“Jožef Stefan” Institut, Ljubljana, Slovenia Energy Efficiency Centre Experiences with energy-related GHG projections for Slovenia Stane Merše M.Sc. UNFCCC Workshop on emission projection, Bonn. 6-8 September 2004

JSI Energy Efficiency Centre Industrial CHP Industrial hydro PP Ind. heat distribution Ind. Electr. distribution Space heating Boilers Non energy use Thermal processes Electrical motors Elec. proc. & applian. Electricity distribution Heat distribution Steam distribution Aluminum electrolysis Market valuation Electricity ind. Electricity Low temp. heat Low temp. heat ind.Electricity 1-35kV District heat Process heat Value added Product [1, kt] Factor [mioSIT/1, mioSIT/kt] Energy intensity [TJ/1,TJ/kt] Efficiency Market share Electricity 110 kV Electr. arc furnaces steel FINAL ENERGYUSEFUL ENERGY PRODUCT VALUE ADDED Hydro en. Steam Fuels FE S,I Fuels TR Standard technology Market share FUELS HEAT demand CO 2,CH 4, N 2 O, SO 2, NO X Improved technology EMISIONS BOILERS COSTS Efficiency Emis. factor S,I RES Industry - main drivers for projected GHG emissions

JSI Energy Efficiency Centre Modeling of GHG mitigation measures - INDUSTRY Technological progress: –Current best available technologies (BAT) –IPPC requirements (BREFs,...) Measures (on site energy efficiency improvments): –Decrease of compressed air networks leakages,... –Overall decrease of energy intensity: -0,5%/a (M&T,...) New technologies: –CHP, VSD,... Fuel switching Penetration of measures: –driven by legislation (IPPC, EU harmonization, etc.) –Cost benefit (economic signals) ?

JSI Energy Efficiency Centre Market penetration model for energy efficient technologies (spreadsheet)

JSI Energy Efficiency Centre Modeling of future changes in the modal split of transport Overall sector modeling –main drivers - transport demand (volume): Passenger-kilometers (pkm) Ton-kilometers (tkm) Passenger cars Passenger cars Buses Passenger trains Passenger trains Public transport Market shares = modal split pkm Vehicle km Efficiency Emis. factor Cars Standard Cars Standard Cars Improved Cars Improved Fuel Emissions Load factor

JSI Energy Efficiency Centre Impact of voluntary agreements ACEA Separate model of passenger car stock: –Official database data, grouped by: fuel type (gasoline - w/w.o. catalytic conv., diesel) Age (year of production) –future evolution: no. of new and eliminated cars/year, spec. fuel consumption of new cars (agreement ACEA) yearly mileage by group Aggregated input parameters for REES model

JSI Energy Efficiency Centre Conclusions Bottom up – technology oriented approach: –Enables consistent modeling of measures (without double- counting of savings) –Costs calculation: macroeconomic effects, necessary founds, budget resources,... –Data intensive: linking of statistical data and practical experiences (on site informations, international practice,etc.) improved monitoring, new data for modeling (ETS) –Implementation uncertainty: Gap between policy and measures implementation (forecasting of expected policy results )