Supply of fuels
The inverse supply function P = AeB(t)S+D(t)S is used for coal, oil, gas, biofuels and biomass, where P is the price, S is supply and A, B(t) and D(t) are parameters. Note that B(t) and D(t) may be time dependent. In general the parameters differ across countries, but A is the same for all countries (the only exception is biomass where A is country specific). The magnitude of B(t) and D(t) generally reflects how quickly marginal costs rise as output increase.
The coal supply is modelled separately for the three types of coal; steam coal, coking coal and lignite. The base year supply of coal for all model countries is taken from the IEA Extended Energy Balances database. Steam coal is the sum of anthracite, other bituminous coal and sub-bituminous coal, whereas lignite is the sum of lignite and peat.
The inverse supply functions for coal are calibrated so that the supply elasticities in the base year are equal to 2 in the long run and 0.5 in the short run. This applies to both model countries and exogenous countries.
The parameters in the inverse supply functions are adjusted over time in accordance with projections from World Energy Outlook 2011 (IEA 2011). For lignite it is assumed that production declines with 4 % a year for all model countries.
The base year supply data for natural gas is taken from the IEA Extended Energy Balances database. In the model there is a differentiation made between countries that are large gas suppliers to Europe (Russia, Norway, Netherlands, Algeria and the UK), and the remaining countries.
For the five large gas suppliers the future supply is split into “existing fields”, which consists of fields that were in operation in the base year, and “new fields”. To distinguish between existing and new fields, unofficial data from Rystad Energy has been used. For the “existing fields”, an inverse supply function is calibrated setting D(t) = 0. The parameter B(t) is changed over time reflecting projected depreciation rates according to the data from Rystad Energy. For the new fields, inverse supply functions are calibrated (these also vary over time), again based on the data from Rystad Energy.
For the remaining model countries the inverse supply functions are calibrated based on the market equilibrium in 2009, where a common gas price (P) of 280 $/toe (7 $/Mbtu) is assumed. This price is just below the average CIF price in the EU in 2009 (which was 8.5 $/Mbtu), and also lower than the price in all years between 2006 -2010, but above the prices in all years prior to 2006. The supply elasticity in the base year is set to 0.75. This is lower than for oil, reflecting that gas is more dependent on infrastructure. For Poland supply of shale gas is phased in as of 2020.
The base year supply of oil is taken from the IEA Extended Energy Balances database. This database has data for all the model countries. The production of crude oil (the sum of crude oil, natural gas liquids, refinery feedstock, additives and other hydrocarbons, as classified by the IEA), minus the “own use” (which is the “oil and gas extraction” under “energy industry own use”) is used. The inverse supply functions for oil are calibrated so that the implicit supply elasticities in the base year are equal to 1 in the long run, whereas in the short run these are 0.25 of the long-run elasticity. This applies to both model countries and exogenous countries. The parameters in the inverse supply functions are adjusted over time in accordance with projections from World Energy Outlook 2011 (IEA 2011).
The base year supply of biofuels for the model countries is taken from the IEA Extended Energy Balances database and is an aggregate of bioethanol and biodiesel. It is assumed that annual biofuels supply has a growth rate of 2.2 %, again based on IEA (2011).
The supply of biomass is based on data from Biomass Futures (2012). This source has supply curves for EU27 (information about type of biomass, costs in €/toe and potential ktoe). This source is used to calibrate parameters for each model country (A, B(t) and D(t)). For Norway Scarlat et al. (2011) has been used, supplemented by ENOVA SF (2008) and Hobbelstad (2009), to estimate the potential. The cost data for Norway is based on data from Sweden . For Iceland and Switzerland own assumptions were made based on data from other European countries.