Modifications of the GEMINI-E3 model

For the purpose of the coupling with CROSSTEM and as it is done in the GENESwIS model, we have disaggregated the GTAP electricity sector into two sectors, respectively "Electricity generation" and

"Electricity transport and distribution". We assume that the output of the Electricity generation sec-tor is only consumed by the Electricity transport and distribution secsec-tor, which distributes the electri-city to all users (firms and households) and trades electrielectri-city with neighbouring countries.

In contrary to the GENESwIS model, it was not possible to use the Input-Output table to calibrate the two sectors. Indeed the Input-Output tables of the GTAP database do not disaggregate electricity generation and electricity transport and distribution. We implemented the procedure described in Figure 76 to calibrate the electricity generation and distribution sectors:

Figure 76: Calibration of the base year in GEMINI-E3 electricity generation and distribution sectors

1. Calibration of the electricity generation sector:

a. Fuel inputs (coal, natural gas, oil and nuclear fuels) are equal to the values given by the CROSSTEM database;

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b. Operation and maintenance (O & M) costs are equal to the figures of the CROSSTEM model, they are disaggregated between labor and inputs from sectors 6 to 14 using the shares computed from the GTAP database for the electricity sector as a whole;

c. Trade of electricity between countries is also given by the CROSSTEM database;

d. Capital remuneration is equal to the capital annuities given by CROSSTEM;

e. Taxes on nuclear fuel and fossil energy are computed from CROSSTEM;

f. The production level minus imports is assumed to be consumed only by the electrici-ty and transmission sector (minus exports).

2. Calibration of the Electricity transport and distribution sector:

a. The final uses (excluding exports and imports, which are supposed to be zero) are equal to the figures coming from the GTAP database;

b. Energy inputs excluding electricity consumption are equal to zero;

c. Electricity consumption is equal to the value of the GTAP database and represents the own uses and losses;

d. Other intermediate consumptions are equal to figures coming from the GTAP data-base minus the intermediate consumptions by the electricity generation sector;

e. The same procedure is applied to labor remuneration (i.e. labor remuneration is equal to labor remuneration of the electricity sector as a whole minus the labor remuneration of the electricity generation sector);

f. VAT and other indirect taxes are equal to the GTAP figures;

g. The difference between resources and uses is added to the capital remuneration in order to balance the accounting representation of the sector.

At the end of the procedure, the two sectors are balanced but some discrepancies with the GTAP database remain regarding:

• Fossil energy consumption is not balanced at the national level, as the figures are coming from the CROSSTEM database;

• Electricity trade differs from the GTAP figures;

• Capital remuneration of the electricity sector.

The balancing of the economy is performed by solving the GEMINI-E3 model, therefore the repre-sentation of the calibration year is slightly different from the one of the GTAP database.

3.2.3.2.1 Dynamic calibration

The previous section describes the calibration of the two new sectors that have been introduced in GEMINI-E3 for the year 2007. Furthermore, it was necessary to implement a “dynamic calibration”

on the simulation period (2007-2050) to be sure that the two models share a common and consistent view of the future of the European electricity market. The following variables have been harmonized between the two models:

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• the price of energy commodities: coal, oil and natural gas,

• the electricity demands.

3.2.3.2.2 Further modifications to enable the linking of GEMINI-E3 and CROSSTEM We follow the methodology that has been developed for the coupling between CROSSTEM-CH and GENESwIS. The energy mix and other inputs (O & M costs, capital remuneration) computed by CROSSTEM are introduced into GEMINI-E3 by removing the nested CES functions representing the production of the electricity generation sector. The CES functions are substituted by Leontief func-tions where the shares are computed from the CROSSTEM inputs. To disaggregate O & M cost between labor and intermediate consumptions by products (i.e. metals, energy intensive industries, rest of industry, construction etc.), we use the GEMINI-E3 shares.

A similar procedure is applied for the electricity trade; the respective Armington functions are replaced by Leontief functions.

CROSSTEM provides its output for every 5 years (2010, 2015, 2020, ...): As GEMINI-E3 is a CGE with subsequent annual periods, the intermediate annual values are computed by linear interpolations between the periods that are explicitly represented in CROSSTEM.

