Abstract
As wind is a low capacity factor source of power generation, a nonphysically firm connection strategy is key to its cost-effective and timely integration to presently constrained transmission networks. This paper, therefore, outlines the design and study of an optimal nonfirm wind capacity allocation model. While a precise statistical representation of wind power variations and geographical interdependency requires a significant number of data samples, the structured very-large-scale linear programming problem that results is shown to be exploitable by the Benders' decomposition scheme. Various wind capacity target levels are considered, and important sensitivity analyses are performed for multiple load profiles, wind profiles, and fuel price parameter values. Interestingly, the optimal wind capacity allocation is found to be reasonably robust to sizeable load and fuel price deviations, and while the effect of a limited historical wind data profile is more influential, the associated cost-function penalty is not significantly critical. The economic value of combining wind connection with advanced postcontingency network remedial action schemes is also highlighted.
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