North America Wind Power Big Data and IoT Forum

May 30 & 31, 2017 - Boston, Massachusetts, USA

North America Wind Power Big Data and IoT Forum

North America Wind Power Big Data and IoT Forum features 29 speakers in 19 interactive sessions, discussing predictive analytics for wind turbine performance and monitoring.

Agenda Highlights

  • Meeting Market Challenges with Big Data – Opportunities to Reduce the LCOE and Increase the Uptake of Wind Energy
  • Creating and Delivering the Digital Services ‘App Store’
  • How Does my Wind Farm Compare to the Rest of the Industry? An Inside Look on Leveraging Disparate Datasets
  • A Machine Learning Method for Wind Power Curve Modeling and Its Impact
  • NoSQL Databases and Ideal Data Architecture for Storing Time Series Data
  • Using Data Analytic Tools to Reduce Component Failures and Operational Costs
  • A Big Data Approach to Wind Turbine Condition Monitoring
  • Developing a Data-Driven Predictive Maintenance Strategy to Optimize Wind-Turbine Performance and Life Extension
  • Predictive and Condition based Maintenance Solutions as Case Sample in the Wind Industry
  • Bring Down Costs through an Effective Approach to Condition Monitoring and Data Analysis
  • Big Data Analytics for Optimised Wind Farm Operation and Maintenance
  • The Overall Architecture of Wind Power Asset Life Cycle Management System based on IoT
  • Effective Reliability-Centered Maintenance: Minimizing Costs and Risk
  • Advanced Predictive Maintenance for Increased Turbine Efficiency and Reliability

Key Learning Benefits

  • Leverage risk based monitoring to drive greater efficiency
  • Learn how quantifying of the impact of various flow conditions on turbine performance can all for better detection of underperformance
  • Understand how to uses machine learning algorithms for turbine performance monitoring
  • Discover how to accurately monitor the performance in wind parks in each turbine at anytime during their life time
  • Gain an understanding of how to optimize Wind Turbine Performance and reduce O&M costs through Big Data
  • Discover how machine learning techniques improve the yield of a wind turbine
  • Understand how to improve the accuracy of commercial renewable energy forecasting systems
  • Learn how to monitor the performance of all your turbines in the wind park, observe changes in the power curve over the complete life time and compare them to each other