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The EU target of 45% renewable electricity by 2030 requires additional capacities of wind and solar power across Europe. In this work, a novel high-resolution multi-country power systems model, which comprises full-year hourly chronological AC optimal power flow simulations, is applied within a multi-objective optimization framework. This framework is applied to determine the optimal portfolio of wind and solar capacities across Europe, which achieves the EU target while minimizing curtailment, residual load fluctuations and investment costs. The optimal portfolio comprises new wind and solar capacities of 221 GW and 82 GW respectively; the geographic locations of the new capacities are identified. To accommodate these additional capacities, 4% of central European transmission lines require reinforcement. The presented approach of simultaneously optimizing the renewable portfolios across multiple countries reduces curtailment, residual load variability and electricity prices by best utilizing each country's renewable resources and the intrinsic balancing effects of large-scale wind power.

In order to reliably design the planning and operation of large interconnected power systems that can incorporate a high penetration of renewables, it is necessary to have a detailed knowledge of the potential impacts of exogenous factors on individual components within the systems. Previously, the assessment has often been conducted with nodes that are aggregated at the country or regional scale, this makes it impossible to reliably extrapolate the impact of higher penetration of renewables on individual transmission lines and/or power plants within an aggregated node. In order to be able to develop robust power systems this study demonstrates an integrated framework that employs high resolution spatial and temporal, physical modeling of power generation, electricity transmission and electricity demand, across the scale of a continent or country. Using Germany as a test case, an assessment of the impacts of exogenous factors, including local changes in ambient weather conditions, effect of timely implementation of policy, and contingency for scenarios in 2020 are demonstrated. It is shown that with the increased penetration of renewables, while the power production opportunities of conventional power plants are reduced, these power plants are required during periods of low renewables production due to the inherent variability of renewables. While the planned reinforcements in Germany, including high voltage direct current lines, reduce congestion on the grid and alleviate the differentials in power price across the country, on the other hand the reinforcements make the interconnected transmission system more vulnerable as local perturbations have a more widespread impact.

High spatial and temporal resolution optimal power flow simulations of the 2013 and 2020 interconnected grid in Central Western Europe and Central Eastern Europe regions are undertaken to assess the impact of an increased penetration of renewables. In contrast to prior studies, the present work models the individual transmission lines and power plants within the two regions. It is shown that the planned 2020 developments of the AC grid reduce the mean loading of the grid from 34% to 24%. Most impacted are north-south lines in Germany. The planned developments of HVDC lines further reduce the loading on the AC grid to 22%, as the HVDC lines provide a low-loss transmission solution for the abundant wind energy in northern Germany. Physical loop flows in central Europe increase by 15% for planned 2020 penetration levels of renewables; however these loop flows are reduced by 15% with addition of German HVDC lines.

In order to accomplish the reliable planning and operation of large interconnected power systems with high penetration of renewables, knowledge of the impacts on individual transmission lines and power plants within the system is required. This may be accomplished using high-resolution optimal power flow simulations with which different scenarios can be assessed. This paper presents detailed numerical weather prediction models that can be used for accurate predictions of solar and wind generated electricity. Furthermore a high-resolution power demand model that accounts for the spatial and temporal variations of different sectors is presented. The models are demonstrated in the case of one-year hourly resolution simulation of the central European power system.