RT info:eu-repo/semantics/masterThesis
T1 Machine Learning for the Power Generation Forecast of a Wind Farm
A1 March Ruiz, Jonathan
A2 Máster Universitario en Energías Renovables
AB One of the greatest challenges of the wind energy nowadays is the delivery of its power outputinto the energy grid, because of the intermittency of the wind speed and the fluctuating nature.For that reason, an accurate forecast for the short-term period is necessary to increase the insertionof wind power into the energy mix, as well as preventing extreme events and other possibledrawbacks. In this regard, Machine Learning algorithms have played an important role in the windpower prediction in recent years, since this automatic learning method presents several advantagesthat make it ideal for this task. In this study two Machine Learning approaches will be studiedand developed with Python, the Linear Regression algorithm and the Multilayer Perceptronalgorithm, which is a kind of Artificial Neural Network, applying them to the dataset with realmeasures (wind speed, power generation, temperature,…) of an actual wind farm for a two-yearperiod as a case study. The two algorithms will have multiple variables of the set as inputs inorder to learn from the existing data, train the corresponding algorithm, so it can be utilised toforecast future wind power generation. Both models will be validated with the aim of verifyingthe accuracy of the methods.
YR 2021
FD 2021
LK http://riull.ull.es/xmlui/handle/915/23105
UL http://riull.ull.es/xmlui/handle/915/23105
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 02-may-2024