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Classification of electricity load forecasting based on the factors influencing the load consumption and methods used: An-overview

机译:基于影响负荷消耗的因素和所用方法的电力负荷预测分类:概述

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Electrical energy consumption is affected by many parameters. These includes the variables related to power system itself, weather and climatic factors and socio-economic being of the energy consumers. In this paper, two components of load forecasting are classified. The parameters that influence the energy consumption and the methods used to forecast the energy consumption are reviewed. It is observed that, many factors have great influence on the energy consumption, and the forecasting accuracy depends on the amount of data used. Also the methods applied contribute in the forecasting accuracy and complexity of the method. It is therefore important to use large data, and apply an appropriate method (technique) while forecasting electrical energy. A lot of methods are reviewed, from time series method to artificial intelligence with varying parameters, most of which are weather related, demography of the area, economy class of the consumers and the history of electrical energy consumed.
机译:电能消耗受许多参数影响。这些变量包括与电力系统本身,天气和气候因素以及能源消耗者的社会经济状况有关的变量。在本文中,负荷预测分为两个组成部分。回顾了影响能耗的参数和预测能耗的方法。可以看到,许多因素对能耗都有很大的影响,并且预测的准确性取决于所使用的数据量。所应用的方法也有助于该方法的预测准确性和复杂性。因此,重要的是使用大数据,并在预测电能时应用适当的方法(技术)。审查了许多方法,从时间序列方法到具有不同参数的人工智能,其中大多数与天气有关,与地区有关的人口统计学,消费者的经济舱以及所消耗电能的历史。

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