气候和非气候参数对尼日尔月用电量的影响

A. Bonkaney
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引用次数: 2

摘要

本研究利用简单多元线性回归(MLRs)研究了尼日尔四个主要城市的相关因素(气候和非气候)对月用电量(MEC)的影响。使用的参数包括GDP/人均、气温(平均值)、相对湿度(RH)、风速(WSP)、太阳辐射(SR)、降水量和清晰度指数(K)。此外,还计算了热指数(HI)和不适指数(DI)两个热指数,以考虑高湿和高环境温度的影响。因此,从上述变量推导出三种不同的模型。这三个模型已经用交叉验证进行了测试。结果表明,对于尼亚美、马拉迪、津德尔和阿加德兹,采用人均GDP、平均值、相对湿度、SR和WSP等原始变量所建立的模型,其决定系数分别为0.87、0.854、0.833和0.551,优于其他两种模型。根据所考虑的月份,平均绝对百分比误差对于气候变量的特定组合可能会产生很小的误差。降水量和净度指数等变量均无统计学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Influence of Climate and Nonclimate Parameters on Monthly Electricity Consumption in Niger
This study examines the impacts of relevant factors (climatic and nonclimatic) on the monthly electricity consumption (MEC) in four major cities in Niger using simple multiple linear regressions (MLRs). Parameters such GDP/capita, air temperature ( mean), relative humidity (RH), wind speed (WSP), solar radiation (SR), precipitation, and clearness index (K) are used. In addition, two heat indices, heat index (HI) and discomfort index (DI) are calculated to take into account the impacts of high humidity in conjunction with high ambient temperature. Hence, three different models were derived from the aforementioned variables. The three models have been tested using the - folds cross-validation. Results show that the model with primitive variables such GDP per capita, mean, RH, SR, and WSP perform better than the other two models with a coefficient determination equal to 0.87, 0.854, 0.833, and 0.551 for Niamey, Maradi, Zinder, and Agadez, respectively. According to the month considered, the mean absolute percentage error can give a small error for specific combinations of climate variables. The variables such as precipitation and clearness index are found to be not statistically significant.
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28 weeks
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