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电力大数据:2019,22(4):-
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大数据挖掘下冲击性负荷特性电网短期负荷预测的探索与实践
(1.国网抚顺供电公司;2.国网铁岭供电公司)
Exploration and practice of short term load forecasting based on large data mining under impulse load characteristics
(1.Fushun power supply company of national network;2.Tieling power supply company of national network)
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投稿时间:2018-06-26    修订日期:2018-12-07
中文摘要: 抚顺地区冲击性负荷占地区总负荷比重较大,而地区总负荷冲击特性明显时,有可能引起系统频率的连续振荡以及电压摆动,不利于电网安全稳定运行。因此,本文对如何提高地区电网短期负荷预测精确度进行探索和相关的实践,改善冲击性负荷预测和预处理的准确程度,以期望能够合理经济调度、降低生产成本、保障电网安全。
Abstract:The impact load of Fushun area accounts for a large proportion of the total load in the region, and when the impact characteristic of the total load is obvious, it may cause the continuous oscillation of the system frequency and the swing of the voltage, which is not conducive to the safe and stable operation of the power grid. Therefore, this paper explores how to improve the accuracy of short-term load forecasting in regional power grid and related practice, improving the accuracy of impact load forecasting and preprocessing, so as to expect reasonable economic dispatch, reduce production cost and ensure the safety of power grid.
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