Selection of two key uncertainties,
Scenarios testing against criteria,
Robustness test,
Scenario(s) selection,
Pathway development.

6. Current state overview and problem analyses
Figure 3.Structure of final energy consumption
for the heat demand
in the household sector in 2010.
(Sustainable Energy Action Plan for the City of Nis)
Figure 4.Structure of final
energy consumption for the heat demand
in the public sector in 2010.
(Sustainable Energy Action Plan for the City of Nis)

7. Household sector 90,3 kg CO2/m2

8. Vision Criteria development
"Affordable, comfortable and environmentally friendly heating in the city of Nis".
Criteria development
What the future system should fulfill?

9. Criteria with subcriteria

10. Criteria ranking Reliability and availability Affordability
Group 1
Group 2
Group 3
Reliability and availability
0,35
0,30
Affordability
0,25
Environmental acceptance (environmentally friendly)
0,10
0,15
0,20
Comfortable
Energy efficiency

12. Driver analysis High trends key uncertainties Political situation
Price of energy
Availability of energy sources
Demography
Price of energy
Policy influence
Availability of energy sources
Standard of life
Policy influence
Life standard
Investment
Legislation
Legislation
Climate change
Technical Solutions
Climate change
Technical and technological progress
Demography
High
Low
uncertainty
Education
Population growth
Education
Impact
Driver analysis
Population
Awareness of citizens as users
Low 12

13. Options for solutions Level of centralization Basic/Input resources
Advancement of technology
Energy efficiency of buildings
Natural-focus
Expansion of DH % multystory+privat (Fully connected system)
Individual solutions
Fossile fuels
Renewable resources
Low tech
High (smart) technology
Low
Passive buildings,
Not focused
Fully focused

14. Solution 1 “Advanced nature-based”
Individual-based + not expanding of DH
Renewables + Natural gas (for pick demand)
Smart technology
Passive for new and maximum possible efficiency for old buildings (retrofitting)
Nature focus

15. Solution 2 “Advanced renewable-based”
No nature focus
Passive for new and maximum possible efficiency for old
Smart technology
Renewables + Natural gas (for pick demand)
Individual-based (no expanding DH)

16. Solution 3 “DH expansion + building efficiency”
No nature focus
Passive for new and maximum possible efficiency for old
More advanced technology introduced (co-generation, etc)
Renewables (waste incineration+biomass CHE, heat pump on geothermal and waste water, solar accumulators)+natural gas (pick demand)
DH expansion

17. Solution 4 “DH expansion based on renewables”
No nature focus
Efficiency of building is almost the same as it is now (Example: new buildings – standard “C”, minor improvements for old buildings)
More advanced technology introduced (co-generation etc)
Renewables-based Examples: waste incineration & biomass-based CHE, heat pump on geothermal and waste water, solar accumulators + natural gas for pick demand
DH expansion and connection to the maximum (covers even private sector of the city)

18. Solution 5 “Nature focused individuals”
Passive for new and maximum possible efficiency for old
Smart technology
Renewables (as much as you can) + natural gas
Fully individual-based

19. Scenario of support - high level of political will of the implementation of laws and regulations that promote the modernization of the heating system, the application of renewable energy, etc. There have been developed support mechanisms, but the economic development isn’t intensive.
Extremely positive scenario - the political will of the implementation of laws and regulations that promote the modernization of the heating system, the implementation of renewable energy with a higher standard of living and higher incomes, ie. intensive economic development. Highly increasing energy efficiency by supporting investments in improvements technology in the sector of construction.
Political will– high level
Economic Development – non intensive
Economic Development – intensive
Scenario of economic development - political will of the implementation of laws and regulations that promote the modernization of the heating system, the application of renewable energy, etc. is low. There are no developed mechanisms of support, even though the intense economic development, it is lack of adequate supporting results in terms of modernizing the system and increase energy efficiency.
Extremely negative scenario - the political will of the implementation of laws and regulations that promote the modernization of the heating system, the application of renewable energy, etc. is low. Without the support with much lower standard of living and very low income.
Political will– low level

20. S4 S1 S2 S3 S5 Group 3 Politička volja – visok nivo
Ekonomski razvoj– slab
Ekonomski razvoj– intenzivan S3 S5
Group 3
Politička volja – nizak nivo

21. Present and future
Figure 5. Comparison of energy demand for heating in 2030, by scenario

23. Thank you for attention!