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Explore the complex statistical properties of wind power fluctuations through a comprehensive analysis of data from an 80-turbine wind farm spanning 20 kilometers over five years. Discover how wind energy production exhibits universal, collective, and nonlinear correlations that create excess persistence and intermittency in aggregated power output, challenging conventional assumptions about power smoothing effects. Learn about the transition from local decoherence to large-scale turbulence-driven scaling through space-time correlation analysis, and examine bivariate analysis techniques that reveal nonlinear dependencies between individual turbine outputs. Understand how these nonlinear correlations contribute to stronger intermittency in total farm output than expected from simple averaging, and explore the implications for grid stability, renewable energy integration, and wind farm design optimization. Gain insights into advanced statistical methods for characterizing wind power fluctuations and their applications in grid management and storage optimization strategies, presented by Mahesh Bandi from the Okinawa Institute of Science and Technology in collaboration with researchers from JSPS and Exus Renewables North America.
