Abstract: When wind power participates in primary frequency regulation through active power reserve or energy storage integration, the coordination strategy and capacity allocation significantly impact the performance and economic efficiency of wind-storage frequency regulation systems. This paper presents a coordinated primary frequency regulation and capacity optimization strategy for wind power and shared energy storage that accounts for wind farm cluster effects. The methodology develops a high-dimensional dynamic Vine Copula function to characterize correlations and uncertainties among multiple wind farms using correlated wind speed forecasting, while incorporating cluster effects including wake effects, time-delay impacts, and terrain influences. A reserved power allocation strategy for wind turbines is proposed considering both turbine performance and operational economics. Furthermore, an opportunity-constrained programming model optimizes energy storage capacity with the objective of minimizing primary frequency regulation reserve costs while incorporating cluster effects. Case studies validate the effectiveness of the proposed model and strategy, while analyzing how spatiotemporal wind speed correlations and wind power cluster characteristics influence primary frequency regulation capacity planning.