Optimal sharing of quantity risk for a coalition of wind power producers facing nodal prices
KAUST Grant Number025478
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AbstractIt is widely accepted that aggregation of geographically diverse wind energy resources offers compelling potential to mitigate wind power variability, as wind speed at different geographic locations tends to decorrelate with increasing spatial separation. In this paper, we explore the extent to which a coalition of wind power producers can exploit the statistical benefits of aggregation to mitigate the risk of quantity shortfall with respect to forward contract offerings for energy. We propose a simple augmentation of the existing two-settlement market system with nodal pricing to permit quantity risk sharing among wind power producers by affording the group a recourse opportunity to utilize improved forecasts of their ensuing wind energy production to collectively modify their forward contracted positions so as to utilize the projected surplus in generation at certain buses to balance the projected shortfall in generation at complementary buses. Working within this framework, we show that the problem of optimally sizing a set of forward contracts for a group of wind power producers reduces to convex programming and derive closed form expressions for the set of optimal recourse policies. We also asses the willingness of individual wind power producers to form a coalition to cooperatively offer contracts for energy. We first show that the expected profit derived from coalitional contract offerings with recourse is greater than that achievable through independent contract offerings. And, using tools from coalitional game theory, we show that the core for our game is non-empty.
CitationBitar EY, Baeyens E, Khargonekar PP, Poolla K, Varaiya P (2012) Optimal sharing of quantity risk for a coalition of wind power producers facing nodal prices. 2012 American Control Conference (ACC). Available: http://dx.doi.org/10.1109/ACC.2012.6315524.
SponsorsSupported in part by OOF991-KAUST US LIMITED under awardnumber 025478, the UC Discovery Grant ele07-10283 under the IMPACTprogram, NSF under Grant EECS-0925337, NSF Grant ECCS-1129061,and the Florida Energy Systems Consortium. Thanks to Ram Rajagopal formany helpful discussions.