A joint research program NTNU / SINTEF / MIT / IFE
2004 - 2007
The initiative for the Joint Research Program Alternatives for the Transition to Sustainable Energy Services in Northern Europe (TRANSES) came from MIT, Norsk Hydro and NTNU/SINTEF as a result of a meeting in May 2001. The main objective of TRANSES is to enable governments, industries and communities to meet their future energy service needs in a cost-effective and sustainable manner in a liberalized energy market environment.
Two major scientific tracks have been followed in parallel during the project: A techno-economic optimisation and analysis of the Nordic energy system with large computer models like EMPS and MARKAL, and a detailed study of energy demand and demand forecasting in Norway.
In order to create a sufficient number of strategies over a large variation of technology and policy options, a special multi-scenario setup was applied to create a total of 1152 MARKAL scenarios consisting of 18 unique futures (3 levels of energy demand growth, 3 levels of fuel prices and 2 different CO2 tax levels) and 64 unique strategies (2 levels of wind power, 2 levels of hydro power, 2 levels of nuclear power, 2 levels of coal and gas w/CCS technology, 2 levels of biomass and 2 different transport vehicle development). Rather than giving the model a set of alternatives and letting it choose the best strategies within given boundaries, we forced the model to apply given strategies and took the resulting system cost as input for further analysis. This enabled a huge spectre of different scenarios, compared to the handful of optimized development paths that would result from a "classic" scenario setup.
It is neither feasible nor desirable to identify a “single-option” strategy to achieve a reduction of GHG emissions and at the same time keep the overall system cost low. Strategies containing a mix of electric, thermal and transport options are needed. The multi-attribute trade-off analysis performed on the 1152 MARKAL scenarios shows that strategies containing a lot of biomass and biofuel/hybrid vehicles, large amounts of new hydropower, wind power and nuclear capacity perform best in the cost-emission space and are most robust with respect to the uncertain futures.
It is worth noting that the analysis was performed with system cost and CO2 emissions as main attributes. Especially the large scale nuclear option is very favourable in the "cost-emission space" but has other environmental concerns. If we define the term "sustainable" wider than the "low emissions" attribute used here, other strategies would be more preferable. Omitting the nuclear option, less CO2 emission reductions are possible in the Nordic system, and the cost increases. Also the option of a large scale utilization of currently restricted hydro power resources may not be easy to implement from a policy perspective. -dette avsnittet kan utgå
Another observation from the analyses is that direct cost for emissions in the form of CO2 quotas is a more effective instrument to reduce CO2 emissions than green certificates. However, CO2 quotas will also favour non-renewable capacity like nuclear and gas- and coal fired units with CCS, and will not contribute directly to a significant increase in the share of renewable energy as is the case with green certificates.
In order to give a credible forecast for future energy demand, the development of a new energy forecast model ePlan was based on the assumption that energy demand is the product of activity in society multiplied by energy intensity. In the residential and service sector, heated space floor area (m2) is a common measure of activity, and the respective intensity is then specific energy demand measured in (kWh/m2). In industry and "other" sectors, production values (NOK) are common activity measures, and respective intensities are measured in (kWh/NOK). To calibrate the model and analyse trends, statistical time series of activities and energy demand are used to calculate historical intensities and share of energy carriers. Then the calculations are reversed to give a forecast of demand by extrapolating activities and intensities to find future energy demand. Usually, linear or logarithmic (declining) growth rates are used instead of exponential growth, signifying a saturation phenomenon in a developed economy like Norway.
Two separate rounds of analyses with slightly different assumptions gave the same result: Efforts aiming to shift energy consumption to more thermal carriers like district heating, biomass and gas will reduce the (increase in) demand for electricity but will cause total energy demand to increase since thermal energy conversion equipment has higher losses than electrical equipment. If the effort is directed towards energy efficiency measures and low energy buildings, however, total energy demand will be reduced.
As a final remark, the team would like to emphasize the complexity of the issues analysed in this project. A large number of assumptions and simplifications have been made to obtain the presented results, and these have to be kept in mind when then results are interpreted.
