Wind Energy Yield Forecasting Innovation Project

The Wind Energy Yield Forecasting project is an award-winning innovation for wind energy yield prediction using weather and electricity generation data. It developed a Random Forest Regression prediction model with Machine Learning to forecast wind speed and energy output, created by Mr. Rittichai Liamthong, Business Development Engineer, Business Development Department.

Benefits: Increased Accuracy:

• Enhances the precision of wind energy yield forecasts.
• Budget Planning: Aids in efficient budget planning processes.
• Enhanced Efficiency: Improves overall energy management efficiency.
• Reduced Risk: Mitigates risks from inaccurate predictions.

Expected Project Impacts:

• Reduced Error: Decreased prediction errors from 66% to 1.36% in June 2023 and 3.06% in September 2023.
• Time Savings: Shortened assessment time, enabling future benefit expansion independently.
• Cost Reduction: Typically, the Group hires external companies for calculation and evaluation.
• Increased Opportunity: Enhances investment opportunities; the system can quickly assess wind power plant investment feasibility in the future.
• Innovation Implementation Date: January 2023.