Optimum Modified Fractional Order Controller for Future Electric Vehicles and Renewable Energy-Based Interconnected Power Systems

  • Emad M. Ahmed
  • , Emad A. Mohamed
  • , Ahmed Elmelegi
  • , Mokhtar Aly
  • , Osama Elbaksawi

Research output: Contribution to journalArticlepeer-review

97 Scopus citations

Abstract

Several issues have been risen due to the recent vast installations of renewable energy sources (RESs) instead of fossil fuel sources in addition to the replacement of electric vehicles (EVs) for fuel-powered vehicles. Mitigating frequency deviations and tie-line power fluctuations has become driving challenge for the control design of interconnected power systems. RESs represent continuously varying power generators due to their nature and dependency on the environmental conditions. In this context, this article presents a new modified hybrid fractional order controller for load frequency and EVs control in interconnected power systems. The new controller combines the benefits of two widely employed fractional order controllers, including the FOPID and TID controllers. In addition, a new practical application of recent artificial ecosystem optimization (AEO) method has been proposed in this article for determining simultaneously the optimum controller parameters. The proposed controller and optimization method are validated on two areas interconnected power system with different types of RESs and with considering the natural characteristics of sources, EVs and load variations. Obtained simulation results verify the superior performance of the proposed controller and optimization method for achieving high mitigation of frequency fluctuations and tie-line power deviations, increased robustness, enhanced system stability over a wide range of parameters uncertainty and fast response during transients.

Original languageEnglish
Article number9352782
Pages (from-to)29993-30010
Number of pages18
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Artificial ecosystem optimization
  • electric vehicles (EVs)
  • fractional order controller
  • load frequency control
  • renewable energy sources

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