International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
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Fuzzy Logic Controller for Modern Power Systems 1Samudyata S J, 2Sharanya S, 3Shrusti Heroor, 4Sneha
Majumder, 5Sangeeta Modi
Dept. of Electrical and Electronics Engineering, PES University, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------Synchronous Generators play a very important role in the Abstract - The main objective of this work is to design a
stability of power systems. Electric power system stability requirement is increasing along with the growth of load. Thus, a robust reliable AVR system is needed to enhance the voltage stability. Here, the AVR system used is Fuzzy logic control system.
fuzzy logic controller for the modern power system. In this paper we deal with 2 different simulations that could be designed to study the fuzzy logic controller design a). to simulate the control of automatic voltage regulator for a single synchronous generator during different load conditions and b).to develop a linearized Heffron-Philips model of a Single Machine Infinite Bus (SMIB) power system with a Fuzzy Logic Power System Stabilizer (FPSS) for different membership functions[2]. In AVR modelling the work has been achieved on a main generator, which is mechanically coupled with a small synchronous generator as an exciting system for the main generator. The result for the fuzzy logic controller has been compared with a MATLAB demo system using NO controller with the same load conditions. The proposed fuzzy controller enhanced the performance of the generator in terms of response and performance. Where as in FPSS, speed deviation and acceleration deviation are taken as inputs. Further this paper investigates the design and implementation of a Reduced Rule Fuzzy Logic Power System Stabilizer (RLFPSS). A Reduced Rule Fuzzy Logic Power System Stabilizer for different membership functions is proposed. The effectiveness of the RLFPSS for different membership functions is illustrated with simulation carried out in MATLAB
1.1 Fuzzy Logic Control System Fuzzy control is an appealing alternative to conventional control methods when systems follow some general operating characteristics and a detailed process understanding is unknown or traditional system models become overly complex [7-8]. Fuzzy logic control is a rangeto-point or range-to-range control. The output of a fuzzy controller is derived from fuzzifications of both inputs and outputs using the associated membership functions.[2] A crisp input will be converted to the different members of the associated membership functions based on its value. From this point of view, the output of a fuzzy logic controller (FLC) is based on its memberships of the different membership functions, which can be considered as a range of inputs.[10].A fuzzy controller comprises of three stages: fuzzification, fuzzy rule and defuzzification as shown in Fig 1. 1.2 Fuzzification
Key Words: AVR, Fuzzy logic controller (FLC), Fuzzy sets and membership functions, Heffron-Philips Single Machine Infinite Bus model.
A fuzzy set is an expansion of standard sets and can be comprehended as a membership degree of a set [6]. For example, a classic set can be written as { 1, 2, 3, 4 } whereas a ,Fuzzy Set can be written as { (1,0.4), (2,0.7), (3,0.1), (4,0.2)} wherein every pair (X,Y), X represents the value of the element whereas Y represents the degree of membership of the element in the set.
1. INTRODUCTION The two types of power system stability are steady state and transient stability. Here we will be dealing with transient stability, i.e., ability of the power system to return to its normal conditions after a large disturbance[2][7]. The large disturbance occurs in the system due to the sudden removal of the load, line switching operations; fault occurs in the system, sudden outage of a line, etc.
Fuzzification is the process of converting a crisp input value to a fuzzy value that is performed by the use of the information in the knowledge base [4]. This is done by the help of fuzzifiers (membership functions).
The transient stability of a system was conventionally suppressed using AVR (Automatic voltage regulator), but the electric system has been seen with oscillations of frequencies ranging from 0.1 to 2 Hz. These regulators have high gain leading to destabilizing effect on power system. Thus, we use Fuzzy logic controller. Fuzzy Logic has the features of simple concept, easy implementation, and computational efficiency. This provides an easy method to draw the definite conclusion from hazy, uncertain or inexact information.
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