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The impact of integrating 20% of renewable resources, primarily wind and solar, on regulation and load following requirements within the California Independent System Operator (CAISO)'s Balancing Authority Area is analyzed in detail. The analysis entails a stochastic process that employs Monte Carlo simulations and uses a random number generator to generate forecast errors over multiple iterations. Load and wind forecast errors are simulated based on the statistical characteristics (standard deviation and autocorrelation) of actual historical forecast error data. A refined persistence model is used to simulate real-time solar forecast errors. Clearness Index (CI) is used in the simulation of hour-ahead and real-time solar forecast errors. Various aspects of the CAISO operating practices and market timelines are modeled in detail from hour-ahead to real-time dispatch to provide realistic intra-hour operational requirements. Also, statistical interactions of load, wind and solar generation in a minute-to-minute interval are modeled with sufficient details to evaluate the regulation and load following capacity, ramp rate and ramp duration requirements in the 2012 timeframe. A comparison of these requirements is made between 2006 and 2012.