Title: Optimal AGC scheme design using hybrid particle swarm optimisation and gravitational search algorithm

Authors: Nour El Yakine Kouba; Mohamed Menaa; Mourad Hasni; Mohamed Boudour

Addresses: Laboratory of Electrical and Industrial Systems (LSEI), University of Sciences and Technology Houari Boumediene, USTHB, BP 32 El Alia, 16111, Bab Ezzouar, Algiers, Algeria ' Laboratory of Electrical and Industrial Systems (LSEI), University of Sciences and Technology Houari Boumediene, USTHB, BP 32 El Alia, 16111, Bab Ezzouar, Algiers, Algeria ' Laboratory of Electrical and Industrial Systems (LSEI), University of Sciences and Technology Houari Boumediene, USTHB, BP 32 El Alia, 16111, Bab Ezzouar, Algiers, Algeria ' Laboratory of Electrical and Industrial Systems (LSEI), University of Sciences and Technology Houari Boumediene, USTHB, BP 32 El Alia, 16111, Bab Ezzouar, Algiers, Algeria

Abstract: In this paper, a novel hybrid particle swarm optimisation and gravitational search algorithm (HPSO-GSA) is proposed to design an optimal automatic generation control (AGC) scheme in interconnected power system. The proposed algorithm combines the advantages of both particle swarm optimisation (PSO) and gravitational search algorithm (GSA). This new meta-heuristic HPSO-GSA is applied to achieve the optimal proportional-integral-derivative (PID) controller parameters. Hence, the optimal PID controller is used to reduce the system fluctuations with the best dynamic performances. The AGC issue is formulated as an optimal load frequency control problem, where the frequency fluctuations and the tie-line power flow deviations are to be minimised in the same time. In order to test the performance of the proposed HPSO-GSA strategy, the integral time multiplied by absolute error (ITAE) is used as an objective function. To evaluate the efficiency of the proposed approach over disturbances, the standard two-area power system is used for the simulation. The obtained simulation results are compared to those yielded using classical and heuristic optimisation techniques surfaced in the recent state-of-the-art literature. The comparative study demonstrates the potential of the proposed strategy and shows its robustness to solve the optimal AGC problem.

Keywords: automatic generation control; AGC; load frequency control; LFC; optimal control; particle swarm optimisation; PSO; gravitational search algorithm; GSA; hybrid PSO-GSA.

DOI: 10.1504/IJPEC.2019.098622

International Journal of Power and Energy Conversion, 2019 Vol.10 No.2, pp.241 - 263

Received: 18 Oct 2016
Accepted: 05 Apr 2017
Published online: 29 Mar 2019 *

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