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Combined Grey Model Based on Entropy Weight Method for Long-term Load Forecasting

机译：基于熵权法的组合灰色模型在长期负荷预测中的应用

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摘要

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.
机译：长期负荷预测是电力系统运行中最重要的问题之一。灰色理论模型和灰色Verhulst模型是预测电力负荷的最常用方法。但是，这两种方法都有或多或少的局限性，并且每个模型都有不同的应用范围，例如，仅当预测数据显示出指数级的发展趋势时，GM（1,1）才能准确执行。由于实际负载受到随机因素的干扰，因此波动很大。单一模型无法可靠地应用。因此，本文提出了一种基于熵权法并结合GM（1,1）和灰色Verhulst模型的非稳定增长负荷预测模型。该模型的预测能力更加准确。

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