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Ashraf Optimization design of recon guration algorithm for high voltage power distribution network based on ant colony algorithm
| Content Provider | Semantic Scholar |
|---|---|
| Author | Li, Zhen Zhang, Yao Aqeel, Muhammad |
| Copyright Year | 2019 |
| Abstract | Distribution network recon guration is a very complex and large-scale combinatorial optimization problem. In network recon guration, whether an e ective solution can be obtained is a key issue. Aiming at the problems in network reconstruction by traditional algorithm, such as long time required, more times of power ow calculation and high network loss, a network optimization design algorithm based on improved ant colony algorithm for high voltage power distribution network is proposed. After analyzing the operating characteristics of the high voltage power distribution network, the network topology of thehighvoltagepowerdistributionnetwork is described by constructing a hierarchical variable-structure distribution network model. A mathematical model of distribution network reconstruction considering the opportunity constraint with the minimum network loss as the objective function is established. The power ow distribution is calculated by using the pre-push back-generation method combined with the hierarchical structure of the distribution network. The maximum and minimum ant colony algorithm is introduced to improve the pheromone updating method of the traditional ant colony algorithm, and the search range is expanded, so that the algorithm can jump out of the local optimization trap to realize the accurate solution of the power distribution network reconstruction model. The experimental results show that compared with the current network reconstruction algorithm, the proposed algorithm requires less time for convergence, less power ow calculation, and lower network loss. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.degruyter.com/downloadpdf/j/phys.2018.16.issue-1/phys-2018-0130/phys-2018-0130.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
