Method and system of predicting electric system load based on wavelet noise reduction and EMD-ARIMA
US11888316B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 4, 2021 |
| Grant date | Jan 30, 2024 |
| Priority date | — |
| Expiry date | Jan 3, 2042 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY04S10/50
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a system of predicting an electric system load based on wavelet noise reduction and empirical mode decomposition-autoregressive integrated moving average (EMD-ARIMA) are provided. The method and the system belong to a field of electric system load prediction. The method includes the following steps. Raw load data of an electric system is obtained first. Next, noise reduction processing is performed on the load data through wavelet analysis. The noise-reduced load data is further processed through an EMD method to obtain different load components. Finally, ARIMA models corresponding to the different load components are built. Further, the ARIMA models are optimized through an Akaike information criterion (AIC) and a Bayesian information criterion (BIC). The load components obtained through predicting the different ARIMA models are reconstructed to obtain a final prediction result, and accuracy of load prediction is therefore effectively improved.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.