Data Analytics for Renewable Energy Integration
4th ECML PKDD Workshop, DARE 2016, Riva del Garda, Italy, September 23, 2016, Revised Selected Papers
Published on 19. January 2017
Book
Paperback/Softback
VII, 137 pages
978-3-319-50946-4 (ISBN)
Description
This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held in Riva del Garda, Italy, in September 2016.
The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
58 s/w Abbildungen
VII, 137 p. 58 illus.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
238 gr
ISBN-13
978-3-319-50946-4 (9783319509464)
DOI
10.1007/978-3-319-50947-1
Schweitzer Classification
Other editions
Additional editions
Wei Lee Woon | Zeyar Aung | Oliver Kramer
Data Analytics for Renewable Energy Integration
4th ECML PKDD Workshop, DARE 2016, Riva del Garda, Italy, September 23, 2016, Revised Selected Papers
E-Book
01/2017
Springer
€53.49
Available for download
Content
Locating Faults in Photovoltaic Systems Data.- Forecasting of Smart Meter Time Series Based on Neural Cybersecurity for Smart Cities: A Brief Review.- Machine Learning Prediction of Photovoltaic Energy from Satellite Sources.- Approximate Probabilistic Power Flow.- Dealing with Uncertainty: An Empirical Study on the Relevance of Renewable Energy Forecasting Methods.- Measuring Stakeholders' Perceptions of Cybersecurity for Renewable Energy Systems.- Selection of Numerical Weather Forecast Features for PV Power Predictions with Random Forests.- Evolutionary Multi-Objective Ensembles forWind Power Prediction.- A Semi-Automatic Approach for Tech Mining and Interactive Taxonomy Visualization.- Decomposition of Aggregate Electricity Demand into the Seasonal-Thermal Components for Demand-Side Management Applications in "Smart Grids".