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Forecasting of electricity demand to reduce the inventory cost of imported coal

机译:电力需求预测降低进口煤炭库存成本

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The purpose of this paper is to apply forecasting methods to forecast the electricity demand in Thailand. Demand forecasts will be used to estimate the imported coal order quantity in order to decrease the inventory cost of the imported coal. The monthly electricity demand data from January 2010 to December 2014 are used to forecast the monthly electricity demand from January 2015 to December 2015. The forecasting models are additive and multiplicative decomposition models and additive and multiplicative Holt-Winters models. The forecasting accuracies are measured by mean absolute percentage error and compared by randomized complete block design. The results of the study show that all forecasting accuracies are not significantly different so the multiplicative decomposition model is chosen because of its simplicity. The proposed imported coal order quantity is equal to 5.95 percent of the electricity demand forecasts. The inventory cost in 2015 decreased by 3,721.82 million baht or 14.84 percent compared to the inventory cost under the current order quantity.
机译:本文的目的是应用预测方法预测泰国的电力需求。需求预测将用于估计进口煤炭秩序数量,以降低进口煤炭的库存成本。 2010年1月至2014年12月的每月电费数据用于预测2015年1月至2015年12月的每月电费。预测模型是附加和乘法分解模型和添加剂和乘法孔冬季模型。预测精度是通过平均绝对百分比误差测量的,并通过随机完成块设计进行比较。研究结果表明,所有预测精度都没有显着差异,因此选择了乘法分解模型,因为其简单性。拟议的进口煤炭订单数量等于电力需求预测的5.95%。与当前订单数量下的库存成本相比,2015年的库存成本下降了3,721.82百万泰铢或14.84%。

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