Data Analytics for Renewable Energy Integration. Technologies, Systems and Society
6th ECML PKDD Workshop, DARE 2018, Dublin, Ireland, September 10, 2018, Revised Selected Papers
(Sprache: Englisch)
This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018.
The 9 papers presented in this volume were carefully...
The 9 papers presented in this volume were carefully...
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Klappentext zu „Data Analytics for Renewable Energy Integration. Technologies, Systems and Society “
This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018.The 9 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.
Inhaltsverzeichnis zu „Data Analytics for Renewable Energy Integration. Technologies, Systems and Society “
Mathematical Optimization of Design Parameters of Photovoltaic Module.- Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features.- Sampling Strategies for Representative Time Series in Load Flow Calculations.- Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale.- Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation.- Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access.- Contribution Machine learning as Surrogate to Building Performance Simulation: A Building Design Optimization Application.- Clustering River Basins using Time-Series Data Mining on Hydroelectric Energy Generation.- Short-Term Electricity Consumption Forecast using Datasets of Various Granularities?.- Intelligent Monitoring of Transformer Insulation using Convolutional Neural Networks.- Nonintrusive Load Monitoring based on Deep Learning.- Urban Climate Data Sensing, Warehousing, and Analysis: A Case Study inthe City of Abu Dhabi, United Arab Emirates.
Bibliographische Angaben
- 2018, 1st ed. 2018, X, 167 Seiten, 65 farbige Abbildungen, Maße: 15,7 x 23,6 cm, Kartoniert (TB), Englisch
- Herausgegeben: Wei Lee Woon, Zeyar Aung, Alejandro Catalina Feliú, Stuart Madnick
- Verlag: Springer, Berlin
- ISBN-10: 3030043029
- ISBN-13: 9783030043025
Sprache:
Englisch
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