Real power loss reduction by tundra wolf algorithm
In this work Tundra wolf algorithm (TWA) is proposed to solve the optimal reactive power problem. In the projected Tundra wolf algorithm (TWA) in order to avoid the searching agents from trapping into the local optimal the converging towards global optimal is divided based on two different condition...
| Published in: | International Journal of Informatics and Communication Technology (IJ-ICT) |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://zenodo.org/record/4243346 https://doi.org/10.11591/ijict.v9i2.pp100-104 |
| Summary: | In this work Tundra wolf algorithm (TWA) is proposed to solve the optimal reactive power problem. In the projected Tundra wolf algorithm (TWA) in order to avoid the searching agents from trapping into the local optimal the converging towards global optimal is divided based on two different conditions. In the proposed Tundra wolf algorithm (TWA) omega tundra wolf has been taken as searching agent as an alternative of indebted to pursue the first three most excellent candidates. Escalating the searching agents’ numbers will perk up the exploration capability of the Tundra wolf wolves in an extensive range. Proposed Tundra wolf algorithm (TWA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively. |
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