Wind power variability during the passage of cold fronts across South Africa
DOI:
https://doi.org/10.17159/2413-3051/2019/v30i3a6356Keywords:
weather systems, variability, cold fronts, wind power simulationAbstract
Wind is a naturally variable resource that fluctuates across timescales and, by the same token, the electricity generated by wind also fluctuates across timescales. At longer timescales, i.e., hours to days, synoptic-scale weather systems, notably cold fronts during South African winter months, are important instigators of strong wind conditions and variability in the wind resource. The variability of wind power production from aggregates of geographically disperse turbines for the passage of individual cold fronts over South Africa was simulated in this study. When considering wind power variability caused by synoptic-scale weather patterns, specifically cold fronts, the timescale at which analysis is conducted was found to be of great importance, as relatively small mean absolute power ramps at a ten-minute temporal resolution, order of 2-4% of simulated capacity, can result in large variations of total wind power production (at the order of 32–93% of simulated capacity) over a period of three to four days as a cold front passes. It was found that when the aggregate consists of a larger and more geographically dispersed set of turbines, as opposed to a smaller set of turbines specifically located within cold-front dominated high wind areas, variability and the mean absolute ramp rates decrease (or gets ‘smoothed’) across the timescales considered. It was finally shown that the majority of large simulated wind power ramp events observed during the winter months, especially at longer timescales, are caused by the passage of cold fronts.
Downloads
References
Albadi, M.H. & El-Saadany, E.F. 2010. Overview of wind power intermittency impacts on power systems. Electric Power Systems Research 80(6): 627–632. Available at: http://dx.doi.org/10.1016/j.epsr.2009.10.035.
Choukri, K., Naddami, A. & Hayani, S.M. 2017. Deep analysis of wind variability and smoothing effect in Moroccan wind farms. Wind Engineering 41(4): 272–281.
https://doi.org/10.1177/0309524x17709731
Council for Scientific and Industrial Research [CSIR]. 2010. No title. Available at: http://wasadata.csir.co.za/wasa1/WASAData [Accessed July 10, 2018].
Couto, A., Costa, P., Rodrigues, L., Lopes, V. V. & Estanqueiro, A. 2015. Impact of weather regimes on the wind power ramp forecast in Portugal. IEEE Transactions on Sustainable Energy 6(3): 934–942.
https://doi.org/10.1109/tste.2014.2334062
Department of Energy. 2018. Draft Integrated Resource Plan. Pretoria.
ECR Newswatch. 2016. PICS: Cold weekend brings snow in parts of KZN. Available at: https://www.ecr.co.za/news/news/pics-cold-weekend-brings-snow-kzn/ [Accessed July 10, 2018].
Eumetrain. 2012. South African Cold Fronts. Available at: http://www.eumetrain.org/satmanu/CMs/SACF/print.htm.
Gallego-Castillo, C., Cuerva-Tejero, A. & Lopez-Garcia, O. 2015. A review on the recent history of wind power ramp forecasting. Renewable and Sustainable Energy Reviews 52: 1148–1157.
https://doi.org/10.1016/j.rser.2015.07.154
Gallego-castillo, C., Garcia-bustamante, E., Cuerva, A. & Navarro, J. 2015. Identifying wind power ramp causes from multivariate datasets: A methodological proposal and its application to reanalysis data. IET Renewable Power Generation 9(8): 867-875
Google Earth Pro, US Department of State Geographer, DATA SIO, US Navy, NOAA, & Image Landsat/ Copernicus. 2019. South Africa.
Joubert, C.J. 2017. Geographical location optimisation of wind and solar photovoltaic power capacity in South Africa using mean- variance portfolio theory and time series clustering. Master of Engineering dissertation, Stellenbosch University, Stellenbosch South Africa.
https://doi.org/10.29252/jafm.12.06.29789
Kalverla, P.C., Steeneveld, G.J., Ronda, R.J. & Holtslag, A.A.M. 2017. An observational climatology of anomalous wind events at offshore meteomast IJmuiden (North Sea). Journal of Wind Engineering and Industrial Aerodynamics 165 (2017): 86–99. Available at: http://dx.doi.org/10.1016/j.jweia.2017.03.008.
https://doi.org/10.1016/j.jweia.2017.03.008
Kiviluoma, J., Holttinen, H., Weir, D., Scharff, R., Söder, L., Menemenlis, N., Cutululis, N.A., Lopez, I.D. & Lannoye, E. 2016. Variability in large-scale wind power generation. Wind Energy 19:1649–1665.
https://doi.org/10.1002/we.1942
Knorr, K., Zimmermann, B., Bofinger, S., Gerlach, A.K., Bischof-Niemz, T. & Mushwana, C. 2016. Wind and Solar PV Resource Aggregation Study for South Africa.
