马 杰, 韩民晓, 姚蜀军. 基于模型参数递推修正的电力负荷建模[J]. 现代电力, 2010, 27(2): 11-14.
引用本文: 马 杰, 韩民晓, 姚蜀军. 基于模型参数递推修正的电力负荷建模[J]. 现代电力, 2010, 27(2): 11-14.
Ma Jie, Han Minxiao, Yao Shujun. Electric Load Modeling Based on Model Parameters Recurrence Modification[J]. Modern Electric Power, 2010, 27(2): 11-14.
Citation: Ma Jie, Han Minxiao, Yao Shujun. Electric Load Modeling Based on Model Parameters Recurrence Modification[J]. Modern Electric Power, 2010, 27(2): 11-14.

基于模型参数递推修正的电力负荷建模

Electric Load Modeling Based on Model Parameters Recurrence Modification

  • 摘要: 随着负荷特性记录装置所记录数据的增加, 使用基因优化算法进行负荷建模的工作量急剧增加。本文借鉴综合负荷建模的思想, 提出将不同时段实测数据辨识得到的负荷模型进行综合, 以充分利用之前的辨识结果, 解决负荷实测记录数据样本数增多引起的辨识过程过长问题, 并给出了详尽的TVA负荷模型综合公式。讨论了权重的选择原则, 考虑到新的数据能更真实地反映负荷的特性, 提出了按时段定性确定权重系数的方法。基于现场实测数据的建模实践表明, 所提方法简单、有效、省时, 能从很大程度上反映负荷的时变性。

     

    Abstract: As the recorded data of load characteristic recording devices increase, the calculation work of load modeling using genetic optimizing algorithm increases dramatically. Referring to synthesis load modeling method, the idea of integrating composite load models in different time interval is proposed to take full advantages of the previous identification results and to reduce identification process. Detailed recurrence formulas are given. The weight coefficient selection principle is discussed. Owing that the new data can reflect load characteristics better, weight coefficient selection principle according to recorded time of data are given. Pratical load modeling shows that this method is simple, effective, time saving and can reflect the time variant load.

     

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