Loading...

Uncertainty cost of stochastic producers: metrics and impacts on power grid flexibility

Pourahmadi, F ; Sharif University of Technology | 2022

39 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/TEM.2020.2970729
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage robust SCUC, one through a fixed and the other via an adjustable uncertainty set, for which the state-of-the-art techniques may not be always feasible, efficient, and practical. To address these concerns and to account for the effects of the uncertainty cost resulting from dispatch limitations of flexible resources, a new framework centered on the adjustable penetration of stochastic generation is proposed. Our hypothesis is that if the SCUC is scheduled with an appropriate dispatch level of stochastic generation, the system uncertainty cost will decrease, and subsequently, the system's ability to accommodate additional uncertainty will improve. Numerical simulations on a modified IEEE 73-bus test system verify the efficiency of the suggested assessment techniques. © 1988-2012 IEEE
  6. Keywords:
  7. Measurement ; Random processes ; Robustness (control systems) ; Stochastic systems ; Uncertainty analysis ; Wind power ; Adjustable penetration ; Indexes ; Operational flexibility ; Optimal uncertainty set ; Power grids ; Stochastic generation ; Uncertainty ; Wind farm ; Electric power transmission networks
  8. Source: IEEE Transactions on Engineering Management ; Volume 69, Issue 3 , 2022 , Pages 708-719 ; 00189391 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9011571