短期工业负荷预测:以意大利一家工厂为例

A. Bracale, G. Carpinelli, P. D. Falco, Tao Hong
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引用次数: 24

摘要

电力系统的卓越规划和运行在很大程度上依赖于对负荷的准确预测。虽然在过去的几十年里,负荷预测已经得到了广泛的研究,但科学界对工业负荷预测的重视程度还不够。工厂的电力需求取决于许多因素,其中一些因素在经典负荷预测模型中并不常见或不那么重要。例如,计划流程和工作班次对于预测短期工业负荷非常重要。在本文中,我们对工业负荷建模提供了一些见解。我们为意大利一家变压器生产工厂开发了一套多元线性回归模型。该模型在预测24小时工业负荷方面优于其他两种基准模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term industrial load forecasting: A case study in an Italian factory
Excellence in the planning and operations of power systems largely relies on accurate forecasts of loads. Although load forecasting has been extensively studied over the past several decades, the scientific community has not yet paid much attention to industrial load forecasting. The electricity demand of factories depends on many factors, of which some are uncommon or not as important in the classical load forecasting models. For instance, the scheduled processes and work shifts are very important to forecasting short-term industrial loads. In this paper, we offer some insights into modeling industrial loads. We develop a set of multiple linear regression models for an Italian factory that manufactures transformers. The proposed models outperform two other benchmark models for forecasting industrial loads 24 hours in advance.
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