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- W2897720906 abstract "To optimally dispatch uncertain, energy-constrained reserves, model predictive control offers a viable tool to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. Therefore, this paper investigates the uncertainty associated with energy-constrained aggregations of flexible distributed energy resources (DERs). The uncertainty studied herein is associated with estimating the capacity of and the estimated state of charge from an aggregation of DERs. To that effect, a risk-based chance constrained MPC (RB-CC-MPC) is developed that co-optimizes the operational risk of prematurely saturating the (virtual) energy storage against deviating generators from their scheduled set-point. On a fast minutely timescale, the RB-CC-MPC coordinates energy-constrained virtual resources to minimize unscheduled participation of and overcome ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. To illustrate the effectiveness of the proposed method, simulation-based analysis is carried out on an augmented IEEE RTS-96 network with uncertain energy resources." @default.
- W2897720906 created "2018-10-26" @default.
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- W2897720906 date "2018-10-19" @default.
- W2897720906 modified "2023-09-27" @default.
- W2897720906 title "Corrective dispatch of uncertain energy resources using chance-constrained receding horizon control" @default.
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- W2897720906 hasPublicationYear "2018" @default.
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