Open AccessAutomatic generation control using disrupted oppositional based gravitational search algorithm optimised sliding mode controller under deregulated environment
Author(s) -
Dahiya Preeti,
Sharma Veena,
Naresh Ram
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.0175
Subject(s) - pid controller , control theory (sociology) , controller (irrigation) , turbine , automatic generation control , mode (computer interface) , computer science , sensitivity (control systems) , constant (computer programming) , genetic algorithm , power (physics) , governor , electric power system , control engineering , mathematics , engineering , temperature control , mathematical optimization , control (management) , physics , electronic engineering , artificial intelligence , biology , operating system , quantum mechanics , agronomy , aerospace engineering , programming language , mechanical engineering
A disrupted oppositional based gravitational search algorithm (DOGSA) tuned sliding mode controller (SMC) is proposed in this study for the solution of automatic generation control of interconnected multi‐area power system under deregulated environment. The novelty of the control scheme is established by performing the sensitivity analysis under different conditions such as variation of the system load, turbine time constant, governor time constant and tie‐line power coefficient. The dynamic response of the system under consideration is also studied and analysed in the presence of non‐linear constraints namely generation rate constraint with reheat steam turbine, governor deadband and time delay during signal processing. Further, in order to validate the effectiveness of the proposed DOGSA tuning over the genetic algorithm and differential evolution tuned schemes reported in the literature, it is also employed to tune the integral (I), proportional‐integral (PI), integral‐derivative (ID) and proportional integral derivative (PID) controllers. Moreover, the performance of the optimised SMC scheme is also compared with I, PI, ID and PID controllers. The comparative results reveal that SMC scheme tuned using DOGSA gives better results than the conventional controllers.