Data Analytics for Renewable Energy Integration. Technologies, Systems and Society (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
167
Utgivningsdatum
2018-11-17
Upplaga
1st ed. 2018
Förlag
Springer Nature Switzerland AG
Medarbetare
Aung, Zeyar / Catalina Feli, Alejandro
Illustrationer
65 Illustrations, color; 10 Illustrations, black and white; X, 167 p. 75 illus., 65 illus. in color.
Dimensioner
234 x 156 x 10 mm
Vikt
259 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783030043025
Data Analytics for Renewable Energy Integration. Technologies, Systems and Society (häftad)

Data Analytics for Renewable Energy Integration. Technologies, Systems and Society

6th ECML PKDD Workshop, DARE 2018, Dublin, Ireland, September 10, 2018, Revised Selected Papers

Häftad Engelska, 2018-11-17
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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.
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Innehållsförteckning

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 in the City of Abu Dhabi, United Arab Emirates.