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A novel probabilistic method for under frequency load shedding setting considering wind turbine response

Ashouri Zadeh, A ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1109/TPWRD.2021.3113284
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. The Under Frequency Load Shedding (UFLS) is the last automated action to restore power system frequency stability when a severe contingency causes a significant drop in the frequency of interconnection or islanded areas. In this paper, a novel probabilistic algorithm that considers the wind turbine frequency response is proposed to design and optimize the UFLS scheme. The uncertainties of power systems such as wind speed, hourly load, inertia time constant, and generation losses are taken into account. The Monte-Carlo Simulation (MCS) method is used to model the power system uncertainties. Additionally, a novel method is developed to calculate the power system frequency response and accelerate the multistage UFLS scheme optimization processes. In this method, a time-independent formulation for power system frequency response is utilized to reduce the computational complexity. More than Twenty different UFLS plans are designed using the proposed probabilistic algorithm. Besides, some time-domain simulations are carried on the modified IEEE 39-bus test system to investigate the performance of the designed UFLS schemes. Results indicate that designed UFLS schemes provide stable frequency response and improve the power system frequency stability. © 1986-2012 IEEE
  6. Keywords:
  7. Frequency stability ; Uncertainty ; Under frequency load shedding ; Wind turbine ; Electric power plant loads ; Frequency response ; Monte Carlo methods ; Time domain analysis ; Wind ; Wind turbines ; Power system frequencies ; Probabilistic algorithm ; Probabilistic methods ; System uncertainties ; Time constants ; Time independents ; Time-domain simulations ; Underfrequency load-shedding ; Electric load shedding
  8. Source: IEEE Transactions on Power Delivery ; Volume 37, Issue 4 , 2022 , Pages 2640-2649 ; 08858977 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9540244