Data Analytics for Renewable Energy Integration Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers / [electronic resource] :
edited by Wei Lee Woon, Zeyar Aung, Stuart Madnick.
- 1st ed. 2014.
- IX, 151 p. 63 illus. online resource.
- Lecture Notes in Artificial Intelligence, 8817 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 8817 .
Towards Flexibility Detection in Device-Level Energy Consumption -- Balancing Energy Flexibilities Through Aggregation -- Machine Learning Prediction of Large Area Photovoltaic Energy Production -- The Research on Vulnerability Analysis in OpenADR for Smart Grid -- Improving an Accuracy of ANN-Based Mesoscale-Microscale Coupling Model by Data Categorization: With Application to Wind Forecast for Offshore and Complex Terrain Onshore Wind Farms -- PowerScope: Early Event Detection and Identification in Electric Power Systems -- Machine Learning Techniques for Supporting Renewable Energy Generation and Integration: A Survey -- A Framework for Data Mining in Wind Power Time Series -- Systematical Evaluation of Solar Energy Supply Forecasts -- Forecasting and Visualization of Renewable Energy Technologies Using Keyword Taxonomies -- Rooftop Detection for Planning of Solar PV Deployment: A Case Study in Abu Dhabi.
This book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
9783319132907
10.1007/978-3-319-13290-7 doi
Artificial intelligence.
Data mining.
Renewable energy sources.
Computer science--Mathematics.
Energy policy.
Energy and state.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Renewable Energy.
Mathematics of Computing.
Energy Policy, Economics and Management.
Q334-342 TA347.A78
006.3
Towards Flexibility Detection in Device-Level Energy Consumption -- Balancing Energy Flexibilities Through Aggregation -- Machine Learning Prediction of Large Area Photovoltaic Energy Production -- The Research on Vulnerability Analysis in OpenADR for Smart Grid -- Improving an Accuracy of ANN-Based Mesoscale-Microscale Coupling Model by Data Categorization: With Application to Wind Forecast for Offshore and Complex Terrain Onshore Wind Farms -- PowerScope: Early Event Detection and Identification in Electric Power Systems -- Machine Learning Techniques for Supporting Renewable Energy Generation and Integration: A Survey -- A Framework for Data Mining in Wind Power Time Series -- Systematical Evaluation of Solar Energy Supply Forecasts -- Forecasting and Visualization of Renewable Energy Technologies Using Keyword Taxonomies -- Rooftop Detection for Planning of Solar PV Deployment: A Case Study in Abu Dhabi.
This book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
9783319132907
10.1007/978-3-319-13290-7 doi
Artificial intelligence.
Data mining.
Renewable energy sources.
Computer science--Mathematics.
Energy policy.
Energy and state.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Renewable Energy.
Mathematics of Computing.
Energy Policy, Economics and Management.
Q334-342 TA347.A78
006.3