ON-LINE VOLTAGE STABILITY EVALUATION USING NEURO-FUZZY INFERENCE SYSTEM AND MOTH-FLAME OPTIMIZATION ALGORITHM

Purpose. In recent years, the problem of voltage instability has received special attention from many utilities and researchers. The present paper deals with the on-line evaluation of voltage stability in power system using Adaptive Neuro-Fuzzy Inference System (ANFIS). The developed ANFIS model tak...

Full description

Saved in:
Bibliographic Details
Published in:Electronics and electromechanics 2019-01 (2), p.47-54
Main Authors: Bourzami, Arif, Amroune, Mohammed, Bouktir, Tarek
Format: Article
Language:English
Subjects:
adaptive neuro-fuzzy inference system
Adaptive systems
Algorithms
Analysis
Applied research
Artificial neural networks
Basis functions
Buses (Transportation)
Data buses
Electric power systems
Fuzzy logic
Fuzzy systems
Inference
Line voltage
line voltage stability index
Moth-Flame optimization
Multilayer perceptrons
Multilayers
Neural networks
On-line systems
Operating costs
Optimization
Optimization algorithms
Optimization theory
Power loss
Radial basis function
Stability
Stability (Physics)
Stability analysis
Testing equipment
Utilities
Voltage stability
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Purpose. In recent years, the problem of voltage instability has received special attention from many utilities and researchers. The present paper deals with the on-line evaluation of voltage stability in power system using Adaptive Neuro-Fuzzy Inference System (ANFIS). The developed ANFIS model takes the voltage magnitudes and their phases obtained from the weak buses in the system as input variables. The weak buses identification is formulated as an optimization problem considering the operating cost, the real power losses and the voltage stability index. The recently developed Moth-Flame Optimization (MFO) algorithm was adapted to solve this optimization problem. The validation of the proposed on-line voltage stability assessment approach was carried out on IEEE 30-bus and IEEE 118-bus test systems. The obtained results show that the proposed approach can achieve a higher accuracy compared to the Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks.
ISSN:2074-272X
2309-3404
DOI:10.20998/2074-272X.2019.2.07