Abstract
The rapid development in smart grids needs efficient state estimation methods. This paper presents a novel method for smart grid state estimation (e.g., voltages, active and reactive power loss) using artificial neural networks (ANNs). The proposed method which is called SE-NN (state estimation using neural network) can evaluate the state at any point of smart grid systems considering fluctuated loads. To demonstrate the effectiveness of the proposed method, it has been applied on IEEE 33-bus distribution system with different data resolutions. The accuracy of the proposed method is validated by comparing the results with an exact power flow method. The proposed SE-NN method is a very fast tool to estimate voltages and re/active power loss with a high accuracy compared to the traditional methods.
Original language | English |
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Pages (from-to) | 92-100 |
Number of pages | 9 |
Journal | INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE |
Volume | 5 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jun 2018 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Neural Network
- Smart Grid
- Renewable Energy
- Power Loss
- Voltage Profile
- POWER-FLOW
- PENETRATION
- PV