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Load forecasting for multiple sites: development of an expert system-based technique

机译:多个站点的负荷预测:基于专家系统的技术的开发

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摘要

Most papers on short-term load forecasting (STLF) emphasize the use of a certain technique rather than the methodology used to arrive at that technique. Moreover, few, if any, of the techniques reported in the literature have looked at the electric power load from a site-independent viewpoint. A newly developed site-independent technique for STLF is analyzed in this paper. The load is modeled using a parameterized rule base and a parameter database. The extraction and representation of knowledge about the load are discussed. A site-independent expert system-based technique is tested using data from different sites around the United States including Alabama, Georgia, Florida, Massachusetts, Texas, Virginia and Washington. The mean absolute percentage errors for 24-h ahead load forecast range from 1.23 to 3.35% over all hours in all seasons. The expert system itself was implemented in UNIX/C, and the solution time per 1 day of forecast is around 4s.
机译:关于短期负荷预测(STLF)的大多数论文都强调使用某种技术,而不是用于得出该技术的方法。此外,从位置无关的观点来看,文献中报道的任何技术(如果有的话)都很少。本文分析了STLF的新开发的站点无关技术。使用参数化规则库和参数数据库对负载进行建模。讨论了有关负荷知识的提取和表示。使用美国各地不同站点(包括阿拉巴马州,乔治亚州,佛罗里达州,马萨诸塞州,德克萨斯州,弗吉尼亚州和华盛顿州)的数据对基于站点的专家系统技术进行了测试。在所有季节中,所有小时的24小时提前负荷预测的平均绝对百分比误差在1.23至3.35%的范围内。专家系统本身是在UNIX / C中实现的,每1天预测的解决时间约为4秒。

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