8/12/2019 Final Word Load Flow Analysis Using Neural Networks%5B1%5D(1)

1/39

Abstract

Power flow (PF) study, which is performed to determine the power

system static states (voltage magnitudes and voltage angles) at each bus

to find the steady state operating condition of a system, is very important

and is the most frequently carried out study by power utilities for power

system planning, operation and control. In this project, a ewton

raphson method is proposed to solve power flow problem under differentloading!contingency conditions for computing bus voltage magnitudes

and angles of the power system. "he composition of the input variables

for the proposed neural networ# has been selected to emulate the

solution process of a conventional power flow program. "he

effectiveness of the proposed $ based approach for solving power flow

is demonstrated by computation of bus voltage magnitudes and voltage

angles for different loading conditions and single line%outage

contingencies in I&&& ' %bus system.

'

8/12/2019 Final Word Load Flow Analysis Using Neural Networks%5B1%5D(1)

2/39

CONTENTS

Page o.

CHAPTER1: INTRODUCTION

'.' oad flow analysis *

CHAPTER-2: LOAD FLOW STUDIES

+.' Introduction to load flow studies

+.+ -lassification of buses

+./ Formulation of the oad Flow Problem

''

CHAPTER-3: NEWTON RAPHSON METHOD

/.'. 0eneral 1pproach '2

/.+. 1pplication of the ewton%$aphson 3ethod to the 4pecific Problem

'

/./. 4ample $esults for the ewton%$aphson 3ethod 21

/. oad Flow 1lgorithm ++

+

8/12/2019 Final Word Load Flow Analysis Using Neural Networks%5B1%5D(1)

3/39

/. .' Formation of the 5acobian 3atri6 ++

/+

CHAPTER-6 7 INTRODUCTION TO MATLAB

*.'7 Introduction *

*.+7 3%files 8

*./ $unning 31" 19 8

CHAPTER- : INTRODUCTION TO SIMULIN!

8.'7 Introduction

8.+7 :ey Features

8./7 -reating and ;or#ing with 3odels

CHAPTER-" 7SUMMAR# OF RESULTS AND S#STEM CALCULATIONS

20enetic algorithms7 concepts and applications?, I&&&

"ransactions on Industrial &lectronics, / (' *), 2, pp. 2' % 2//.

+ Q 3. 0en, and $. -heng, >0enetic algorithms and engineering design?, (5ohn ;iley N 4ons,

Inc., ' 8).

+2Q 5.]. ]u, -.4. -hang, and ].;. ;ang, >-onstrained multiobjective global optimiBation of

longitudinal interconnected power system by genetic algorithm?, I&& Proceedings, 0eneration,

"ransmission N Wistribution, ' / (' *), 2, pp /2% *.

+*Q ]in Gao, ?1 new simulated annealing algorithm?, International 5ournal of -omputer

3athematics, 2* (' 2), pp '*'%'* .

/

8/12/2019 Final Word Load Flow Analysis Using Neural Networks%5B1%5D(1)

39/39