Dieses Buch fokussiert auf zwei zentrale Aspekte im Betrieb von Windparks: Entscheidungen und Steuerung. Im ersten Teil werden Entscheidungsprozesse erläutert, bei denen der Betrieb von Hybrid-Windparks von der Auswahl optimaler Alternativen zur Einspeisung von Windenergie ins Netz abhängt. Präzise Windvorhersagen sind entscheidend, um Fehler auszugleichen und mittels eines Batteriespeichersystems Reservekapazitäten ins Netz einzuspeisen. MCDM-Methoden und ein unscharfer Ansatz werden verw...

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMSRenewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design.Due to the importance of renewable energy...

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction an...

This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecast...