As more wind energy is connected to utility systems, it becomes important to understand and manage the impact of wind generation on system operations. Recent studies and simulations provide a better understanding of these impacts, and with this knowledge, progress is now being made in developing the tools and methods to minimize costs and operate reliably with higher levels of wind generation and lower level of uncertainty. In order to reduce the uncertainty in the wind generation, and facilitate the introduction of wind energy in the utility system as power capacity instead of energy source, this paper proposes a novel integrated wind DG with energy storage system. Rayleigh probability density function is used to model the wind speed during each month in the year, from which the average power and capacity factor can be estimated, which is an indication of the uncertainty of the system. Depending on this information during the year, the appropriate energy storage system can be selected.
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