论文标题
在有限的不确定性下，多区域电力系统的两级强大状态估计
Two-level Robust State Estimation for Multi-Area Power Systems Under Bounded Uncertainties
论文作者
论文摘要
本文介绍了一种两级强大的方法，以估计大规模功率系统的未知状态，而测量和网络参数则受到不确定性的影响。功率网络中考虑的有界数据不确定性（BDU）是一个结构化的不确定性，由于传输线的错误，不准确的建模，未建模的动态，参数变化和其他各种原因，在实用系统中不可避免。在建议的方法中，首先将相应的网络分解为较小的子系统（区域），然后提出了两级算法以进行状态估计。在该算法中，在第一级，每个区域都使用加权的最小二乘（WLS）技术来估算其自身状态，该技术基于强大的混合估计，利用相组量测量单元（PMU），第二级，中央协调器从subarreas中进行了所有结果，并对整个系统进行了强大的估计。 IEEE 30总线测试系统的仿真结果验证了拟议的多区域可靠估计器的准确性和性能。
This paper introduces a two-level robust approach to estimate the unknown states of a large-scale power system while the measurements and network parameters are subjected to uncertainties. The bounded data uncertainty (BDU) considered in the power network is a structured uncertainty which is inevitable in practical systems due to error in transmission lines, inaccurate modelling, unmodeled dynamics, parameter variations, and other various reasons. In the proposed approach, the corresponding network is first decomposed into smaller subsystems (areas), and then a two-level algorithm is presented for state estimation. In this algorithm, at the first level, each area uses a weighted least squares (WLS) technique to estimate its own states based on a robust hybrid estimation utilizing phasor measurement units (PMUs), and at the second level, the central coordinator processes all the results from the subareas and gives a robust estimation of the entire system. The simulation results for IEEE 30-bus test system verifies the accuracy and performance of the proposed multi-area robust estimator.
