电力系统低模型耦合智能状态估计
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TM73

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中国南方电网有限责任公司科技项目(ZDKJXM20180087)


Smart power system state estimation with low model coupling
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    摘要:

    在传统电力系统状态估计中,状态修正方程的迭代步长一般选取固定值,该方法常因数据质量低、网络条件复杂而不能有效收敛。为解决该问题并提高状态估计的适配性,首先,对经典逻辑函数进行重构,找到在图像上与状态估计高质量数值迭代具有天然适配性的母函数,并将其作为步长控制因子,通过控制参数实现步长因子的智能调整。然后,引入权因子函数,使算法在迭代过程中执行变权操作,可降低不良数据的影响。与解析方法调整步长的策略相比,该方法具有对模型耦合性较低、可移植性强的特点。最后,以IEEE 30节点系统为例,在量测出现不良数据和网络准病态、病态的条件下,验证所提方法的数值稳定性、运算效率和估计质量均明显优于传统固定步长方法。

    Abstract:

    In traditional power system state estimation (PS-SE), the iterative step size of the state correction equation is generally fixed. But this method often fails to converge effectively because of the low data quality and complex network conditions. For the purpose of solving this problem and improving the suitability of state estimation, the classical logic function is reconstructed to find the generating function which is naturally suitable for the high-quality numerical iteration of state estimation on the image. Then, this function is considered as the step size control factor, and the step size factor can be adjusted intelligently by controlling parameters. After that, the weight factor function introdueced to make the algorithm perform variable weight operation in the iterative process and the influence from the bad data can be reduced then. Compared with the analytical method in terms of an adjustable step size, this method has the characteristics of low coupling in model and strong portability. Consider an IEEE30 node system as example. It is found that the proposed algorithm is superior to the traditional fixed step size method in terms of numerical stability, computation efficiency, and estimated quality when the measurement has bad data and the power system is under quasi ill-conditioned and ill-conditioned.

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赵化时,李胜,林子杰,何宇斌,周华锋,陈根军,胡斯佳,曹一家.电力系统低模型耦合智能状态估计[J].电力科学与技术学报,2022,(2):116-128. ZHAO Huashi, LI Sheng, LIN Zijie, HE Yubin, ZHOU Huafeng, CHEN Genjun, HU Sijia, CAO Yijia. Smart power system state estimation with low model coupling[J]. Journal of Electric Power Science and Technology,2022,(2):116-128.

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  • 在线发布日期: 2022-05-26
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