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As the energy system becomes increasingly dependent on intermittent meteorological sources, there is a need to understand better the possible consequences of a changing climate on weather variability and how it will affect wind power generation in the future. Most previous validation studies of regional climate datasets focus on the distributional properties or, in fewer cases, the variability at lower frequencies, such as interannual and seasonal. However, accurate wind variability at a high-enough resolution (e.g., hourly) is crucial for many aspects of power and energy system analyses. Using European country-level wind generation data and metrics relevant to power and energy system applications, we validate the wind speed output from seven regional climate models from the EURO-CORDEX project. We show that the EURO-CORDEX models adjusted with the Global Wind Atlas (GWA2) can simulate temporal dependencies and generation distributions with accuracy similar to or better than the ERA5 reanalysis. The spatial correlations, however, are overestimated compared to observations by most analysed models. Assuming the GWA2 scaling is also valid for the future, the projections under the RCP8.5 scenario show a slight negative trend (2026–2065) in capacity factors for most analysed European countries. • Three-hourly climate data validated for power and energy system applications. • Only wind speed time series at heights compatible with modern wind turbines selected. • Focus on the correlations of wind power generation at country level in Europe. • Accuracy of EURO-CORDEX simulations adjusted by microscale details. [ABSTRACT FROM AUTHOR]

The energy sector is highly dependent on climate variability for electricity generation, maintenance activities and demand. In recent years, a few climate services have appeared that provide tailored information for the energy sector. In particular, seasonal climate predictions of wind speed have proven useful to the wind power industry. However, most of the service users are ultimately interested in forecasts of electricity generation instead of wind. Although power generation depends on many factors other than wind conditions, the capacity factor is a suitable indicator to quantify the impact of wind variability on production. In this paper a methodology to produce seasonal predictions of capacity factor for a range of turbine classes is proposed for the first time. The strengths and weaknesses of the method are discussed and the forecast quality is evaluated for an application example over Europe. • A method to produce seasonal forecasts of renewable generation is presented. • A unified approach that fits the specific nature of any wind farm is employed. • Some limitations of seasonal prediction systems are identified and addressed. • The generation forecasts perform better than climatology in some European regions. [ABSTRACT FROM AUTHOR]

For a cost efficient design of a future renewable European electricity system, the placement of renewable generation capacity will seek to exploit locations with good resource quality, that is for instance onshore wind in countries bordering the North Sea and solar PV in South European countries. Regions with less favorable renewable generation conditions benefit from this remote capacity by importing the respective electricity as power flows through the transmission grid. The resulting intricate pattern of imports and exports represents a challenge for the analysis of system costs on the level of individual countries. Using a tracing technique, we introduce flow-based nodal levelized costs of electricity (LCOE) which allow to incorporate capital and operational costs associated with the usage of generation capacity located outside the respective country under consideration. This concept and a complementary allocation of transmission infrastructure costs is applied to a simplified model of an interconnected highly renewable European electricity system. We observe that cooperation between the European countries in a heterogeneous system layout does not only reduce the system-wide LCOE, but also the flow-based nodal LCOEs for every country individually. [ABSTRACT FROM AUTHOR]

The resource quality and the temporal generation pattern of variable renewable energy sources vary significantly across Europe. In this paper spatial distributions of renewable assets are explored which exploit this heterogeneity to lower the total system costs for a high level of renewable electricity in Europe. Several intuitive heuristic algorithms, optimal portfolio theory and a local search algorithm are used to find optimal distributions of renewable generation capacities that minimise the total costs of backup, transmission and renewable capacity simultaneously. Using current cost projections, an optimal heterogeneous distribution favours onshore wind, particularly in countries bordering the North Sea, which results in average electricity costs that are up to 11% lower than for a homogeneous reference distribution of renewables proportional to each country's mean load. The reduction becomes even larger, namely 18%, once the transmission capacities are put to zero in the homogeneous reference distribution. Heuristic algorithms to distribute renewable capacity based on each country's wind and solar capacity factors are shown to provide a satisfactory approximation to fully optimised renewable distributions, while maintaining the benefits of transparency and comprehensibility. The sensitivities of the results to changing costs of solar generation and gas supply as well as to the possible cross-sectoral usage of unavoidable curtailment energy are also examined. [ABSTRACT FROM AUTHOR]

Based on a data-intensive weather-driven modelling approach, technically and economically optimal designs are derived for a simplified, highly renewable pan-European electricity system, which minimise the need for backup energy, backup capacity, transmission capacity and the levelised system cost of delivered electricity. The overall cost-optimal design, based on standard cost assumptions, relies on synchronised backup across the transmission grid and comes with a renewable penetration of 50% with a rather high wind fraction of 94%. Given the current European electricity consumption, this corresponds to 600 GW rated wind power capacities, 60 GW installed solar power capacities, 320 GW conventional backup power capacity, and about five times today's installed transmission capacities. A sensitivity analysis reveals that the design and cost of the optimal system depend mostly on the assumed cost of wind capacity and fuel for backup energy. Lower costs for wind capacity, higher costs for backup energy and usage of otherwise curtailed excess electricity generation lead to a strong increase of the optimal renewable penetration. The sensitivity analysis is also used to find that a CO 2 tax of over 100 €/ton would be needed for the economic viability of carbon capture and sequestration. [ABSTRACT FROM AUTHOR]

Abstract: The residual load and excess power generation of 30 European countries with a 100% penetration of variable renewable energy sources are explored in order to quantify the benefit of power transmission between countries. Estimates are based on extensive weather data, which allows for modelling of hourly mismatches between the demand and renewable generation from wind and solar photovoltaics. For separated countries, balancing is required to cover around 24% of the total annual electricity consumption. This number can be reduced down to 15% once all countries are networked together with unconstrained interconnectors. The reduction represents the maximum possible benefit of transmission for the countries. The total Net Transfer Capacity of the unconstrained interconnectors is roughly 11.5 times larger than current values. However, constrained interconnector capacities 5.7 times larger than the current values are found to provide 98% of the maximum possible benefit of transmission. This motivates a detailed investigation of several constrained transmission capacity layouts to determine the export and import capabilities of countries participating in a fully renewable European electricity system. [Copyright &y& Elsevier]

Abstract: The storage and balancing needs of a simplified European power system, which is based on wind and solar power generation only, are derived from an extensive weather-driven modeling of hourly power mismatches between generation and load. The storage energy capacity, the annual balancing energy and the balancing power are found to depend significantly on the mixing ratio between wind and solar power generation. They decrease strongly with the overall excess generation. At 50% excess generation the required long-term storage energy capacity and annual balancing energy amount to 1% of the annual consumption. The required balancing power turns out to be 25% of the average hourly load. These numbers are in agreement with current hydro storage lakes in Scandinavia and the Alps, as well as with potential hydrogen storage in mostly North-German salt caverns. [Copyright &y& Elsevier]

Abstract: The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases. [Copyright &y& Elsevier]