3.2.3.2.3 GEMINI-E3 stand-alone versus GEMINI-E3 with energy mix coming from CROSSTEM

In this section, we present a preliminary coupling that aims to demonstrate the feasibility of the full coupling already demonstrated within the Swiss ELECTRA framework. This coupling is a preliminary step, because only the energy mix coming from CROSSTEM is implemented in the GEMINI-E3 model.

It is also a one way coupling, as the demand computed by GEMINI-E3 is not reintroduced into CROSSTEM. Neither is the electricity trade computed by CROSSTEM coupled with GEMINI-E3, which computes electricity trade with its own equations.

We performed two runs:

1. The first one is based on a stand-alone version of GEMINI-E3 but where the representations of the electricity sectors are calibrated with data coming from the CROSSTEM model (see section 3.2.3.2). The nested CES function used for the electricity sectors (generation, and transmission and distribution) retains the substitution elasticities of the GEMINI-E3 standard version.

2. The second one builds on the energy mix of the electricity generation sector as computed by the CROSSTEM model. In this case, we assume that the elasticities σoth, σe and σef reported in the Figure 39 are equal to zero (i.e. the three CES functions become Leontief functions). The coefficients representing the shares of the Leontief functions are given by the CROSSTEM model.

The scenarios presented hereafter assume that a carbon price is implemented in the power sector which is equal to the one reported in Table 11. Also, we have harmonized between the two models the world energy prices and the electricity demands. Nevertheless, the models have two different assumptions concerning CCS technology and the German nuclear moratorium. GEMINI-E3 does not integrate any penetration of Carbon Capture and Storage technology, in contrary to CROSSTEM.

CROSSTEM assumes that a nuclear moratorium is implemented in Germany, which is not the case in

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the GEMINI-E3 runs. Finally, as GEMINI-E3 does not represent explicitly renewable and nuclear power plants, we compare the fossil energy mix computed by the two models (GEMINI-E3 stand-alone vs. the coupled models).

Figure 77 gives for the four countries (Austria, Germany, Italy and France) the fossil energy mix computed by the two models for the years 2010, 2020, 2030, 2040 and 2050.

In 2010, the two models give similar results. Indeed, GEMINI-E3 alone is calibrated from the energy mix coming from CROSSTEM for the calibration year 2007. After the first periods of the simulation, however, the two models diverge and give completely different results. In the long term, CROSSTEM finds a solution where only one fossil energy dominates the electricity generation: coal with CCS. In contrary to CROSSTEM, GEMINI-E3 represents a diversified fossil energy mix in Europe, where coal is gradually replaced by natural gas whose low carbon content limits the impacts of the carbon price.

These two different views of the future of European electricity generation come mainly from the availability of CCS in CROSSTEM, which is not assumed in GEMINI-E3. Nevertheless, these simulations demonstrate that CGE models like GEMINI-E3 tend to underestimate the possibility of substitution in comparison to bottom-up models like CROSSTEM, which maybe have a tendency to overestimate this substitution.

Figure 77: Electricity generation fossil energy mix in Mtoe.

At country level, Austria and Italy face similar dynamics. First, the total amounts of fossil energy con-sumption computed by the two models are similar in the two countries. As we already noticed, in GEMINI-E3 coupled with CROSSTEM fossil energy use is almost fully represented by coal with CCS. In contrary, the GEMINI-E3 stand-alone run shows a mix dominated by natural gas where coal contri-butes respectively only 33% and 18% to the fossil energy consumption in Austria and Italy.

The German case in the coupled version is mainly driven by the nuclear moratorium where nuclear power plants are replaced by renewables and coal. In contrary, the stand-alone GEMINI-E3 version assumes that nuclear power still contributes to German electricity generation.

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In France, the two models find that fossil energy contribution to electricity generation remains limi-ted in the future (it is less than 10% in 2012). This contribution is divided by two in the coupled version and mainly represented by coal with CCS. In the stand-alone version this contribution also decreases and remains dominated by natural gas.