Induced Technological Change in a Limited Foresight Optimization Model

Abstract

The threat of global warming calls for a major transformation of the energy system in the coming century. The treatment of technological change in energy system models is a critical challenge. Technological change may be treated as induced by climate policy or as exogenous. We investigate the importance of induced technological change (ITC) in GET-LFL, an iterative optimization model with Limited Foresight that incorporates Learning-by-doing. Scenarios for stabilization of atmospheric CO2 concentrations at 400, 450, 500 and 550 ppm are studied. We find that the introduction ofITC reduces the total net present value of the abatement cost over this century by 3-9% compared to a case where technological learning is exogenous. Technology specific policies which force the introduction of fuel cell cars and solar PV in combination with ITC reduce the costs further by 4-7% and lead to significantly different technological solutions, primarily in the transport sector.