Modelling of diffusion of renewable technologies and its application in the long-term energy forecasting
Tadeusz Skoczkowski , Sławomir Bielecki , Joanna Wojtyńska
AbstractOne of the major challenges the EU will be facing in the coming decades is to create a secure, efficient and clean energy system. Therefore, the EU aspirations are, among others, aimed at spreading the use of renewable energy sources (RES). The largest share in RES is mainly to be obtained by wind and solar-photovoltaic (PV) technologies. Forecasting the future, in this respect, requires a long-term energy modelling which includes, apart from many other aspects, a rate of diffusion of novel technologies into the market and the prediction of their costs. The aim of the article is to research how the modelling determines the development of the above-mentioned RES technologies. The task has been accomplished in two steps. First, depending on the data available a variety of learning curves describing the expected development of PV and wind technologies in the EU till 2050…2100 has been modelled. The learning curves have been presented as a unit cost of the power installed versus cumulative installed capacity (market size). As the production capacity increases, the cost per unit is reduced thanks to learning how to streamline the manufacturing process. Complimentary to these learning curves has been the use of logistic S-shape functions which describe technology diffusion in time. PV and wind generation technologies have been estimated in time domain. The doubts whether learning curves are a proper method of representing technological change due to various uncertainties have been discussed. The second step of the research has been a critical analysis on how these approaches are employed in commonly applied models for long-term energy forecasting (ADVANCE-Remind, WITCH). The measures characterizing the progress of technology development have been selected for each of these models and compared with the learning curves obtained in the first step. The measures depend on the anticipated amount of energy generated, installed capacity and investment expenditures. It has been observed that the analysed models, despite differences in the target saturation levels, predict stagnation in the development of PV and wind technologies from around 2040.
|Publication size in sheets||0.85|
|Book||Stanek Wojciech, Paweł Gładysz, Sebastian Werle, Wojciech Adamczyk (eds.): Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems , 2019, Politechnika Śląska, ISBN 978-83-61506-51-5, 4805 p.|
|Keywords in English||Logistic curves, Learning curves, Photovoltaics, Wind energy, Energy modelling|
|Score||= 5.0, 19-01-2020, ChapterFromConference|
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