Ramachandran Kannan and Neil Strachan, Policy Studies Institute
This paper details modelling efforts within the UK Energy Research Centre’s Energy System Modelling theme, to integrate demand and behavioural responses into a technology optimization model. This has involved the construction of detailed end-use technological characterization within a new MARKAL MACRO model for the UK.
The standard version of MARKAL is a dynamic technology-rich energy systems economic optimisation model of the entire UK energy system. The user inputs the structure of the energy system to be modelled, including resource supplies, energy conversion technologies, end-use demands, and the technologies used to satisfy these demands. MARKAL then calculates, using dynamic linear programming techniques, the least cost way to satisfy the specified demands, subject to a range of physical and user defined constraints.
This modelling paradigm has been extended in two ways. Firstly, detailed end-use characterization of energy technologies and efficiency options within disaggregated energy service demands was undertaken. This allows detailed assessment of the scope for energy efficiency reductions, including the actual costs of efficiency measures, hurdle rates to mimic market risk, availability for different market segments, targeted technology standards, and autonomous drivers of specific energy demands
Secondly, this very rich technological characterization of the UK energy system was linked with a neoclassical macroeconomic model with an aggregated view of long-term economic growth. This approach allows an aggregated demand response to supplement technology pathway optimization, and also facilitates direct analysis of the impacts (i.e., consumption and GDP) of various energy and environmental policies on the growth of the economy.
Outputs of the model under a consistent set of carbon reduction scenarios generate insights into the impact and scope of demand and behaviour responses for total system cost, the fuel and technological mix, and future estimates of physical energy demandIncorporating_Behavioural_Responses_within_a_Technology_Optimization_Energy_Model_2006_pres.pdf 164.96 KB