长期空间负荷预测中地平线年负荷人机协同智能

Tao Hong, S. Hsiang, Le Xu
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引用次数: 12

摘要

水平年负荷(HYL)是涉及Gompertz函数的负荷预测算法中的一个重要参数。利用土地利用信息,通过计算机程序确定HYL。然而,当计算机试图寻求最优解但忽略了数据的物理意义时,这种方法就失败了,而规划者可以克服这一点。本文提出并实现了一种利用土地利用信息和规划者领域知识确定地平线年负荷的方法。所提出的方法已被实施并应用于几家美国公用事业公司,以计算服务区域内小区域的HYL。将所得的HYL用于长期负荷增长预测,并得到了满意的预测结果。
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Human-machine co-construct intelligence on horizon year load in long term spatial load forecasting
Horizon year load (HYL) is an important parameter in load forecasting algorithms that involve the Gompertz functions. Land use information has been utilized to determine HYL by computerized program. However, this approach fails when computer tries to seek optimal solution but ignores the physical meaning of the data, which can be overcome by the planners. This paper proposes and implements a methodology to determine horizon year load using land use information and planners' domain knowledge. The proposed methodology has been implemented and applied to several US utility companies to calculate the HYL of the small areas in the service territory. The resulting HYL has been used to drive the long-term electric load growth forecasting and to get satisfying forecast.
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