Fuzzy Mamdani-based Model Predictive Load Frequency Control

Mohammad Saeid Akbari, Ali Akbar Safavi, Navid Vafamand, Tomislav Dragicevic, Jose Rodriguez

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.
Original languageEnglish
Title of host publicationProceedings of 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems
PublisherIEEE
Publication date2020
Pages7-12
ISBN (Print)9781728169897
DOIs
Publication statusPublished - 2020
EventIEEE 11th International Symposium on Power Electronics for Distributed Generation Systems - Virtual event, Dubrovnik, Croatia
Duration: 28 Sep 20201 Oct 2020

Conference

ConferenceIEEE 11th International Symposium on Power Electronics for Distributed Generation Systems
LocationVirtual event
CountryCroatia
CityDubrovnik
Period28/09/202001/10/2020
Series2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)
ISSN2329-5767

Keywords

  • Load frequency control (LFC)
  • Model predictive control (MPC)
  • Fuzzy logic
  • Online cost function tuning
  • Isolated microgrid

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