| Issue |
E3S Web Conf.
Volume 124, 2019
International Scientific and Technical Conference Smart Energy Systems 2019 (SES-2019)
|
|
|---|---|---|
| Article Number | 05026 | |
| Number of page(s) | 4 | |
| Section | Additional papers | |
| DOI | https://doi.org/10.1051/e3sconf/201912405026 | |
| Published online | 10 February 2020 | |
Prediction of the electrical load of the power system using neural networks
Krasnoselskaya st., 51, Kazan, Rep. Tatarstan, 420034, Russia
* Corresponding author: dinar91121@mail.ru
Prediction of the electrical load schedule of an electrical system is an important aspect for determining electrical loads, which ensures the correct selection and cost-effective operation of reactive power compensation devices and voltage control devices, as well as relay protection and automation. This article discusses methods for predicting electrical load using an artificial neural network. The problems of choosing the optimal architecture and algorithm of neural network training are considered. The methods of the best forecast accuracy are determined. A genetic algorithm based on the group method of data handling was chosen as the main calculation.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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