Fuzzy based load frequency control of power system incorporating nonlinearity

Yadav, Sneha; Namrata, Kumari; Kumar, Nishant; Samadhiya, Akshit

doi:10.1109/icepe55035.2022.9798219

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…All birds have a worthy value that is evaluated by the merit function that needs to be optimized [19]. In addition, each i ، bird has a position in the next D dimensional space of the problem, which, in t th repeating, is represented by a vector as (1).…”

Section: B Particle Swarm Optimization (Pso) Algorithmmentioning

confidence: 99%

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Design of Multivariate PID Controller for Power Networks Using GEA and PSO

Zadehbagheri

Ma’arif

Ildarabadi

et al. 2023

Journal of Robotics and Control

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The issue of proper modeling and control for industrial systems is one of the challenging issues in the industry. In addition, in recent years, PID controller design for linear systems has been widely considered. The topic discussed in some of the articles is mostly speed control in the field of electric machines, where various algorithms have been used to optimize the considered controller, and always one of the most important challenges in this field is designing a controller with a high degree of freedom. In these researches, the focus is more on searching for an algorithm with more optimal results than others in order to estimate the parameters in a more appropriate way. There are many techniques for designing a PID controller. Among these methods, meta-innovative methods have been widely studied. In addition, the effectiveness of these methods in controlling systems has been proven. In this paper, a new method for grid control is discussed. In this method, the PID controller is used to control the power systems, which can be controlled more effectively, so that this controller has four parameters, and to determine these parameters, the optimization method and evolutionary algorithms of genetics (EGA) and PSO are used. One of the most important advantages of these algorithms is their high speed and accuracy. In this article, these algorithms have been tested on a single-machine system, so that the single-machine system model is presented first, then the PID controller components will be examined. In the following, according to the transformation function matrix and the relative gain matrix, suitable inputs for each of the outputs are determined. At the end, an algorithm for designing PID controller for multivariable MIMO systems is presented. To show the effectiveness of the proposed controller, a simulation was performed in the MATLAB environment and the results of the simulations show the effectiveness of the proposed controller.

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Section: B Particle Swarm Optimization (Pso) Algorithmmentioning

confidence: 99%

“…Resistant PID controller for controlling the frequency of power systems is investigated using the algorithm (ICA) in Swarm Optimization [1]. In this paper, the controller is designed in order to overcome the load disturbance problem based on filtering method, that eliminates the effect of this kind of turbulences.…”

Section: Introductionmentioning

confidence: 99%

Design of Multivariate PID Controller for Power Networks Using GEA and PSO

Zadehbagheri

Ma’arif

Ildarabadi

et al. 2023

Journal of Robotics and Control

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“…The gain of the PID controller is scheduled with the help of ABC optimization technique. The fuzzy has two inputs ACE and derivative of ACE and output is given to the governor (24) . Seven membership function for each input is taken and seven MF for the output of FLC.…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

Application of Intelligent controller For Load Frequency Control for Multi-Area Multi-Source Power System

Nath,

Sambariya

2023

IJST

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Objectives: This paper demonstrates the application of an artificial intelligence (AI) based controller for load frequency control for a two-area multi-source interconnected power system. Fuzzy PID controller parameters area Tuned using Artificial BEE colony (ABC) algorithm. The FLC-PID performance is simulated and verified using MATLAB. Method: For evaluating LFC Problem two different systems are considered. The first system consists of four units of the non-reheat thermal power system. The analysis is further extended by adding a hydropower plant unit with a non-reheat thermal unit. A perturbation of 0.01 P.U in step load form is considered for each area for the automatic generation control (AGC) study. Finding: The suggested controller Fuzzy-PID robustness is observed by varying operating loading conditions and plant parameters for a wide range. The variation in time constant (seconds) of system parameters is carried out in a range of +75% to -75%. The objective is to improve the steady-state error of the tie-line power deviation and frequency variation of an interlinked power plant. By the suggested approach, the variation in frequency and tie-line power is minimized to a great extent. Novelty: Artificial BEE colony (ABC) algorithm is effective. The performance of the adapted controller is compared with the previously published tuned PID controller based on Settling Time (ST) and ITAE Error. The proposed controller shows superiority. It is observed that the proposed technique can handle abrupt amplification of load (PU) and variation in system parameters like the governor, and turbine time constant. Eigenvalue analysis is also carried out. The result of the Fuzzy-PID controller is also compared with the proposed-FOPID and Proposed-ANFIS controller. The parameter of fractional order is also optimized by the ABC algorithm. For simulation, MATLAB 2016 @ Version is taken.

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