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电力大数据:2018,21(3):-
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计及行业间同时率的分区最大负荷预测方法及应用
冯磊,李超
(云南电网有限责任公司,杭州鸿晟电力设计咨询有限公司)
The Method of Subarea Maximum Load Forecasting considering with Inter-Industry Simultaneous
fenglei and lichao
(Yunnan Power Grid Co. Ltd.,Hangzhou Hongsheng Electric Power Design Co. Ltd)
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投稿时间:2018-03-08    修订日期:2018-03-13
中文摘要: 电网规划发展由原来的粗放型向集约化转变,这使得设备利用率对经济性影响显著。为了提高设备利用率,本文从提高最大负荷预测准确性的角度,在对现有负荷预测众多方法的归纳总结,以及对行业间典型日特征曲线的分析,引入了行业间负荷同时率的概念,提出了计及行业间同时率的分区最大负荷调整的方法。该方法提出了不同行业之间的负荷高峰时段也存在着差异,即通过行业间同时率对最大负荷预测值进行修正即能得到更为精确的最大负荷预测值。结合文末对线路理论需求的计算的算例表明,计及行业间同时率的最大负荷预测方法可以提升最大负荷预测的准确性,提升设备的利用率以及电力系统经济性运行效益。研究成果对配电网经济性运行具有较大的指导性意义。
Abstract:The development of power grid planning has changed from the original extensive to the intensive, which has made equipment utilization significantly affect economic performance. In order to improve the utilization rate of the equipment, this article has introduced the concept of simultaneous load of industries,from the perspective of improving the accuracy of maximum load forecasting,summed up in many existing load prediction method of induction, and the analysis of the typical daily characteristic curves between inter industries. and introduces the concept of inter industry load rate at the same time, A method for adjusting the maximum load of a subarea that takes into account the simultaneous rate between inter industries has been proposed. This method puts forward that there are also differences between peak load periods of different inter industries. That is to say, by modifying the maximum load forecast value through the inter industry simultaneity rate, a more accurate maximum load prediction value can be obtained. The calculation example of the theoretical demand of the line at the end of the paper shows that the maximum load forecasting method taking into account the simultaneous rate among industries can improve the accuracy of the maximum load forecasting, improve the utilization rate of the equipment, and the economical operation efficiency of the power system. The research results have great guiding significance for the economical operation of distribution networks.
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