采用切线逼近方法求解IEEE14节点电力系统多目标的无功优化问题，目标为发电机无功总出力和网损。

“Optimal Reactive Power Dispatch (ORPD) Using Particle Swarm

Optimization (PSO)”

By

Kartik S. Pandya

Associate Professor

Dept of Electrical Engineering,

CSPIT,

Charotar University of Science and Technoloogy-Changa,

Important note:

I have solved the optimal reactive power dispatch problem using Particle Swarm Optimization

algorithm for IEEE 30 bus test system. I have used MATPOWER[1] software, version 3.2 for

executing load flow analysis for each particle. As MATPOWER is a system requirement, users

are kindly requested to download it from its website first (www.pserc.cornell.edu/matpower) and

then in the folder of MATPOWER, please include ORPD_30bus.m file. Users are requested to

define some variables as global in some files of MATPOWER as given in table 1.

Table 1: Variables to be defined as global in MATPOWER files

Sr no. File name.m Variables to be defined as global

the input data.

Introduction:

Optimal reactive power dispatch is a complex optimization problem in which we try to

“optimally” set the values of control variables like reactive power output of generators

(generator bus voltages), tap ratios of transformers and reactive power output of shunt

compensators like capacitors etc. to minimize the total transmission active power losses

while satisfying a given set of constraints [2]. I have used basic Particle Swarm

Optimization (PSO) for minimizing the following objective function (1).

All equations are taken from ref. [2].

s.t.

Static square penalty function is used to handle inequality constrains. So the Augmented

objective function (fitness function) would be as equ(2)

Particle Swarm Optimization

PSO is a fast, simple and efficient population-based optimization method which was

proposed by Eberhart and Kennedy [3]. Each particle updates its position based upon its

own best position, global best position among particles and its previous velocity vector

according to the following equations:

where,

: Global best position of the particle in the population

: The position of particle at