Power Identification of Distributed Generation Based on Back-Propagation Neural Network
Distributed generator (DG) is widely used and applied due to the energy and environment issues. Distributed photovoltaic generation is a typical kind of DG. Its output power is random and fluctuant, which has great influence on the safe, stable and economic operation of power system. Thus it is nece...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2021-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/32/e3sconf_posei2021_01037.pdf |
| Summary: | Distributed generator (DG) is widely used and applied due to the energy and environment issues. Distributed photovoltaic generation is a typical kind of DG. Its output power is random and fluctuant, which has great influence on the safe, stable and economic operation of power system. Thus it is necessary to identify the power generated by the distributed photovoltaic generation. This paper proposes a power identification method based on BP Neural Network. The sample data comes from simulation by PSCAD and consists of current and active power that are measured in the branch of distributed network connected with DG and active power generated by the DG. The training is based on Matlab. Simulation results verify that the BP Neural Network can identify active power of DG accurately. |
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| ISSN: | 2267-1242 |