Research Paper#Renewable Energy, Power Grid Optimization, Machine Learning🔬 ResearchAnalyzed: Jan 4, 2026 00:09
Economic and Reliability Benefits of Improved Offshore Wind Forecasting
Analysis
This paper investigates the economic and reliability benefits of improved offshore wind forecasting for grid operations, specifically focusing on the New York Power Grid. It introduces a machine-learning-based forecasting model and evaluates its impact on reserve procurement costs and system reliability. The study's significance lies in its practical application to a real-world power grid and its exploration of innovative reserve aggregation techniques.
Key Takeaways
Reference
“The improved forecast enables more accurate reserve estimation, reducing procurement costs by 5.53% in 2035 scenario compared to a well-validated numerical weather prediction model. Applying the risk-based aggregation further reduces total production costs by 7.21%.”