电力负荷预测方法综述

H. Temraz, M. Salama, A. Chikhani
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引用次数: 16

摘要

根据负荷数据模式的类型,现有的负荷预测技术可分为三类:(1)平稳型;(2)不稳定;(3)非平稳、季节性和周期性技术。该准则分为三个阶段:(1)识别;(2)评估;(3)诊断检查。识别阶段的目的是确定似乎更有希望充分描述给定数据集的技术。本文提出了一种选择和构建最合适的电力负荷预测模型的算法过程。从这一综述中可以清楚地看出,模型的选择和构建标准对于一个合适的预测模型是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of electric load forecasting methods
The different available load forecasting techniques can be classified according to the type of load data pattern, into three classes: (1) stationary; (2) nonstationary; and (3) nonstationary, seasonal and cyclical techniques. The criterion is divided into three stages: (1) identification; (2) estimation; and (3) diagnostic checking. The purpose of the identification stage is to ascertain the techniques(s) that appear to hold more promise for adequately describing a given data set. The paper presents an algorithmic procedure for selecting and constructing the most appropriate electric load forecasting model. From this review, it is clear that models for the selection and construction criteria are essential for a proper forecasting model.
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