Impact of electric vehicles aggregators with communication delays on stability delay margins of two-area load frequency control system

Naveed A., Sonmez S., AYASUN S.

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, vol.43, no.12, pp.2860-2871, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 43 Issue: 12
  • Publication Date: 2021
  • Doi Number: 10.1177/01423312211014420
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Page Numbers: pp.2860-2871
  • Keywords: Communication time delays, electric vehicles aggregators, frequency regulation, PI controller, stability delay margin, TIME-DELAY, DEPENDENT STABILITY, POWER-SYSTEMS, CONSTANT, COMPUTATION, GAIN, ROBUSTNESS
  • Gazi University Affiliated: Yes


This paper investigates the impact of electric vehicles (EVs) aggregator with communication time delay on stability delay margin of a two-area load frequency control (LFC) system. A frequency-domain exact method is used to calculate stability delay margins for various values of proportional-integral (PI) controller gains. The proposed method first eliminates the transcendental terms in the characteristic equation without using any approximation and then transforms the transcendental characteristic equation into a regular polynomial using a recursive approach. The key result of the elimination process is that real roots of the new polynomial correspond to imaginary roots of the transcendental characteristic equation. With the help of new polynomial, delay-dependent system stability and root tendency with respect to the time delay is determined. An analytical formula is then developed to compute delay margins in terms of system parameters. The qualitative impact of EVs aggregator on stability delay margins is thoroughly analysed and the results are verified by time domain simulations and quasi-polynomial mapping-based root finder (QPmR) algorithm.