Effects of Wind Power Technology Development on Large-scale VRE Generation Variability

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2019Researchpeer-review

Documents

DOI

View graph of relations

As variable renewable energy (VRE) shares are growing around the world, power systems are becoming more weather dependent. The weather driven variability in VRE generation can cause challenges to the operation and planning of power systems. This paper investigates how the expected technology development of wind power affects VRE generation variability over a large geographical area. A case study of Northern Europe is presented, where a mixture of offshore wind, onshore wind and solar photovoltaic generation is considered. Different scenarios with a doubling of today’s annual VRE energy generation is modelled. The results show that modern wind turbine technology can significantly decrease the variability in aggregate VRE generation. When considering also an optimal mixture of different VRE sources, standard deviation of the aggregate VRE generation is estimated to be 31 % lower compared to simply doubling existing installations.
Original languageEnglish
Title of host publicationProceedings of the 13th IEEE PowerTech Milano 2019: Leading innovation for energy transition
Number of pages6
PublisherIEEE
Publication date2019
ISBN (Print)978-1-5386-4723-3
ISBN (Electronic)978-1-5386-4722-6
DOIs
Publication statusPublished - 2019
Event13th IEEE PowerTech Milano 2019: Leading innovation for energy transition - Bovisa Campus of Politecnico di Milano, Milano, Italy
Duration: 23 Jun 201927 Jun 2019
Conference number: 13
http://ieee-powertech.org/

Conference

Conference13th IEEE PowerTech Milano 2019
Number13
LocationBovisa Campus of Politecnico di Milano
CountryItaly
CityMilano
Period23/06/201927/06/2019
OtherPowerTech is the anchor conference of the IEEE Power & Energy Society (PES) in Europe
Internet address
CitationsWeb of Science® Times Cited: No match on DOI

Download statistics

No data available

ID: 179419426