Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

Andresen, Gorm Bruun; Søndergaard, Anders A.; Greiner, Martin

doi:10.1016/j.energy.2015.09.071

Cited by 91 publications

(87 citation statements)

References 14 publications

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“…where η = 0.95, ∆u = 1.27 m/s and σ 0 = 2.29 m/s are the optimal parameters minimising the error between the re-analysis-based time-series and a year of Danish wind feed-in [46]. A study comparing the wind generation time-series based on the re-analysis MERRA-2 dataset for a 20 year period to the percountry wind feed-in and several wind park generation measurements found non-negligible discrepancies of the optimal bias correction parameters between different countries [50].…”

Section: Wind Generationmentioning

confidence: 99%

PyPSA-Eur: An open optimisation model of the European transmission system

Hörsch

Hofmann

Schlachtberger

et al. 2018

Energy Strategy Reviews

216

150

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PyPSA-Eur, the first open model dataset of the European power system at the transmission network level to cover the full ENTSO-E area, is presented. It contains 6001 lines (alternating current lines at and above 220 kV voltage level and all high voltage direct current lines), 3657 substations, a new open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power. The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability. The restriction to freely available and open data encourages the open exchange of model data developments and eases the comparison of model results. A further novelty of the dataset is the publication of the full, automated software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy replacement and improvement of the individual parts. This paper focuses on the description of the network topology, the compilation of a European power plant database and a top-down load timeseries regionalisation. It summarises the derivation of renewable wind and solar availability time-series from re-analysis weather datasets and the estimation of renewable capacity potentials restricted by land-use. Finally, validations of the dataset are presented, including a new methodology to compare geo-referenced network datasets to one another. challenges for the efficient design and regulation of electricity markets; the need to decarbonise heating and transport is driving electrification of these sectors; and finally energy markets are being integrated across the continent [1].To study this transformation, accurate modelling of the transmission grid is required. The need to take account of international electricity trading and the possibility of smoothing variable renewable feed-in over large distances (wind generation has a typical correlation length of around 600 km [2]) mean that models should have a continental scope. At the same time, high spatial detail is required, since national grid bottlenecks are already hindering the uptake of renewable energy today [3], and given persistent public acceptance problems facing new transmission projects [4], severe grid bottlenecks will remain a feature of the energy system for decades to come.Currently there is no openly-available model of the full European transmission network with which researchers can investigate and compare different approaches to the energy transformation. The transmission grid dataset provided by the European Network of Transmission System Operators for Electricity (ENTSO-E) for the 2016 Ten Year Network Development Plan (TYNDP) [5] is rendered unusable by restrictive licensing, the exclusion of Finland, Norway and Sweden, and a lack of geographic...

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Section: Wind Generationmentioning

confidence: 99%

PyPSA-Eur: An open optimisation model of the European transmission system

Hörsch

Hofmann

Schlachtberger

et al. 2018

Energy Strategy Reviews

216

150

View full text Add to dashboard Cite

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“…Weather data covering multiple years are converted into prospective wind and solar power generation with good spatial and temporal resolution [21,22,[30][31][32], and are then used as the driving force in networked electricty system models. This modelling approach has produced estimates on the required amount of conventional backup power plants, transmission lines and storage [22][23][24][25][26][27][28][33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Principal Mismatch Patterns Across a Simplified Highly Renewable European Electricity Network

et al. 2017

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Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

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“…Using a renewable energy atlas [5], the renewable generation in this data set is obtained by converting weather data into raw generation data for solar PV and wind power generationG S n (t) andG W n (t), respectively [3]. The demand side in the data set is represented by the load time series L n (t), which is based on regionalised historical load data taken from ENTSO-E [3].…”

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confidence: 99%

Scaling of transmission capacities in coarse-grained renewable electricity networks

Schäfer

Siggaard

Zhu

et al. 2017

EPL

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Network models of large-scale electricity systems feature only a limited spatial resolution, either due to lack of data or in order to reduce the complexity of the problem with respect to numerical calculations. In such cases, both the network topology, the load and the generation patterns below a given spatial scale are aggregated into representative nodes. This coarse-graining affects power flows and thus the resulting transmission needs of the system. We derive analytical scaling laws for measures of network transmission capacity and cost in coarse-grained renewable electricity networks. For the cost measure only a very weak scaling with the spatial resolution of the system is found. The analytical results are shown to describe the scaling of the transmission infrastructure measures for a simplified, but data-driven and spatially detailed model of the European electricity system with a high share of fluctuating renewable generation.

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Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis

Cited by 91 publications

References 14 publications

PyPSA-Eur: An open optimisation model of the European transmission system

PyPSA-Eur: An open optimisation model of the European transmission system

Principal Mismatch Patterns Across a Simplified Highly Renewable European Electricity Network

Scaling of transmission capacities in coarse-grained renewable electricity networks

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