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Intelligent distribution network using load information management
Mohammad Hafiz1, Aravind, C.V2, Sarimuthu, Charles R3.
Power systems operation is widely monitored through load flow analyses. The
three main methods used in these analyses are Newton-Raphson (NR), GaussSeidel
and Fast-Decoupled method. These methods involve long calculations and
numerous iteration which leads to an increase in computation time. However, fast
analyses are required for an efficient power system protection scheme. Therefore,
an alternative method which consumes much lesser time to compute and able to
provide accurate results are necessary. In this paper, the accuracy of Artificial
Neural Network (ANN) is studied by comparing numerical and analytical results
for an IEEE 14-bus power system network model. The study is done by varying
the load parameters at bus 6 and the output voltages (in per unit values) of all the
buses are recorded for ANN training and testing purposes. The ANN is coded
using the MATLAB software and the result obtained is compared with the
analytical and simulation results. Findings from this study suggest that the ANN
could possibly be an alternative method for load flow solutions.
Affiliation:
- Taylor's University, Malaysia
- Taylor's University, Malaysia
- Taylor's University, Malaysia
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Indexation |
Indexed by |
MyJurnal (2019) |
H-Index
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0 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus (SCImago Journal Rankings 2016) |
Impact Factor
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- |
Rank |
Q3 (Engineering (miscellaneous)) |
Additional Information |
0.193 (SJR) |
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