ADDRESSING GRID CAPACITY THROUGH TIME SERIES : Deriving a data driven and scenario-based method for long-term planning of local grids.

Simultaneously as the societal trends of urbanization, digitalization and electrification of society are moving at a high speed, the Swedish power grid is undergoing a necessary transition to a renewable energy system. Even though there are difficulties on all grid levels, the lack of capacity in some local grids is among the most present problems and originates from the long lead time of grid expansion as well as the challenges within long-term planning of grids. This thesis aims to improve the understanding of future trends’ impact on grid capacity needs. More specifically, a scenario-based and data driven method, with an accompanying model, is derived to target local capacity challenges. The trends identified to pose impact on the future grid capacity were electrification of different sectors, energy efficiency actions, decentralized energy generation, energy storage solutions, flexibility, smart grids, urbanization and climate. The thesis concludes that the impact of a trend on national level is not simply equal to the impact on a local level. Similarly, a long-term increase of the national electricity consumption does not necessarily worsen local capacity challenges. Furthermore, the developed model in this project shows potential to provide more detailed and accurate information about consumption than currently used methods based on standardized power estimations, which could favor more transparent decision making when dimensioning local grids