Joef Stefan Institut Ljubljana Slovenia Energy Efficiency Centre

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

RES Industry - main drivers for projected GHG emissions Value added VALUE ADDED Energy intensity [1, kt] Efficiency PRODUCT Product Electricity District heat Efficiency Electricity 1 -35 k. V Electricity 110 k. V Low temp. heat Process heat USEFUL ENERGY Electricity ind. Low temp. heat ind. Hydro en. Steam Fuels TR Fuels FE FINAL ENERGY [TJ/1, TJ/kt] S, I Boilers Market share Aluminum electrolysis Industrial CHP Ind. Electr. distribution Industrial hydro PP Electr. arc furnaces steel Standard technology Improved technology COSTS CO 2, CH 4, N 2 O, SO 2, NOX Efficiency Emis. factor EMISIONS FUELS BOILERS HEAT demand Ind. heat distribution Electricity distribution Electrical motors Heat distribution Elec. proc. & applian. Steam distribution Space heating Market share JSI Energy Efficiency Centre S, I Factor [mio. SIT/1, mio. SIT/kt] S, I Market valuation S, I Thermal processes Non energy use

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) Market shares = modal split Fuel Efficiency Vehicle Emissions Emis. factor km Cars Standard Load factor Passenger cars Buses Cars Improved pkm Passenger trains JSI Energy Efficiency Centre Public transport

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 doublecounting 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 ) JSI Energy Efficiency Centre