The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Assessment of solar and wind resource synergy in Australia
Open accessAbstract
Solar and wind generated power is expected to increase drastically in the future. Unlike fossil fuels, however, solar and wind resource extraction introduces challenges of variability and intermittency. Several recent studies around the world have shown that since dissimilar climatological factors are responsible for wind and solar resources, they can often operate in tandem to offset lulls in each other. While most research on solar and wind resource interaction has been undertaken over the Northern Hemisphere (America, Europe and China), there is a lack of understanding on how much (or even if) solar and wind resources complement one another in other parts of the world. To partially address this issue in the Southern Hemisphere, this study provides a systematic quantitative analysis of the complementary characteristics of solar and wind resources on the Australian continent. As such, wind power density and surface incident shortwave flux are derived from the hourly Modern Era Retrospective Analysis for Research and Applications (MERRA) product for the entire continent for the period from 1979 to 2014. It was found that the temporal synergy between solar and wind resource is maximum along the western and southern coast of Australia. Tasmania, south-eastern (parallel to eastern Great Dividing Range), and northern regions (Cairns and Kimberley Plateau) of the continent also showed significant synergy (≈40% within a distance of 93km), which was mostly influenced by hours of daylight when the solar resource is available. Increasing the spatial extent increased the occurrence of synergy characteristics to 50% within a distance of 465km. These findings are significant because most of the synergy (and intermittency) in solar and wind resources was found in proximity to transmission lines – locations where renewables are likely to be cited going forward. Amongst current large-scale solar and wind farms operating in south-eastern Australia, this study also finds that increased power production is possible by balancing existing assets with complementary solar and wind farms. While these results are limited to a single continent, the proposed approach (e.g. using similar metrics) can be readily applied to investigate synergies between solar and wind resource in other parts of the world using the global MERRA product.
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Cites
Updated world map of the Köppen-Geiger climate classification
Peel, M. C., Finlayson, B. L., & McMahon, T. A. (2007) · doi:10.5194/hessd-4-439-2007 · Cited by 13,640
Updated world map of the Köppen-Geiger climate classification
(2007) · doi:10.5194/hess-11-1633-2007 · Cited by 13,640
World map of the Köppen-Geiger climate classification updated
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006) · Meteorologische Zeitschrift · doi:10.1127/0941-2948/2006/0130 · Cited by 11,456
MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., et al. (2011) · Journal of Climate · doi:10.1175/jcli-d-11-00015.1 · Cited by 4,852
Jacobson, M. Z., & Delucchi, M. A. (2011) · Energy Policy · doi:10.1016/j.enpol.2010.11.040 · Cited by 1,570
The effect of renewable energy consumption on economic growth: Evidence from top 38 countries
Bhattacharya, M., Paramati, S. R., Ozturk, I., & Bhattacharya, S. (2016) · Applied Energy · doi:10.1016/j.apenergy.2015.10.104 · Cited by 1,527
Integration of renewable energy into the transport and electricity sectors through V2G
Lund, H., & Kempton, W. (2008) · Energy Policy · doi:10.1016/j.enpol.2008.06.007 · Cited by 1,073
Yang, H., Zhou, W., Lu, L., & Fang, Z. (2007) · Solar Energy · doi:10.1016/j.solener.2007.08.005 · Cited by 926
Zhou, W., Lou, C., Li, Z., Lu, L., & Yang, H. (2010) · Applied Energy · doi:10.1016/j.apenergy.2009.08.012 · Cited by 893
A novel optimization sizing model for hybrid solar-wind power generation system
Yang, H., Lu, L., & Zhou, W. (2006) · Solar Energy · doi:10.1016/j.solener.2006.06.010 · Cited by 790
Metadata
- Authors
- Prasad, A. A., Taylor, R. A., & Kay, M.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 190
- Pages
- 354-367
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2571254282
- Cited by
- 258
- References
- 36
- FWCI
- 14.10
- Type
- journal article
- Language
- en
- Open access
- green
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