Investigation of Hybrid Particle Swarm Optimization Methods for Solving Transient-Stability Constrained Optimal Power Flow Problems

نویسندگان

  • Kit Yan Chan
  • G. T. Y. Pong
  • K. W. Chan
چکیده

In this paper, hybrid particle swarm optimization (PSO) is proposed for solving the challenging multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problem. The objective of this nonlinear optimization problem is to minimize the total fuel cost of the system and at the same time fulfil the transient stability requirements. The optimal power flow (OPF) with transient stability constraints considered is re-formulated as an extended OPF with additional rotor angle inequality constraints, which is suitable for hybrid PSO to solve. Comparison between various existing hybrid PSO techniques is carried out by solving the New England 39-bus system. Experimental results indicate that the hybrid PSO integrated with the mutation operation of genetic algorithms is better than the other existing hybrid PSO methods in both solution quality and stability.

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

Solving Transient-stability Constrained Optimal Power Flow Problems

The paper extends our pervious work on solving multi-contingency transient stability constrained optimal power flow problems (MC-TSCOPF) with the approach of particles swarm optimization (PSO). A hybrid PSO method that incorporates with a new wavelet theory based mutation operation, intends to improve the searching strategies on previously used PSO methods, is proposed to solve MC-TSCOPF proble...

متن کامل

A Modified Particle Swarm Optimization Technique for Solving Transient Stability Constrained Optimal Power Flow

This paper presents an improved Particle Swarm Optimization (PSO) algorithm for solving Transient Stability Constrained Optimal Power Flow (TSCOPF) problem through the application of Gaussian and Cauchy probability distributions. The modified PSO approach introduces new diversification and intensification strategy into the particles thus preventing PSO algorithm from premature convergence. The ...

متن کامل

Solving Multi-objective Optimal Power Flow Using Modified GA and PSO Based on Hybrid Algorithm

The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage ...

متن کامل

Optimal Placement and Sizing of DGs and Shunt Capacitor Banks Simultaneously in Distribution Networks using Particle Swarm Optimization Algorithm Based on Adaptive Learning Strategy

Abstract: Optimization of DG and capacitors is a nonlinear objective optimization problem with equal and unequal constraints, and the efficiency of meta-heuristic methods for solving optimization problems has been proven to any degree of complex it. As the population grows and then electricity consumption increases, the need for generation increases, which further reduces voltage, increases los...

متن کامل

Transient Stability Constrained Optimal Power Flow Using Improved Particle Swarm Optimization Approach

Stability is an important constraint in power system operation; the transient stability constrained optimal power flow (TSCOPF) has a considerable attention in recent years. The solution obtained from the conventional optimal power flow (OPF), which considers only the static constraints, does not guarantee transient stability in the system against possible contingencies such as line fault. In t...

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 2007