11.3.3 Studies of interactions between energy supply and demand

This section looks at literature dealing specifically with the modelling of interactions between energy supply and demand. It first considers the carbon content of electricity, a crucial feature of the cross-sectoral aggregation of potentials discussed above, and then the effect of mitigation on energy prices. The studies emphasize the dependence of mitigation potentials from end-use electricity savings on the generation mix.

11.3.3.1 The carbon content of electricity

As discussed above, there are many interactions between CO₂ mitigation measures in the demand and supply of energy. Particularly in the case of electricity, consumers are unaware of the types and volumes of primary energy required for generating electricity. The electricity producer determines the power generation mix, which depends on the load characteristics. The CO₂ mitigation measures not only affect the generation mix (supply side) through the load characteristics. They are also influenced by the price.

Iwafune et al. (2001a; 2001b; 2001c), and Kraines et al. (2001) discuss the effects of the interactions between electricity supply and demand sectors in the Virtual Tokyo model. Demand-side options and supply-side options are considered simultaneously, with changes in the optimal mix in power generation reflecting changes in the load profile caused by the introductions of demand-side options such as the enhanced insulation of buildings and installation of photovoltaic (PV) modules on rooftops. The economic indicators used for demand-side behaviours are investment pay-back time and marginal CO₂ abatement cost. Typical results of Iwafune et al. (2001a) are that the introduction of demand-side measures reduces electricity demand in Tokyo by 3.5%, reducing CO₂ emissions from power supply by 7.6%. The CO₂ emission intensity of the reduced electricity demand is more than two times higher than the average CO₂ intensity of electricity supply because reductions in electricity demands caused by the saving of building energy demand and/or the installation of PV modules occur mainly in daytime when more carbon-intensive fuels are used. A similar ‘wedge’ – in this case between the average carbon intensity of electricity supply and the carbon value of electricity savings – was found, in the UK system, to depend upon the price of EU ETS allowances, with high ETS prices increasing the carbon value of end-use savings by around 40% as coal is pushed to the margin of power generation (Grubb and Wilde, 2005).

Komiyama et al. (2003) evaluate the total system effect in terms of CO₂ emission reduction by introducing co-generation (CHP, combined heat and power) in residential and commercial sectors, using a long-term optimal generation-mix model to allow for the indirect effects on CO₂ emissions from power generation. In a standard scenario, where the first technology to be substituted is oil-fired power, followed later by LNG CC and IGCC, the installation of CHP reduces CO₂ emission in the total system. However, in a different scenario, the CO₂ reduction effect of CHP introduction may be substantially lower. For example, the effect is negligible when highly efficient CCGTs (combined cycle gas turbines) are dominant at baseline and replaced by CHP. Furthermore, in the albeit unlikely case of nuclear power being competitive at baseline but replaced by CHP, the total CO₂ emission from the energy system increases with CHP installation. These results suggest that the CO₂ reduction potential associated with the introduction of CHP should be evaluated with caution.