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On the Local Identifiability of Load Model Parameters in Measurement-based Approach
Choi, Byoung-Kon,Chiang, Hsiao-Dong The Korean Institute of Electrical Engineers 2009 Journal of Electrical Engineering & Technology Vol.4 No.2
It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.
Development of Composite Load Models of Power Systems using On-line Measurement Data
Choi Byoung-Kon,Chiang Hsiao Dong,Li Yinhong,Chen Yung Tien,Huang Der Hua,Lauby Mark G. The Korean Institute of Electrical Engineers 2006 Journal of Electrical Engineering & Technology Vol.1 No.2
Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.
Trust-Tech based Parameter Estimation and its Application to Power System Load Modeling
Choi, Byoung-Kon,Chiang, Hsiao-Dong,Yu, David C. The Korean Institute of Electrical Engineers 2008 Journal of Electrical Engineering & Technology Vol.3 No.4
Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.
On the Local Identifiability of Load Model Parameters in Measurement-based Approach
Byoung-Kon Choi,Hsiao-Dong Chiang 대한전기학회 2009 Journal of Electrical Engineering & Technology Vol.4 No.2
It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter illconditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.
Trust-Tech based Parameter Estimation and its Application to Power System Load Modeling
Byoung-Kon Choi,Hsiao-Dong Chiang,David C. Yu 대한전기학회 2008 Journal of Electrical Engineering & Technology Vol.3 No.4
Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.
Development of Composite Load Models of Power Systems using On-line Measurement Data
Byoung-Kon Choi,Hsiao-Dong Chiang,Yinhong Li,Yung-Tien Chen,Der-Hua Huang,Mark G. Lauby 대한전기학회 2006 Journal of Electrical Engineering & Technology Vol.1 No.2
Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.