e-Highway 2050: Methodology of Data Contextualization for the Purpose of Scenario Building
Journal Title: Acta Energetica - Year 2016, Vol 27, Issue 2
Abstract
The e-Highway 2050 project is co-financed by the EU Seventh Framework Programme and is aimed at developing a methodology to support the long-term planning of the Pan-European Transmission Network, focusing on year 2050, to ensure the reliable delivery of renewable electricity and pan-European market integration. One of the tasks of the project is to create five scenarios covering the time period 2020–2050 and taking into account financial, technological/ economic, environmental and socio-political issues. One of the key questions in the context of the whole project is how to select the typical range of technology data according to the five elaborated scenarios. To this end, an approach called data contextualization is suggested. It aims to allocate, for a given technology, typical values to key variables descriptive of this technology, within the 2050 time horizon, for each of the five considered scenarios. The key assumption used is that the main driver for contextualization is the penetration rate of a given technology (cumulated number of units at a given time). It is indeed assumed that the cost and performance trends of a technology by 2050 are directly correlated to its level of deployment. The first stage of the contextualization process was to determine the degree of influence of individual factors (uncertainties as defined for each “future” and options as defined for each “strategy”) on variables selected to be contextualized. Each parameter of the selected scenarios (future uncertainty or option) has then been analysed in order to determine its impact on a potential incentive to develop a given technology as well as its investment and O&M costs. It has been assumed that development of a given technology is stimulated and hence its penetration increases by lowering the overall investment costs and vice versa. Based on the impact of each parameter’s value, a final assessment of the projected level of both types of costs was assigned to each scenario and each technology category. Finally, the values of selected variables have been allocated to individual scenarios and technologies. The allocation has been performed based on the assessment of appropriate technology groups in a given scenario and the range of values for the selected variable.
Authors and Affiliations
Michał Bajor, Maciej Wilk
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