Smart Grid Wind Power Generation Variation
Wind power's significant role in the global energy mix, challenges of wind power forecasting, wind speed variation, wind power calculation, importance of wind power forecasting for grid stability, different types of wind power models, and conclusions on wind power variability and forecasting.
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Presentation Transcript
ELEC-E8423 - Smart Grid Wind power generation variation and its modeling Muhammad Rehan, Immanuel Williams
Introduction Wind power has the potential to play a significant role in the global energy mix In Finland, electricity production from wind power increased by 41 percent 14.1 percent of Finland s electricity consumption was covered by wind power in 2022 Main problem: Intermittent in nature, forecasting 24.02.2025 Page 2
Wind speed variation Approximate increase of speed with height: v2 = v1(?2 ?1)n Source: globalwindatlas.info 24.02.2025 Page 3
Wind power calculation Cp Curves Coefficient of Performance Cp = Rotor Power/Wind Power Max Cp for Wind Turbines = 0.59 (Betz Limit) For Vertical Axis Wind max theoretical Cp is lower than the Horizontal Axis Turbine 24.02.2025 Page 4
Wind power calculation Power vs Speed Curves Source: Dupont et al (2017) Source: https://ca.audubon.org/conservation/wind-power Wind power Power output Source: Inoue et al (2006) 24.02.2025 Page 5
Forecast of wind power Why do we even need a forecast? Wind power variation has enormous effects on the whole grid Needed to install effective countermeasures against these effects Without a forecast, a TSO has to assume that there is no wind generation Types of forecasting Very short term Short term Medium term Minutes to hours Up to following week Up to 72 hours Controlling wind turbine Scheduling maintenance Used by TSO How is it used? Used for trading/setting bids to the electricity market based on the view of the power production in the near future Forecast tool needs a capability of at least 36 hours with hourly resolution 24.02.2025 Page 6
Types of wind power models Source: Wang et. Al. (2021) 24.02.2025 Page 7
Conclusions Wind speed variation depends on numerous factors like height and weather TSOs have to know the exact wind power output hence forecasting is necessary Forecasting is also necessary for grid stability There are multiple forecasting models but hybrid models are the most popular among them. 24.02.2025 Page 8
Source material used Yun Wang, Runmin Zou, Fang Liu, Lingjun Zhang, Qianyi Liu, A review of wind speed and wind power forecasting with deep neural networks, Applied Energy, Volume 304, 2021, 117766, H. Holttinen, R. Hirvonen (2005) "Power system requirements for wind power" in Wind Power in Power Systems. New York: Wiley pp. 143-167. Fingrid.fi Globalwindatlas.info 24.02.2025 Page 9
