Don't miss a chance to join 5th Edition Big Data Forum!
The fifth Wind Power Big Data Forum will disclose practical insight for the Big Data management in order to improve Wind Power farms reliability, sustainability and overall performance.
Attendees will gather to discuss the importance of the data-driven predictive maintenance and to develop optimized strategy for the Wind Farm performance. Advanced data analytics serves to improve business processes and value chain simultaniously lowering infrastructure cost with a secure and flexible data infrastructure. Integrated Big Data platfroms based on IoT develop analytical opportunities, for planning and forecasting revealing the bright future for the Wind industry.
Get an insight on best practices and techniques from the Wind Power experts!
- Gain insight on the key facts on how to implement the methodology to they own assets
- Examine the real challenges to face in CMS (Condition Monitoring Systems based on SCADA Data)implementation
- Understand how to uses machine learning algorithms for turbine performance monitoring
- Discover how machine learning techniques improve the yield of a wind turbine
- Learn about predictive maintenance techniques that are possible when data collection is streamlined and repeatable
- Demonstrate the importance and challenges of power forecasting for wind farm portfolios
Join us on 2 days senior-level meeting to explore latest wind power performance development trends, improve existing approaches, master your inventory use and later share gained powerful knowledge within your company.
Past Annual Summary
- Learning the importance and advantages of Big Data and IoT usage in wind
- Applying predictive maintenance approach to wind farm performance
- Enhancing assets integrity and reliability
- Getting an overview of the newest data analysis techniques
Some of our Speakers from 2017:
- Energy & Utilities
- Operation and Maintenance
- Technological solution providers :
- Vice president
- CEO, CTO
- Researcher, Expert
- Lead, Head, Director
- Specialist, Engineer