TY - JOUR
T1 - Probabilistic Reliability Evaluation including Adequacy and Dynamic Security Assessment
AU - Wang, Yingying
AU - Vittal, Vijay
AU - Abdi-Khorsand, Mojdeh
AU - Singh, Chanan
N1 - Funding Information:
Manuscript received January 5, 2019; revised March 20, 2019 and May 7, 2019; accepted June 16, 2019. Date of publication June 20, 2019; date of current version January 7, 2020. This work was supported by the Power System Engineering Research Center. Paper no. TPWRS-00018-2019. (Corresponding author: Vijay Vittal.) Y. Wang, V. Vittal, and M. Abdi-Khorsand are with the Department of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281 USA (e-mail: ywang935@asu.edu; vijay.vittal@asu.edu; mojdeh. khorsand@asu.edu).
Publisher Copyright:
© 1969-2012 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - The growing penetration of variable renewable sources and the competitive power system environment make the application of probabilistic reliability techniques all the more important. Although probabilistic methods have been widely used in resource adequacy assessment, using probabilistic methodologies for reliability evaluation including system dynamic security need to be investigated. This paper proposes a probabilistic methodology for integrated reliability evaluation considering resource adequacy and dynamic security assessment in a unified framework. Sequential Monte Carlo simulation (SMCS) is chosen because of its ability to consider time-varying sequential characteristics. By using an optimization model, which minimizes load curtailment for adequacy assessment, and representing stability preserving protection systems in security assessment, the proposed approach gives quantitative integrated reliability evaluation results. In addition, two acceleration methods are introduced to improve computational efficiency. The proposed approach is demonstrated on a synthetic test system and the results illustrate the efficacy of an integrated reliability evaluation approach.
AB - The growing penetration of variable renewable sources and the competitive power system environment make the application of probabilistic reliability techniques all the more important. Although probabilistic methods have been widely used in resource adequacy assessment, using probabilistic methodologies for reliability evaluation including system dynamic security need to be investigated. This paper proposes a probabilistic methodology for integrated reliability evaluation considering resource adequacy and dynamic security assessment in a unified framework. Sequential Monte Carlo simulation (SMCS) is chosen because of its ability to consider time-varying sequential characteristics. By using an optimization model, which minimizes load curtailment for adequacy assessment, and representing stability preserving protection systems in security assessment, the proposed approach gives quantitative integrated reliability evaluation results. In addition, two acceleration methods are introduced to improve computational efficiency. The proposed approach is demonstrated on a synthetic test system and the results illustrate the efficacy of an integrated reliability evaluation approach.
KW - Dynamic security assessment
KW - Monte-Carlo simulation
KW - reliability
KW - renewable integrated grid
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U2 - 10.1109/TPWRS.2019.2923844
DO - 10.1109/TPWRS.2019.2923844
M3 - Article
AN - SCOPUS:85078414231
VL - 35
SP - 551
EP - 559
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
SN - 0885-8950
IS - 1
M1 - 8742636
ER -