Spatial integration for firm and load-following wind generation
File(s)López_Prol_2024_Environ._Res._Lett._19_094026.pdf (4.04 MB)
Published version
Author(s)
Lopez Prol, Javier
de Llano Paz, Fernando
Calvo Silvosa, Anxo
Pfenninger, Stefan
Staffell, Iain
Type
Journal Article
Abstract
Wind power has considerable potential to decarbonise electricity systems due to its low cost and wide availability. However, its variability is one factor limiting uptake. We propose a simple analytical framework to optimise the distribution of wind capacity across regions to achieve a maximally firm or load-following profile. We develop a novel dataset of simulated hourly wind capacity factors for 111 Chinese provinces, European countries and US states spanning ten years (~10 million observations). This flexible framework allows for near-optimal analysis, integration of demand, and consideration of additional decision criteria without additional modelling. We find that spatial integration of wind resources optimising the distribution of capacities provides significant benefits in terms of higher capacity factor or lower residual load and lower variability at sub-, quasi- and inter-continental levels. We employ the concept of firmness as achieving a reliable and certain generation profile and show that, in the best case, the intercontinental interconnection between China, Europe and the US could restrict wind capacity factors to within the range of 15-40% for 99% of the time. Smaller configurations corresponding to existing electricity markets also provide more certain and reliable generation profiles than isolated individual regions.
Date Issued
2024-09
Date Acceptance
2024-07-01
Citation
Environmental Research Letters, 2024, 19 (9)
ISSN
1748-9326
Publisher
IOP Publishing
Journal / Book Title
Environmental Research Letters
Volume
19
Issue
9
Copyright Statement
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
License URL
Identifier
http://dx.doi.org/10.1088/1748-9326/ad5d7d
Publication Status
Published
Article Number
094026
Date Publish Online
2024-08-07