Fopid Design for Load-frequency Control Using Genetic Algorithm

نویسندگان

  • Navid Bayati
  • Akbar Dadkhah
  • Behrooz Vahidi
  • Seyed Hossein Hesamedin Sadeghi
چکیده

1-Department of Electrical Engineering, Amirkabir University of Technology, Tehran 1591634311, Iran * Corresponding author email: [email protected] ABSTRACT: A fractional order PID (FOPID) for a load frequency control (LFC) is presented in a three-area power system. FOPID controllers are designed the same way as PID controllers are, with the difference that FOPID controllers have five parameters in the controller that should be determined. That is why they have two more degrees of freedom for better tuning the dynamical characteristics of the controller compared to PID controllers. Once the FOPID is designed using Genetic Algorithm (GA), a comparison is made between this approach and FOPID controllers that are designed with other optimization methods such as Imperialist Competitive Algorithm (ICA). Then, the results of the frequency change and transferred power change of each area by FOPID are compared in comparison the PID controller designed using GA. The results indicate that FOPID controllers tail better characteristics compared to the PID controllers. It is also revealed that FOPID controllers designed using GA have better characteristics compared to those designed using other optimization methods such as ICA.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fractional-order load-frequency control of interconnected power systems using chaotic multi-objective optimization

Fractional-order proportional-integral-derivative (FOPID) controllers are designed for load-frequency control (LFC) of two interconnected power systems. Conflicting time-domain design objectives are considered in a multi-objective optimization (MOO)-based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore th...

متن کامل

Load Frequency Control in Power Systems Using Multi Objective Genetic Algorithm & Fuzzy Sliding Mode Control

This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

متن کامل

Design of Fractional Order PID Controller for DC Motor using Genetic Algorithm

Design of fractional order PID (FOPID) controller for DC motor is proposed in this paper. A FOPID (PID) is a PID controller whose derivative and integral orders are fractional numbers rather than integers. Design stage of such controller consists of determining six parameters – proportional constant (Kp), integral constant (Ki), derivative constant (Kd), filter time constant (τd), integral orde...

متن کامل

Determination of Stabilizing Parameter of Fractional Order PID Controller Using Genetic Algorithm

This paper present the development of new tuning method and performance for Genetic Algorithm based Fractional order PID controller ,fractional order PID controller include the conventional order PID controller parameter. The tuning of the PID controller is mostly done using Zeigler and Nichols tuning method. All the parameters of the controller, namely p K (Proportional gain), i K (integral ga...

متن کامل

Load Frequency Control in Power Systems Using Improved Particle Swarm Optimization Algorithm

The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has a longer settling time and a lot of Extramutation in output response of system so it required that the parameters be adjusted ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015