z-logo
open-access-imgOpen Access
Design of intelligent load frequency control strategy using optimal fuzzy-PID controller
Author(s) -
Nour El Yakine Kouba,
Mohamed Menaa,
Mourad Hasni,
Mohamed Boudour
Publication year - 2016
Publication title -
international journal of process systems engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-6350
pISSN - 1757-6342
DOI - 10.1504/ijpse.2016.081207
Subject(s) - control theory (sociology) , pid controller , robustness (evolution) , particle swarm optimization , fuzzy logic , automatic frequency control , frequency deviation , control engineering , electric power system , automatic generation control , fuzzy control system , engineering , computer science , power (physics) , control (management) , temperature control , algorithm , artificial intelligence , telecommunications , biochemistry , chemistry , physics , quantum mechanics , gene
This paper proposes a robust control strategy involving a novel optimised fuzzy-PID controller tuning by particle swarm optimisation (PSO) algorithm. The proposed control strategy was suggested to design an intelligent load frequency control (LFC) scheme in multi-area interconnected power system. The PSO algorithm was employed to optimise the fuzzy-PID controller parameters including the scaling factors of fuzzy logic and the PID controller gains for minimisation of both system frequency deviation and tie-line power changes during load disturbances using the integral time multiply absolute error (ITAE) as objective function. To demonstrate the effectiveness of the proposed control strategy, the three-area 9-unit interconnected power system was used for the simulation. The superiority of the proposed approach was shown by comparing the obtained results to other strategies available in literature. Initially, the simulation was performed using the same controllers in each area, and then was extended with different controllers in each area. The comparative study demonstrates the potential of the proposed control strategy and shows its robustness to enhance frequency stability.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom