Application of Neural Networks in Power Systems; A Review
Abstract—
The electric power industry is currently undergoing
an unprecedented reform. One of the most exciting and potentially
profitable recent developments is increasing usage of artificial
intelligence techniques. The intention of this paper is to give an
overview of using neural network (NN) techniques in power
systems. According to the growth rate of NNs application in some
power system subjects, this paper introduce a brief overview in
fault diagnosis, security assessment, load forecasting, economic
dispatch and harmonic analyzing. Advantages and disadvantages
of using NNs in above mentioned subjects and the main challenges
in these fields have been explained, too.
Keywords—Neural network, power system, security
assessment, fault diagnosis, load forecasting, economic dispatch,
harmonic analyzing.
I. INTRODUCTION
EURAL networks have been used in a board range of
applications including: pattern classification, pattern
recognition, optimization, prediction and automatic control.
In spite of different structures and training paradigms, all
NN applications are special cases of vector mapping [1].
The application of NNs in different power system operation
and control strategies has lead to acceptable results [2-4].
This paper is an overview of application of NNs in power
system operation and control. The comparison of the
number of published papers in IEEE proceedings and
conference papers in this field during 1990-1996 with them
during 2000-2005 has showed that the following fields has
attracted the most attention in the past five years:
1-load forecasting
2-fault diagnosis/fault location
3-economic dispatch
4-security assessment
5-transient stability
Considering this fact, this paper has focused on the
above-mentioned subjects.

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