Method for Designing a High Capacity Factor Wide Area Virtual Wind Farm

Trenkel-Lopez, M.; Matthews, P.C.

Abstract

Moving towards a future power system dominated by renewable energy, it is vital that the siting of spatial-dependent technologies such as wind maximises the power generation while minimising the variability associated with wind power. This study develops a novel methodology for wind farm diversification by identifying pairs and triplets of locations across Western Europe which together form `virtual' wind farms with a better guarantee of a minimum power generation level, providing capacity planners with tools to design a network of connected wind farms working together on a continental scale. These locations were found using hourly wind speed data spanning 10 years by examining time periods of local low wind availability at each grid point and identifying the best complementary wind resource locations. The best links are identified and presented in this paper. From an idealised capacity factor (CF) of 0.70 for a single site, the method found the potential for virtual CFs of 0.64 for grid point pairs and 0.68 for grid point triplets. This suggests that this approach can model virtual wind farms with virtual CFs comparable to conventional generation technologies and drastically reduce the amount of time during which farms are producing no power.

Citation

Trenkel-Lopez, M., & Matthews, P. (2018). Method for Designing a High Capacity Factor Wide Area Virtual Wind Farm. IET Renewable Power Generation, 12(3), 351-358. https://doi.org/10.1049/iet-rpg.2017.0396

• Journal Article Type: Article
• Acceptance Date: Oct 26, 2017
• Online Publication Date: Nov 6, 2017
• Publication Date: Feb 26, 2018
• Deposit Date: Nov 2, 2017
• Publicly Available Date: Nov 3, 2017
• Journal: IET Renewable Power Generation
• Print ISSN: 1752-1416
• Electronic ISSN: 1752-1424
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 3
• Pages: 351-358
• DOI: https://doi.org/10.1049/iet-rpg.2017.0396
• Public URL: https://durham-repository.worktribe.com/output/1372332