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A research on line loss calculation based on BP neural network with genetic algorithm optimization
| Content Provider | Scilit |
|---|---|
| Author | Jin, Yukun Li, Zeng Han, Yipin Li, Xiaopeng Li, Pingting Li, Guangdi Wang, Hao |
| Copyright Year | 2021 |
| Description | Journal: Iop Conference Series: Earth and Environmental Science In order to realize the calculation of the line loss of the distribution network with complex structure and low-voltage station area, this paper presents a line loss calculation method based on BP neural network with genetic algorithm optimization. The proposed method is based on the actual operation data of the distribution network. Firstly, build an error back propagation (BP) neural network model to compute the theoretical line loss of the distribution network, then use genetic algorithm (GA) to optimize the neural network and establish the GA-BP model. Based on the proposed model, the calculation demonstrates that the neural network line loss rate calculation model with genetic algorithm optimization shows better performance than the single BP neural network model, such as better nonlinear fitting ability and higher calculation accuracy. Therefore, the line loss calculation method proposed in this paper based on the BP neural network with the genetic algorithm optimization can improve the accuracy of the distribution network line loss rate calculation model. |
| Related Links | https://iopscience.iop.org/article/10.1088/1755-1315/675/1/012155/pdf |
| ISSN | 17551307 |
| e-ISSN | 17551315 |
| DOI | 10.1088/1755-1315/675/1/012155 |
| Journal | Iop Conference Series: Earth and Environmental Science |
| Issue Number | 1 |
| Volume Number | 675 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2021-02-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Earth and Environmental Science Hardware and Architecture Line Loss Bp Neural Algorithm Optimization Genetic Algorithm Distribution Network |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Physics and Astronomy Environmental Science |
