Models and Scenarios Towards 2050 Perspective- The National Modelling Level

Transcription

1 MILESECURE-2050 Multidimensional Impact of the Low-carbon European Strategy on Energy Security, and Socio-Economic Dimension up to 2050 perspective Models and Scenarios Towards 2050 Perspective- The National Modelling Level WP4 tasks, by Zygmunt Parczewski & Adam Umer IEn & EnergSys, Poland EUROPEAN SOCIETIES FACING ENERGY TRANSITION The challenge of the human factor and energy security, up to 2050 Rome, February 17-18, 2015 This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no

2 Models and Scenarios Towards 2050 Perspective- The National Modelling Level 2 Table of contents Introduction (key issues; differences vs. similarities) Methodological approach general scheme SMET fuzzy model main features General scheme LCE- technologies Energy security & BM CGE-FEU and MESO-Impact main results

3 Models and Scenarios Towards 2050 Perspective- The National Modelling Level 3 Introduction Societal energy transition at National level - Key issues: Significant differences in socio-economic development and welfare need different treatment and distinct modelling (DE vs. PL) Significant differences in energy mix and balances (clean dirty; imported own; more political vs. market oriented, ) Societal aspects in NMS 12 are very new (innovative vs. ) Local democracy (communes) - still not enough active (very short history and unfavourable political system, DK vs. PL)

4 Significant differences in socio-economic development The National Modelling Level 4 Introduction- Socio-economic development An analysis and evaluation of the EU states development coherence some social and economic aspects (CLAN report, Nov. 2014) The results of EU states clusters - complete set of 67 diagnostic variables; data for 2012 The results of EU states clusters sub-set of 43 socio-cultural variables; data for 2012 General conclusions (based on data sets): a) Significant economic changes has occurred (NMS 10 vs. EU 15) b) Socio cultural changes proved to be much more stable (resistant to changes)

5 Significant differences in socio-economic development The National Modelling Level 5 Introduction- Socio-economic development Source: Self-analysis on the basis of Credit Suisse Global Wealth Databook 2013

6 6 CO2 emission how to bridge the gap? (social behaviours, ) Introduction- Socio-economic development CO2 emissions (EU 28) WP1: Deliverable 1.4; Data source:

7 Models and Scenarios Towards 2050 Perspective- The National Modelling Level 7 Macro- models applied national level Methodological approach general scheme & SMET highlights

8 8 Socio-economic macro-modelling Methodological approach general scheme IMACLIM Key assumptions: Demography, Accumulation rate, Productivity, other EnS-Macro (growth model) International fuel and ETS carbon prices paths Labour force; Capital stock Techno-limits paths, costs and pace of their implementation: RES energy supply techno. FEU (residential + transport) (National economy) CGE-FEU (base year 2010) Country GDP GVA structure Energy prices Employment CO2 emissions Households income Production by sectors Wages FEU-module (Final Energy Use technologies in residential and transport sectors) WP3 human factors transformation SMET (fuzzy model) Market penetration LCE technologies data gathering and S-curves estimation Meso-Impact modules (industry, households) General idea of CGE FEU modelling process (national level analysis) by EnergSys and IEn

9 9 Socio-economic modelling SMET fuzzy model general idea Societal Energy Transition Societal Factors by E, S, P domains (WP2 & WP3) Societal processes (WP3 out ~ WP4 inp Consolidating societal input data into quantitative parameters WP4 Modelling approach, analyses, verification and validation issues P1 E3 P3 Option 1 SMET outputs: LCE-technologies S7 Option 2 SMET (Socio Metric Energy Transition fuzzy Model) (S-curve saturation level RES vs. SOS) Societal parameters IMACLIM-R (EU 28) & S5 En S1 Option 3 (S-curve pace of implementation country specific) Institutional inertia Other, CGE model (EU states) DE, IT PL E6 Pk Iterative process (if necessary)

10 10 Socio-economic modelling SMET fuzzy model highlights (LCE-technologies) Saturation levels country specific (Dedicated softwares: R, STATISTICA, Excel) Different implementation pace (country specific) 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 "Natural" Path "Forced" path "Scenario" path

11 11 Socio-economic modelling SMET fuzzy model highlights (LCE-technologies) A1- Production and delivery of energy 1. Wind farms onshore 2. Wind farms offshore 3. PV-Big solar farms 4. Other LCE technologies e.g. Adv_CCGT, A3 Other energy customers public & business 15. Thermo-modern. public & commercial buildings 16. Shift: road freight transport train 17. Liquid biofuels 18. Hybrids & EV vans and buses A2 Individual energy use by households 5. Thermo-modern. buildings 6. New H-efficient buildings 7. Passive buildings 8. PV (small) 9. Solar panels 10. Small wind turbines 11. H-efficient electrical appliances 12. Shifts: car public transport (urban & trains) 13. Shift: car bikes & walk 14. Hybrid & EV cars

12 12 Socio-economic modelling SMET fuzzy model highlights - energy security Power security balancing (daily, seasonal) country specific: 1. Security margin ~ share of intermittent RES in total Net Gen. Capacity 2. Structure of Net Generating Capacity Nuclear energy Thermal power S & M units Renewables Intermittent sources (wind + pv) Thermal power large units Secure power units structure (by fuels and capacity units) Other RES, e.g. Bio- Assumed max. share of installed RESintermittent capa.

13 13 Socio-economic macro-modelling CGE-FEU OUTPUTS - validation BM scenarios (EU documents) EU states EU 27 Milesecure scenarios (Imaclim & CHGE-FEU) Categories: - Demography - Economy - Energy - Emissions - Prices Definition of indicators Milesecure outputs & BM Indicators comparison Categories: - Demography - Economy - Energy - Emissions - Prices Ok? No STOP Yes

14 CGE-FEU and MESO-Impact main results The National LCE- scenarios outputs 14 Key R& D results: EU states: DE, IT, PL in foresighted period of CGE-FEU & SMET: First time societal energy transition impact will be modelled taking into account advanced results of human energy concept GDP growth rates and the national economies structural changes influenced by LCE scenarios Societal energy transition impact on supply and demand side techno-impl. MESO-Impact modules (linked to CGE-FEU outputs): Changes of energy costs in energy-intensive branches (CL-phenomenon threaten) Changes of households energy costs vs. fuel poverty The EU state representatives position on energy transition cost curve to be build

15 15 Thank you for attention Zygmunt Parczewski & Adam Umer IEn & EnergSys; WP4 team