AGC performance amelioration in multi-area interconnected thermal and thermal-hydro-gas power systems using a novel controller

• Published in: Engineering science and technology, an international journal Vol. 24; no. 2; pp. 384 - 396
• Main Authors: Arya, Yogendra, Dahiya, Pankaj, Çelik, Emre, Sharma, Gulshan, Gözde, Haluk, Nasiruddin, Ibraheem
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2021; Elsevier
• Subjects: Generation control of energy system; Interconnected electric power system; Multi-source thermal-hydro-gas power system; Optimal fractional order fuzzy controller; Reheat thermal power system; Robust control operation; Interconnected electric power system; Optimal fractional order fuzzy controller; Generation control of energy system; Reheat thermal power system; Robust control operation; Multi-source thermal-hydro-gas power system
• DOI: 10.1016/j.jestch.2020.08.015
• ISSN: 2215-0986

Due to varying structure, random load demands, nonlinearities, parameters ambiguity, steadily escalating size and intricacy of the interconnected power system (IPS), automatic generation control (AGC) is treated as one of the biggest crucial issues in IPS. Hence, expert, intelligent and robust control scheme is indispensable for stable operation of IPS and supply of electricity under sudden load demand disturbances. In vision of this, in this work, a novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS. Imperialist competitive algorithm is prolifically utilized for optimizing the controller parameters. Initially, a two area non-reheat thermal IPS is studied in detail and next to attest the efficacy of the technique, the study is extended to realistic two-area multi-source thermal-hydro-gas and reheat thermal three-area systems. The prominent benefit of cascade FPIDN-FOPIDN strategy comprises its great lethargy to large load demands and its supremacy over various latest intelligent classical/fuzzy controllers. The control strategy beats several techniques concerning significant lesser settling time, oscillations, over/under shoots and different performance index values. Finally, a robustness investigation is performed in order to validate the robustness of the controller.