2018
DOI: 10.1016/j.joule.2018.06.020
|View full text |Cite
|
Sign up to set email alerts
|

Impacts of Inter-annual Wind and Solar Variations on the European Power System

Abstract: SummaryWeather-dependent renewable energy resources are playing a key role in decarbonizing electricity. There is a growing body of analysis on the impacts of wind and solar variability on power system operation. Existing studies tend to use a single or typical year of generation data, which overlooks the substantial year-to-year fluctuation in weather, or to only consider variation in the meteorological inputs, which overlooks the complex response of an interconnected power system. Here, we address these gaps… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

6
105
0

Year Published

2018
2018
2021
2021

Publication Types

Select...
10

Relationship

1
9

Authors

Journals

citations
Cited by 170 publications
(111 citation statements)
references
References 55 publications
6
105
0
Order By: Relevance
“…It is observed that trends in different samples of the load and renewable generation time series are reflected in the details of the simulation results, but only weakly affect the resulting total system costs. The robustness of the overall results to input weather data from different years confirms earlier results from the literature [53], however specific technologies may be affected by inter-annual variability, so the most robust results are found by taking weather data from several years (see for instance [54]). A shift from an hourly resolution to a 3 hour sampling in the time series can increase the share of solar power generation due to the corresponding smoothing of fluctuations on this time scale, but again the changes are slight.…”
Section: Discussionsupporting
confidence: 82%
“…It is observed that trends in different samples of the load and renewable generation time series are reflected in the details of the simulation results, but only weakly affect the resulting total system costs. The robustness of the overall results to input weather data from different years confirms earlier results from the literature [53], however specific technologies may be affected by inter-annual variability, so the most robust results are found by taking weather data from several years (see for instance [54]). A shift from an hourly resolution to a 3 hour sampling in the time series can increase the share of solar power generation due to the corresponding smoothing of fluctuations on this time scale, but again the changes are slight.…”
Section: Discussionsupporting
confidence: 82%
“…In other words, annual variations within a given climate change scenario are larger than the difference between scenarios. This indicates that it is more important to incorporate existing inter-annual variation in long-term electricity system design decisions, as discussed by Collins et al, 54 compared to including the effect of climate change. Furthermore, a paired t test reveals that, in most cases, the null hypothesis of no difference between the historical and the future 20-year mean values of the key metrics cannot be rejected (95% confidence).…”
Section: Resultsmentioning
confidence: 99%
“…Thirdly, only one single year of historical weather data (2015) has been modelled. Since the optimal wind/solar mix is very likely sensitive to the capacity factors of wind and solar, different weather years may lead to a slightly different picture [38]. For the sake of simplicity, electricity and heating demand are fixed to today's values and considered to be inelastic, which can be improved by implementing heat savings and demand-side management (DSM).…”
Section: Limitations Of the Studymentioning
confidence: 99%