Multi-objective distribution feeder reconfiguration along with optimal sizing of capacitors and distributed generators regarding network voltage security
Distribution network reconfiguration is one of the well-known and effective strategies in the distribution networks which performs by the status management of the network switches in order to obtain a new optimal configuration for the feeders. This study formulates multi-objective distribution feede...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Taylor and Francis Ltd.
2022
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| Subjects: | |
| Online Access: | http://eprints.utm.my/103537/ http://dx.doi.org/10.1080/15325008.2021.2011486 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Distribution network reconfiguration is one of the well-known and effective strategies in the distribution networks which performs by the status management of the network switches in order to obtain a new optimal configuration for the feeders. This study formulates multi-objective distribution feeder reconfiguration along with optimal sizing of distributed generators and capacitors. The prevalent objective functions in the network reconfiguration studies comprise of power loss and voltage deviations that are considered as the main objectives for traditional distribution systems, however, less attention has been paid to the objective functions of reliability and network voltage security in the previous literatures. Therefore, the main objective of this study is to improve the reliability and network voltage security by solving the distribution network reconfiguration problem. To this end, the energy not supplied and voltage stability index are defined as the objective functions of reliability and voltage security. A modified gravitational search algorithm is suggested to solve the complex and non-convex optimization problem. Ultimately, to demonstrate the efficiency of the proposed method, it has been tested on two 33 and 70-bus test systems, and the results are compared with the results of using other evolutionary algorithms, such as particle swarm optimization and shuffled frog leaping. |
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