Optimal radial topology of electric unbalanced and balanced distribution system using improved coyote optimization algorithm for power loss reduction
This paper presents an improved coyote optimization algorithm (ICOA) for the electric distribution network reconfiguration (EDNR) problem considering unbalanced load. ICOA is first developed by carrying out two improvements on two new solution generation mechanisms of original coyote optimization al...
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| Tác giả chính: | , , |
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| Định dạng: | journal-article |
| Ngôn ngữ: | en_US |
| Thông tin xuất bản: |
2022
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| Chủ đề: | |
| Truy cập trực tuyến: | http://repository.vlu.edu.vn:443/handle/123456789/573 |
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| Tóm tắt: | This paper presents an improved coyote optimization algorithm (ICOA) for the electric distribution network reconfiguration
(EDNR) problem considering unbalanced load. ICOA is first developed by carrying out two improvements on two
new solution generation mechanisms of original coyote optimization algorithm (COA). In the first mechanism, ICOA has
used the so-far best solution instead of the tendency solution like COA. In the second mechanism, a local search
mechanism has been proposed to update the so-far best solution. ICOA determines opened switches in aim to minimize
total power losses. In addition, a modified power flow (MPF) method based on the technique of backward/forward sweeps
is proposed to solve power flow for unbalanced distribution system. The proposed MPF method has been highly accurate in
comparison with the Power System Simulator/Advanced Distribution Engineering Productivity Tool software (PSS/
ADEPT). The ICOA together with COA, particle swarm optimization (PSO) and sunflower optimization (SFO) have been
implemented on three systems including 25-node, 33-node and 69-node for comparison. As a result, ICOA has outperformed
COA, PSO, SFO and other existing methods for the EDNR problem. Consequently, the combination of the
proposed MPF method and ICOA for solving EDNR problem with unbalanced load can lead to high effectiveness |
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