Kruger, A.C. 2011. Wind climatology of South Africa relevant to the design of the built environment. PhD dissertation, Stellenbosch Univeristy, Stellenbsoch, South Africa.
Kruger, A.G., Goliger, A.M., Retief, J. V. & Sekele, S. 2010. Strong wind climatic zones in South Africa. Wind and Structures, An International Journal 13(1): 37–55.
https://doi.org/10.12989/was.2010.13.1.037
Lacerda, M. & Estanqueiro, A. 2017. Wind power ramps driven by windstorms. Energies 10 (10): 1475.
https://doi.org/10.3390/en10101475
Lang, D.T. 2018. Package ‘XML’. Available at: http://www.omegahat.net/RSXML.
Mararakanye, N. & Bekker, B. 2019. Renewable energy integration impacts within the context of generator type, penetration level and grid characteristics. Renewable and Sustainable Energy Reviews 108(March): 441–451.
https://doi.org/10.1016/j.rser.2019.03.045
Mcewan, C. 2017. Spatial processes and politics of renewable energy transition: Land, zones and frictions in South Africa. Political Geography 56: 1–12.
https://doi.org/10.1016/j.polgeo.2016.10.001
Monforti, F., Huld, T., Bódis, K., Vitali, L., Isidoro, M.D. & Lacal-arántegui, R. 2014. Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach. Renewable Energy 63: 576–586.
https://doi.org/10.1016/j.rser.2015.12.318
Monforti, F., Gaetani, M. & Vignati, E. 2016. How synchronous is wind energy production among European countries? Renewable and Sustainable Energy Reviews 59: 1622–1638. Available at: http://dx.doi.org/10.1016/j.rser.2015.12.318.
Mortensen, N.G., Hansen, J.C., Kelly, M.C., Szewczuk, S., Mabille, E. & Prinsloo, E. 2012. Wind Atlas for South Africa (WASA) Observational wind atlas for 10 met. stations in Northern, Western and Eastern Cape provinces. Wind Atlas for South Africa (WASA).
Prasad, R. D., Bansal, R. C. & Sauturaga, M. 2009. Some of the design and methodology considerations in wind resource assessment. IET Renewable Power Generation 3(1): 53–64.
https://doi.org/10.1049/iet-rpg:20080030
Prasad, R.D., Bansal, R.C. & Sauturaga, M. 2009. Wind energy analysis for Vadravadra Site in Fiji Islands: A case study. IEEE Transactions on Energy Conversion 24(3): 750–757.
R Core Team. 2018. R: A language and environment for statistical computing. Available at: https://www.r-project.org/.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D.O., Barker, D. M., Duda, M.G., Huang, X.-Y., Wang, W. & Powers, J.G. 2008. A Description of the Advanced Research WRF Version 3. NCAR Tech. Note NCAR/TN-475+STR.
Sørensen, P., Cutululis, N.A., Vigueras-Rodríguez, A., Madsen, H., Pinson, P., Jensen, L.E., Hjerrild, J. & Donovan, M. 2008. Modelling of power fluctuations from large offshore wind farms. Wind Energy 11(1): 29–43.
https://doi.org/10.1002/we.246
Sørensen, P., Litong-palima, M., Hahman, A.N., Heunis, S., Ntusi, M., and Hansen, J.C. 2018. Wind power variability and power system reserves in South Africa. Journal of Energy in Southern Africa 29(1): 59–71.
https://doi.org/10.17159/2413-3051/2017/v29i1a2067
South African Weather Service. 2018. No Title. Available at: http://www.weathersa.co.za/climate/publications [Accessed July 10, 2018].
Thapar, V., Agnihotri, G. & Sethi, V.K. 2011. Critical analysis of methods for mathematical modelling of wind turbines. Renewable Energy 36(11): 3166–3177.
https://doi.org/10.1016/j.renene.2011.03.016
Ueckerdt, F., Brecha, R. & Luderer, G. 2015. Analyzing major challenges of wind and solar variability in power systems. Renewable Energy 81(2015): 1-10.
https://doi.org/10.1016/j.renene.2015.03.002
Widén, J. et al. 2015. Variability assessment and forecasting of renewables: A review for solar, wind, wave and tidal resources. Renewable and Sustainable Energy Reviews 44: 356–375.
Downloads
Published
Issue
Section
License
Copyright (c) 2019 Amaris Dalton, Bernard Bekker, Andries Kruger
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.