聚类算法在长期负荷预测中的应用

Sanela Carevic, T. Capuder, M. Delimar
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引用次数: 4

摘要

负荷预测是电力系统规划中的一项重要工作。本文以克罗地亚萨格勒布为例,介绍了聚类算法及其在负荷预测中的应用。在配电网中,负荷数据的采集并不总是系统地进行,有些数据往往需要外推。为了使这些方法有效,除了经典的趋势预测方法外,还必须使用额外的计算和分组算法。此外,本文还着重研究了无负荷历史地区的负荷预测问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applications of clustering algorithms in long-term load forecasting
Load forecasting is one of the critical activities in electric power system planning. This paper presents clustering algorithms and their usage in load forecasting on a case study in Zagreb, Croatia. Load data acquisition is not always being systematically conducted in distribution networks and some data often has to be extrapolated. For such methods to work additional computation and grouping algorithms have to be used in addition to classical trend forecasting methods. Furthermore, the paper emphasizes on load forecasting in areas with no load history.
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