Differences in Wind Forecast Accuracy in the German North and Baltic Seas

Zastrau, D; Schlaak, Marius; Bruns, Thomas; Elsner, Robert; Herzog, Otthein

doi:10.7763/ijesd.2014.v5.549

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…where V measured, i and V predicted, i are the measured and predicted wind speed at ith time instant and N(t) is the total number of observations (Figure 10). These RMSE and MAE error ranges match with other published results such as Zastrau et al 40…”

Section: Validation Of Markov Approach With a Reference Wind Measurementsupporting

confidence: 92%

Statistical wind prediction and fatigue analysis for horizontal-axis wind turbine composite material blade under dynamic loads

Kulkarni

Dhoble

et al. 2017

Advances in Mechanical Engineering

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The purpose of this article is to analyze various wind speed-forecasting methods, select the appropriate method for developing synthetic wind speed for 1-year period at Salem in Tamilnadu state in India, and use it for the structural and fatigue analysis of a small horizontal-axis wind turbine blade made of composite material. Various forecasting models such as Markov chain, Kalman filter, and autoregressive integrated moving average are evaluated, and a long-term wind speed pattern at Salem is developed using Markov chain. This wind pattern is used to create time-varying loads using the blade element momentum on blade sections. Then, the fatigue analysis of the blade is carried out using the stress life approach. The blade is found to have available life of about 20 years and the critical area for fatigue is found on the skin near the root of the blade. Various blade skin materials are also compared for fatigue performance. A cohesive zone model of the adhesively joined root joint is also developed and analyzed for fatigue at the metal-composite joint. Thus, an integrated methodology involving high-fidelity modeling of the blade, wind forecasting, and static and fatigue analysis is developed for horizontal-axis wind turbine blade for locations where historically wind speed measurements are available for short time.

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Section: Validation Of Markov Approach With a Reference Wind Measurementsupporting

confidence: 92%

Statistical wind prediction and fatigue analysis for horizontal-axis wind turbine composite material blade under dynamic loads

Kulkarni

Dhoble

et al. 2017

Advances in Mechanical Engineering

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“…The forecast is calculated based on this assimilation in 3-hourly intervals out to 174 hours, i.e., more than 7 days. The wind field forecasts in this work are given in terms of the forecasting look-ahead time t i : t + t 1 seasonal but no significant geographical variability of the DWD wind forecast accuracy in the German North and Baltic Seas (for a detailed evaluation, see [4]). This work will validate those results on an oceanic scale.…”

Section: Wind and Wave Forecastsmentioning

confidence: 99%

The Relation between Storm Risk and Wind and Wave Forecast Accuracy in the North Atlantic Ocean

Zastrau¹,

Schlaak²,

Bruns³

et al. 2015

IJESD

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“…The above-mentioned applications use short and long-time horizon weather forecasts as input to the prediction model. However, the uncertainty level in long-term weather forecasts increases with time [24]. This adversely affects the accuracy of predicted SoR.…”

Section: Introductionmentioning

confidence: 99%

State of Risk Prediction for Management and Mitigation of Vegetation and Weather Caused Outages in Distribution Networks

Baembitov,

Kezunovic

2023

IEEE Access

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The paper proposes a novel approach for the outage State of Risk (SoR) assessment caused by weather and vegetation in the distribution grid. Machine Learning prediction algorithm is used in conjunction with GIS application for mapping the SoR for the entire network. The proposed optimization approach leads to the specification of the mitigation strategies that utility staff and customers can coordinate to minimize the impact of outages. The resulting SoR assessment enables the implementation of an innovative decisionmaking solution for utility operators, represented in the form of risk maps. Additionally, utilizing the SoR assessments, a Customer Notification System (CNS) is introduced to enhance customer awareness and facilitate the adoption of mitigation measures. This holistic approach shifts outage management from a reactive process to a proactive initiative, promoting grid resilience and reliability through planned outage mitigation.

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Differences in Wind Forecast Accuracy in the German North and Baltic Seas

Abstract: Index Terms-Offshore, risk analysis on sea weather forecast, wind speed and wind direction.

Cited by 4 publications

References 3 publications

Statistical wind prediction and fatigue analysis for horizontal-axis wind turbine composite material blade under dynamic loads

Statistical wind prediction and fatigue analysis for horizontal-axis wind turbine composite material blade under dynamic loads

The Relation between Storm Risk and Wind and Wave Forecast Accuracy in the North Atlantic Ocean

State of Risk Prediction for Management and Mitigation of Vegetation and Weather Caused Outages in Distribution Networks

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