Frequency control of the islanded microgrid based on optimised model predictive control by PSO

Masoud Dashtdar, Aymen Flah, Claude Ziad El-Bayeh, Marcos Tostado-Véliz, Ahmed Al Durra, Shady H.E. Abdel Aleem, Ziad M. Ali

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


In this paper, the amount of microgrid frequency deviation in the dynamic state can be reduced by improving the frequency controller and implementing a new method. The proposed controller is designed for a microgrid including renewable resources, and the proposed control strategy is such that the controller coefficients are adjusted and optimised at all times by the model predictive control (MPC). The weight parameters of the MPC controller have been optimised by the particle swarm optimisation (PSO) algorithm. The proposed controller is located in the secondary frequency control loop, and by applying a control signal to the sources, the frequency perturbations following the power changes in the microgrid are reduced. The simulation results show that the proposed controller performs better than the Ziegler–Nichols PI controller (PI-ZN) method, PI-based controllers that rely on fuzzy logic (PI-Fuzzy), the fractional-order proportional-integral-derivative (FOPID) controller that is based on chaos particle swarm optimisation (FOPID-CPSO) algorithm and the PID controllers based on CPSO algorithm (PID-CPSO). It has been able to effectively reduce the frequency fluctuations in terms of amplitude and number of oscillations is also more resistant to the uncertainty of microgrid parameters and shows better performance when changing parameters than other methods.

Original languageBritish English
Pages (from-to)2088-2100
Number of pages13
JournalIET Renewable Power Generation
Issue number10
StatePublished - 27 Jul 2022


Dive into the research topics of 'Frequency control of the islanded microgrid based on optimised model predictive control by PSO'. Together they form a unique fingerprint.

Cite this