DE-Based Design of an Intelligent and Conventional Hybrid Control System with IPFC for AGC of Interconnected Power System

Feleke, Solomon; Pydi, Balamurali; Satish, Raavi; Anteneh, Degarege; AboRas, Kareem M.; Kotb, Hossam; Alharbi, Mohammed; Abuagreb, Mohamed

doi:10.3390/su15075625

Cited by 2 publications

(1 citation statement)

References 47 publications

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“…In this regard, some of the optimization techniques used by a few of the authors are particle swarm optimization (PSO), multi-objective particle swarm optimization (MOPSO), and distributed grey wolf optimization (DGWO) methods, which are briefly discussed in [29][30][31], respectively. The powerful optimization quality of DE in multi-area applications compared to other metaheuristic techniques, such as those with HVDC and IPFC, has also been clearly discussed in [32,33]. In this study, a genetic algorithm was chosen for comparison with DE.…”

Section: Literature Reviewmentioning

confidence: 99%

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

Feleke,

Pydi,

Satish

et al. 2023

Sustainability

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In this paper, multiple virtual synchronous machines (VISMAs) with fuzzy proportional integral derivative (FPID) controllers optimized by differential evolution (DE) are proposed to maintain frequency stability in the grid in the presence of renewable penetration, such as wind and solar photovoltaic (PV) systems, residential loads, and industrial loads, by reducing the area control error in the objective function. Simulations are conducted using MATLAB/Simulink, and in the optimization process, the integral of the time-weighted absolute error (ITAE) is used as the objective function. In the work to obtain optimized values of renewable energy sources (RESs), fuzzy membership functions, controller gain parameters, and loads for system modeling, differential evolution and genetic algorithm (GA) methods are applied and the results were compared. It was shown that better results were achieved while FPID controllers were optimized by DE in the presence of multiple VISMAs than DE in the presence of single VISMAs and GA in multiple VISMAs. Moreover, the study is compared to integral control methods in which, compared to all controllers, the proposed controller reduces undershoot by 0.0674 Hz more than a single VISMAs, in which it is improved approximately by 97.82%. Similarly, the proposed controller improves the system settling time, rise time, and overshoot by more than 99.5% compared to the classical integral controller. To examine the robust operation of the system under the proposed controller, the system was run under a wide range of disturbances and uncertainties using random load perturbation of ± 20%, in which the proposed controller retains the system frequency by reducing or damping the system oscillation.

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Section: Literature Reviewmentioning

confidence: 99%

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

Feleke,

Pydi,

Satish

et al. 2023

Sustainability

Self Cite

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A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design

Khadanga,

Das,

Panda

et al. 2024

Energy Exploration & Exploitation

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To stabilize frequency in a power system, this research study suggests a novel modified Gorilla Troops Optimizer (mGTO) technique, which builds on the original technique, and offers notable gains in effectiveness and efficiency when solving real-world optimization problems. A thorough comparative analysis reveals that the mGTO algorithm is the best option, outperforming its counterparts in terms of stability and overall performance. Interestingly, mGTO performs better than any of its competitors in terms of stability, making it the best option. The mGTO algorithm significantly reduces implementation time and enhances solution quality compared to the conventional GTO algorithm. A new linearized Phillips–Heffron model with an IPFC was developed to investigate power systems’ stability. To effectively dampen low-frequency oscillations, an auxiliary controller for modeling the IPFC is proposed. It provides four options for damping controllers, and the recommended mGTO algorithm is used to adjust the controller parameters. This method is superior to traditional controllers in stability control and has undergone extensive validation. It is a crucial instrument for controlling the frequency of an SMIB power system based on IPFC. Based on the simulation results, the updated strategy that has been suggested is the most effective way to define the mentioned damping controller by considering the percentage improvement in the goal function value.

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DE-Based Design of an Intelligent and Conventional Hybrid Control System with IPFC for AGC of Interconnected Power System

Cited by 2 publications

References 47 publications

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design

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