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Grey Verhulst Power Load Forecasting Method Based on Background Value Optimization
| Content Provider | Scilit |
|---|---|
| Author | Huang, Zonghong Dang, Dongsheng Gao, Chuncheng Wang, Lei |
| Copyright Year | 2019 |
| Description | Journal: Iop Conference Series: Earth and Environmental Science According to the nonlinearity and uncertainty of the load sequence, the grey Verhulst model (GV) adapted to the "S" type growth is used to predict the future electricity consumption of Ningxia. This paper analyzes the application limitations of the traditional grey Verhulst model, and introduces the background value of the vector α modified GV model, thus constructing a more universal background value modified GV model, applying the global optimization ability of adaptive particle swarm optimization algorithm (APSO) to solve the optimal α value. a grey Verhulst model (APSO-GV) based on adaptive particle swarm optimization algorithm is proposed. The case study shows that the model has high prediction accuracy and universality. |
| Related Links | https://iopscience.iop.org/article/10.1088/1755-1315/218/1/012104/pdf |
| ISSN | 17551307 |
| e-ISSN | 17551315 |
| DOI | 10.1088/1755-1315/218/1/012104 |
| Journal | Iop Conference Series: Earth and Environmental Science |
| Issue Number | 1 |
| Volume Number | 218 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2019-02-23 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Earth and Environmental Science Industrial Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Physics and Astronomy Environmental Science |
