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FORECASTING DOMESTIC HOURLY LOAD PROFILES USING VECTOR REGRESSIONS

机译:使用矢量回归预测家庭每小时加载型材

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Electricity distribution to households and business is the final step in the electricity generation, transmission and distribution value chain. Redistributed energy by municipalities to the South African domestic market is key to planning energy demand and supply. In this study we use the concept of vector regression modelling in forecasting total domestic hourly load profiles. Vector regression is done by aligning the time series so that days and hours match across the time period. A linear model is then fitted across this vector [1]. MSE, MAD and the MAPE are used in the study to evaluate model accuracy. Results from this study show that domestic load profiles are seasonal with peaks in the morning and in the evening around 8pm. Also winter months show high usage compared to the other seasons and this domestic load is by far the most dominant profile shape of netenergy sent out from generation.
机译:对家庭和业务的电力分配是发电,传输和分配价值链的最后一步。由市政当局对南非国内市场的重新分配能量是规划能源需求和供应的关键。在这项研究中,我们使用向量回归建模的概念预测家庭每小时总装载概况。向量回归是通过对齐时间序列来完成的,使得时间和时间匹配在时间段。然后在该载体上安装线性模型[1]。 MSE,MAD和MAPE用于研究以评估模型精度。本研究结果表明,国内负荷型材在早晨和晚上晚上8点左右的季节性是季节性的。冬季几个月展示了与其他赛季相比的高效,这家国内负荷是迄今为止未来发电的NetEnergy最占主导地位的形状。

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