Robust state estimator based on maximum constraints satisfaction of uncertain measurements
Robust state estimator based on maximum constraints satisfaction of uncertain measurements
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DOI：
10.1016/j.measurement.2006.11.019
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发表时间：
2007-04
期刊：
影响因子：
5.6
通讯作者：
A. Al-Othman;M. Irving
中科院分区：
文献类型：
--
作者：
A. Al-Othman;M. Irving
本文开发了一种基于测量不确定性概念的新鲁棒估计器。测量的不确定性通过测量误差的确定性上限和下限进行建模，其中考虑了已知的仪表精度。构造不等式约束来模拟测量中的不确定性。满足大多数不等式约束的解点是所提出的估计器的目标。因此，该估计量被称为最大约束满足（MCS）。通过简单回归示例、直流三总线系统和交流测试系统的模拟问题，讨论了所提出的估计器的鲁棒性和性能。考虑了杠杆测量和不良数据的各种场景，以进一步评估 MCS 估计器的性能。特别是，它表明（MCS）估计器在测量中存在共线性的情况下表现得非常好。结果表明，所提出的估计器在电力系统状态估计中是准确可靠的估计器。
A new robust estimator based on the concept of uncertainty in the measurements is developed in this paper. The uncertainty in the measurements is modeled via deterministic upper and lower bounds on measurement errors, which take into account known meter accuracies. Inequality constraints are constructed to model the uncertainty in the measurements. A solution point satisfying most inequality constraints is the objective of the proposed estimator. Hence, this estimator is known as maximum constraints satisfaction (MCS). The Robustness and performance of the proposed estimator is discussed via simulated problems of simple regression examples, DC three-bus system and an AC test system. Various scenarios of leverage measurements and bad data have been considered for further assessment of the performance of the MCS estimator. In particular, it is shown that the (MCS) estimator performs significantly well in situation where collinearity exists in the measurements. Results show that the proposed estimator is an accurate and reliable estimator in power system state estimation.