Title: Combined Grey Model Based on Entropy Weight Method for Long-term Load Forecasting
Abstract: The long-term load forecasting is one of the most important issues in power system operation. Grey theory model and grey Verhulst model are most commonly used methods for forecasting electrical load. However, these two methods both have more or less limitations, and each model has different application scope, for example only when forecast data show an exponential development trend, GM(1,1) performs accurately. Owing to practical load interfered by random factors, it is fluctuating. Single model cannot be reliably applied. Therefore, in this article, a new forecasting model for the unsteady growth load is proposed, which based on entropy weight method combines with GM(1,1) and grey Verhulst model. The prediction ability of the proposed model is more accurate.
Publication Year: 2020
Publication Date: 2020-06-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 4
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