| Issue |
E3S Web Conf.
Volume 165, 2020
2020 2nd International Conference on Civil Architecture and Energy Science (CAES 2020)
|
|
|---|---|---|
| Article Number | 03048 | |
| Number of page(s) | 4 | |
| Section | Geology, Mapping, and Remote Sensing | |
| DOI | https://doi.org/10.1051/e3sconf/202016503048 | |
| Published online | 01 May 2020 | |
Ultra-short-term Load Forecasting Based on Real-Time Response of Classified Flexible Loads
1 North China Electric Power University, Beijing, 102206, China
2 State Power Dispatch Control Center, Beijing, 100031, China
3 State Grid Electric Power co., LTD. In Hebei Province, Hebei, 050021, China
* Corresponding author: 2210055766@qq.com
Ultra-short-term load forecasting is an important basis for optimization and adjustment of power generation plans and dispatch plans. Based on the radial basis function neural network, the inert load is predicted, and the flexible load is predicted based on the price elasticity of electricity demand. Then, combined with the range of the flexible load, an ultra-short-term forecast interval for the total load is constructed. This paper studies the total load after considering the flexible load for demand response, and verifies the feasibility of the proposed method with an example.
© The Authors, published by EDP Sciences, 2020
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