Essays about: "wind turbine machine learning"
Showing result 1 - 5 of 11 essays containing the words wind turbine machine learning.
-
1. Improvement of Wind Power Forecasting and Prediction of Production Losses Caused by Ice Formation on Wind Turbine Blades : - A Machine Learning Approach
University essay from Umeå universitet/Institutionen för fysikAbstract : In the ongoing climate crisis, transitioning to renewable energy sources is essential to manage the increasing energy demand. One such renewable energy source is the weather-dependent energy source, wind power. Many wind farms are located in Cold Climate (CC) regions, known for their vast potential for wind power production. READ MORE
-
2. Wind Turbine Recovery Forecasting using Survival Analysis
University essay from Lunds universitet/Matematisk statistikAbstract : The goal of this thesis is to present a methodology for predicting time until recovery of failed wind turbines. The necessity is motivated by the potential for more accurate wind energy export forecasts. The current approach rests entirely on having an expert examine the turbine and produce a time estimate. READ MORE
-
3. Wind power forecasting using random forests
University essay from Lunds universitet/Institutionen för energivetenskaperAbstract : The present thesis investigated using the random forest machine learning algorithm for wind power forecasting. Meteorological prognoses for wind speed, wind direction, gust winds, and humidity were used. For historical data, wind minimum and temperature was also included. READ MORE
-
4. ASSESMENT OF WIND POWER FORECASTING ERROR FOR GOTLAND
University essay from Uppsala universitet/Institutionen för geovetenskaperAbstract : When the wind blows and wind turbine generators harvests the kinetic energy and trans- forms it to electrical power, there is a need for predicting how much power that will be dispatched from the turbines. Even the most perfect computer model with high computa- tional power could not model the beauty of the forces of nature and we must accept some degree of forecasting error in the predicted power output due to the inherently stochastic patterns in the atmosphere. READ MORE
-
5. PREDICTION OF WIND TURBINE BLADE FATIGUE LOADS USING FEED-FORWARD NEURAL NETWORKS
University essay from Uppsala universitet/Institutionen för geovetenskaperAbstract : In recent years, machine learning applications have gained great attention in the wind power industry. Among these, artificial neural networks have been utilized to predict the fatigue loads of wind turbine components such as rotor blades. READ MORE
