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    AGC performance amelioration in multi-area interconnected thermal and thermal-hydro-gas power systems using a novel controller
    (Elsevier - Division Reed Elsevier India Pvt Ltd, 2021) Arya, Yogendra; Dahiya, Pankaj; Celik, Emre; Sharma, Gulshan; Gozde, Haluk; Nasiruddin, Ibraheem
    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. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.
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    Investigating the Effectiveness of Wind Turbine and Salp Swarm Optimization in Alleviating Transmission Congestion of Power System
    (Taylor & Francis Inc, 2024) Gautam, Anurag; Nasiruddin, Ibraheem; Sharma, Gulshan; Ahmer, Mohammad F.; Celik, Emre; Bekiroglu, Erdal
    The current power system grapples with congestion challenges arising from technological advancements and deregulation. Conversely, renewable energy sources like wind offer an inexhaustible, cost-effective, and environmentally friendly solution, potentially alleviating congestion in the modern transmission network by reducing the need for conventional generators to reschedule. This article conducts a thorough analysis of how the penetration of wind power impacts congestion costs in conventional energy systems. To address this, a novel approach utilizing the bus sensitivity factor is introduced for precise wind turbine placement. To efficiently mitigate congestion costs, a pioneering Salp Swarm Optimization Algorithm is proposed and validated on a modified IEEE 30 Bus system, demonstrating superior performance compared to other algorithms. The findings underscore the effectiveness of the proposed algorithm and highlight wind turbines, coupled with generator rescheduling, as a potent and cost-effective solution for alleviating transmission network congestion.
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    A novel congestion mitigation key of power system via generator rescheduling using Jaya algorithm
    (Taylor & Francis Inc, 2024) Gautam, Anurag; Nasiruddin, Ibraheem; Sharma, Gulshan; Krishnan, Narayanan; Ahmer, Mohd Faraz; Celik, Emre
    In the contemporary power system, congestion is a big hazard to system security. Congestion reduces the capability of the power system to work under secure limits of thermal and voltage profiles. Implementing FACTS devices or rescheduling the generator's active power output are the most prevalent ways to mitigate congestion in the current scenario and hence this paper presents generator rescheduling for congestion management under the N-1 contingency condition. The generator sensitivity factor (GSF) is used to select the generators' participation in the rescheduling process. The minimization of active power rescheduled by the selected generators is the key to success. JAYA algorithm is used first time in this work to reduce the congestion cost of the system. Furthermore, the JAYA algorithm is applied to a modified IEEE 30 bus system and the results obtained are validated by comparing them with other popular heuristic algorithms as available in the literature for diverse case studies.