The objective of this research is to develop a robust metric for measuring and forecasting short-term intra-hour variability of wind power with the ultimate goal of managing the variability to the desired level. The proposed metric uses the statistical range as a measure of dispersion for the varying wind power output. Intellectual Merit: The merit of the proposed work lies in a novel metric to quantify and forecast intra-hour wind power variability and methods to manage it to the desired level. The new metric, appropriately termed conditional range metric, provides the largest wind power excursion over given duration, wind power production level, and coverage rate. New methods for allocating system reserve and sizing and control of distributed energy storage systems will be developed to demonstrate the efficacy of the metric in managing variability at the transmission and distribution system levels, respectively. Broader Impact: The outcome of the proposed work is expected to provide fundamental understanding of wind power variability. The novel conditional range metric makes possible the analysis of factors and conditions such as time (season) of interests, duration of observation, level of wind power production, and coverage rates affecting variability. The new metric is expected to aid system planners and operators to quantify variability accurately, and thus allows for better integration and management of variable wind power. The proposed work also provides additional resources to develop new undergraduate- and graduate-level learning materials. Examples include but not limited to undergraduate-level class projects and hands-on senior-design level projects in simulating and managing variability using a battery system, as well as development of a new graduate-level course in wind power integration.
