Volume 2: Innovative Solutions for Energy Transitions: Part I

Electricity Demand Forecast for Bavaria and the Czech Republic Until 2050: Can Variable Renewables Cope with it? Maximilian Roithner, Jane Wuth, Luis Ramirez Camargo

https://doi.org/10.46855/energy-proceedings-1108

Abstract

The energy transition raises a need for innovative ideas to cope with the integration of high shares of variable renewable energy sources. Across political, industrial and research audiences, the idea of electricity self-sufficiency has been gaining rising interest. It might, among others, solve questions of energy security and help to avoid short term necessary investments into the electricity grids. However, while electricity selfsufficiency can be technically feasible for a large range of user types (e.g. residential, agricultural, and industrial) and cluster sizes (e.g. individuals, districts, municipalities), it becomes rapidly unfeasible when strict regulations are considered. In this study, the feasibility of electricity self-sufficiency based on free-standing photovoltaics, wind power and storage systems was evaluated for all municipalities in Bavaria (Germany) and the Czech Republic. Main focus of this paper is the calculation of the spatially distributed electricity demand of today and the future. Methods for the technology potential evaluation and the development of an optimization model to determine necessary system sizes are shortly presented referring to previous work. Results indicate that around 20% of the German and 6% of the Czech municipalities could achieve self-sufficiency today based on the considered technologies and under current Bavarian regulatory restrictions. These figures improve enormously with milder regulations for wind power installations. Furthermore, due to an expected depopulation of rural areas, a rising trend in potentially electricity self-sufficient municipalities is visible.

Keywords renewable energy resources, spatially distributed electricity demand, demographic changes, land use changes, regional reanalysis, spatiotemporal modelling

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