Abstract
In this work, the state estimation problem of electric power systems is represented through a mathematical programming approach. Initially, a non-linear mathematical model based on the classical method of weighted least squares is proposed to solve the state estimation problem for comparative purposes. Due to the inherent limitations that this classical model presents when dealing with errors in the set of measurements, a new mathematical model is proposed that can be used within an iterative procedure to reduce the impact of measurement errors on the estimated results. Several tests on a didactic 5-bus power system and IEEE benchmark power test systems showed the effectiveness of the proposed approach which achieved better results than the proposed classical state estimation model. The non-linear programming models proposed in this paper are implemented in the mathematical modeling language AMPL. Additionally, to validate the results of the proposed methodologies, the power system operation points are compared with the results obtained using the Matpower simulation package. The results allowed concluding that the proposed mathematical models can be successfully applied to perform state estimation studies in power systems.
Highlights
Determining the operating point of an Electric Power System (EPS) requires the knowledge of its state variables, which are the magnitudes and angles of the nodal voltages
The main features and contributions of this paper are as follows: (i) it presents a novel approach to carry out the state estimation process in electric power systems based on non-linear programming modeling; (ii) the proposed approach is able to reduce the impact caused by the presence of multiple errors in the set of measurements, without using additional statistical error treatment procedures; (iii) the proposed methodology outperforms the results obtained with the classical Weighted Least Squares (WLS) estimator
This paper presented a novel approach to the state estimation problem in power systems using non-linear programming modeling
Summary
Determining the operating point of an Electric Power System (EPS) requires the knowledge of its state variables, which are the magnitudes and angles of the nodal voltages. This work proposes a novel strategy that allows using a non-linear programming model of the WLS method to reduce the impact of bad measurements on the estimated results; contributing to fill the research gap concerning the effectiveness of the solution to the state estimation problem through the WLS method This solution approach allows the addition of new variables and operational constraints in the formulation, which cannot be considered in the classical WLS method. The main features and contributions of this paper are as follows: (i) it presents a novel approach to carry out the state estimation process in electric power systems based on non-linear programming modeling; (ii) the proposed approach is able to reduce the impact caused by the presence of multiple errors in the set of measurements, without using additional statistical error treatment procedures; (iii) the proposed methodology outperforms the results obtained with the classical WLS estimator.
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