Imperial College London
Portrait Picture

Professor Adam Hawkes

Faculty of Engineering, Department of Chemical Engineering

Professor of Energy Systems
 
 
 
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Contact

 

+44 (0)20 7594 9300a.hawkes

 
 
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Location

 

RODH.503Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Chu:2020:10.1016/j.energy.2019.116630,
author = {Chu, C-T and Hawkes, AD},
doi = {10.1016/j.energy.2019.116630},
journal = {Energy},
pages = {1--11},
title = {A geographic information system-based global variable renewable potential assessment using spatially resolved simulation},
url = {http://dx.doi.org/10.1016/j.energy.2019.116630},
volume = {193},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Variable renewable energy is set to become a key energy source worldwide, but there is concern regarding the impact of the intermittency of its output when penetration is high. Energy system models need to tackle this issue by improving modelling resolution and scope. To allow for such modelling, more and better input datasets are needed on variable renewable energy potentials and yields. These need to be of global scope, of sufficient spatial and temporal resolution, and generated with transparent, consistent methods. This study develops the methods and applies it to generate these datasets at subnational and hourly resolution. The assessment is carried out for wind and solar technologies with consistent constraints including geographical, social and economic aspects. Features from the OpenStreetMap are converted into land cover and land use datasets and applied. Hourly energy output is simulated using NASA MERRA-2 meteorological datasets, reconciled with resource maps from the Global Wind Atlas and Global Solar Atlas platforms. Capacity supply curves are provided for 731 terrestrial zones and 339 offshore zones worldwide, along with corresponding hourly output profiles over a 10-year simulation period. The proposed energy potentials are relative conservative compared with other studies. The datasets can serve as input for regional or global energy system models when analyzing high variable renewable energy shares.
AU  - Chu,C-T
AU  - Hawkes,AD
DO  - 10.1016/j.energy.2019.116630
EP  - 11
PY  - 2020///
SN  - 0360-5442
SP  - 1
TI  - A geographic information system-based global variable renewable potential assessment using spatially resolved simulation
T2  - Energy
UR  - http://dx.doi.org/10.1016/j.energy.2019.116630
UR  - https://www.sciencedirect.com/science/article/pii/S0360544219323254?via%3Dihub
UR  - http://hdl.handle.net/10044/1/77162
VL  - 193
ER  -
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