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Optimal Reconfiguration of Distribution System for Loss Reduction, Voltage Profile Improvement and Increase Reliability using Wild Mice Colony Algorithm
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Ehsan Akbari *   |
| Department of Electrical Engineering, Mazandaran University of Science and Technology, Babol, Iran |
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Abstract: (2182 Views) |
Due to the low voltage level and as a result of high current, the distribution networks have high losses and high voltage drop, which has always been the biggest contributor to the losses and reduced reliability of the electricity distribution network. Various methods have been proposed to reduce losses, improve voltage profiles and increase reliability in these networks, one of which is redistribution. Rebuilding Distribution Networks with Switching Keys is to find the best combination of all switches in the network to minimize power losses and load balancing in situations where load distribution constraints, grid radial topology and The minimum voltage required is a very cost-effective and low cost method that reduces losses, improves voltage profiles and increases reliability in power distribution networks without adding additional equipment to the grid. Reliability calculations have used the Cut-Set method to speed up compared to the Monte Carlo method. The rearrangement of distribution networks is a large-scale nonlinear hybrid optimization problem involving a number of constraints. In this paper, a new meta-heuristic algorithm based on the behavioral pattern of wild mice is used to reconfiguration of power distribution networks to reduce losses, improve voltage profiles and increase reliability. The wild mice colony algorithm is a suitable algorithm for finding the optimal answer to complex problems. The effects of distribution system reconfiguration on two distribution networks 33 Bus and 69 Bus of IEEE standard are implemented and the results are evaluated. |
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| Keywords: Wild Mice Colony Algorithm (WMC), Reconfiguration, Voltage Profile Improvement, Loss Reduction, Reliability. |
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Full-Text [PDF 947 kb]
(1634 Downloads)
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Type of Study: Applicable |
Subject:
Special
Received: 2020/03/23 | Accepted: 2020/06/14 | Published: 2020/06/14
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