CODE: RE29
DURATION: 5 Days/10 Days
CERTIFICATIONS: CPD
This course explores the integration of advanced data analytics, machine learning, and predictive modeling techniques to enhance the accuracy of renewable energy forecasting and improve grid reliability. Participants will gain insights into how big data is transforming energy systems by enabling smarter decision making, balancing supply and demand, optimizing storage, and ensuring stability in increasingly complex and renewable dominated power grids.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the role of big data in renewable energy forecasting and grid management.
Apply data analytics and machine learning models to predict renewable generation and demand fluctuations.
Assess challenges and opportunities in integrating renewables into the grid.
Develop strategies to enhance grid stability through real-time data-driven decision-making.
Analyze case studies to identify best practices in renewable energy forecasting and grid operation.
At the end of this course, you’ll understand:
This course is designed for energy professionals, grid operators, utility managers, renewable project developers, data scientists, policymakers, and researchers interested in applying big data and advanced analytics to the renewable energy sector. It is particularly beneficial for professionals tasked with ensuring grid stability, integrating renewable energy sources, or developing data-driven solutions for energy forecasting and management.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
