Back to Search
Start Over
Three-Phase Feeder Load Balancing Based Optimized Neural Network Using Smart Meters
- Source :
- Symmetry, Vol 13, Iss 2195, p 2195 (2021), Symmetry, Volume 13, Issue 11
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The electricity distribution system is the coupling point between the utility and the end-user. Typically, these systems have unbalanced feeders due to the variety of customers’ behaviors. Some significant problems occur<br />the unbalanced loads increase the operational cost and system investment. In radial distribution systems, swapping loads between the three phases is the most effective method for phase balancing. It is performed manually and subjected to load flow equations, capacity, and voltage constraints. Recently, due to smart grids and automated networks, dynamic phase balancing received more attention, thus swapping the loads between the three phases automatically when unbalance exceeds permissible limits by using a remote-controlled phase switch selector/controller. Automatic feeder reconfiguration and phase balancing eliminates the service interruption, enhances energy restoration, and minimize losses. In this paper, a case study from the Irbid district electricity company (IDECO) is presented. Optimal reconfiguration of phase balancing using three techniques: feed-forward back-propagation neural network (FFBPNN), radial basis function neural network (RBFNN), and a hybrid are proposed to control the switching sequence for each connected load. The comparison shows that the hybrid technique yields the best performance. This work is simulated using MATLAB and C programming language.
- Subjects :
- Electric power distribution
Physics and Astronomy (miscellaneous)
Artificial neural network
Computer science
business.industry
General Mathematics
load balancing
Load balancing (electrical power)
Control reconfiguration
artificial intelligence
Smart grid
Three-phase
Chemistry (miscellaneous)
Control theory
Computer Science (miscellaneous)
QA1-939
feed-forward back-propagation
business
MATLAB
computer
radial basis function
Mathematics
computer.programming_language
Subjects
Details
- Language :
- English
- ISSN :
- 20738994
- Volume :
- 13
- Issue :
- 2195
- Database :
- OpenAIRE
- Journal :
- Symmetry
- Accession number :
- edsair.doi.dedup.....d9160329ef4dabc5faae566a86636f9b