Method of Load Forecasting in Microgrid Based on Differential Expansion of Small Sample Data
Abstrak
For load forecasting in renewable energy microgrid, aiming at the problem that the prediction accuracy is not high because of the lack of sample data in mid- and long-term load forecasting. This paper proposes a new data expansion method. The original data sample is used as a new data sample, and the data is filtered by setting a threshold. The data sample is expanded while ensuring the accuracy of the data, and the data based on the difference operation is analyzed. The capacity expansion method can eliminate the uncertainty of load data. Considering the influencing factors such as meteorology and population, using multiple regression analysis to fit the impact of various related factors on the load, the original data load forecasting model was used as a control, and practicality and accuracy of the expansion method in this paper was verified by comparing the error between the predicted result and the actual load.
Topik & Kata Kunci
Penulis (2)
Wei JIA
Yuchun HUANG
Akses Cepat
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Cek di sumber asli →- Tahun Terbit
- 2023
- Sumber Database
- DOAJ
- DOI
- 10.11930/j.issn.1004-9649.202209035
- Akses
- Open Access ✓