• Journal of Electrical Engineering and Technology
• /
• v.4 no.3
• /
• pp.360-364
• /
• 2009

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.

• Proceedings of the KIEE Conference
• /
• 1998.07c
• /
• pp.1073-1075
• /
• 1998

This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management Program. Bass diffusion model was applied in this paper, which has different values according to parameters ; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameter, there are no empirical results in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints are empirical results or expert's decision. Case studies show the diffusion curves of high-efficient lighting and also forecasting of the peak value for power demand considering diffusion of high-efficient lighting, the feedback and least-square parameter estimation method used in this paper enable us to evaluate the status and forecasting of the effect of DSM program.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.4
• /
• pp.451-459
• /
• 2008

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.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.7
• /
• pp.875-882
• /
• 2014

In this paper, we propose a new parameter estimation method that can deal with the data of multiple time intervals simultaneously. If there are common modes in the multiple time intervals, it is possible to create a new polynomial by summing the coefficients of the prediction error polynomials of each time interval. By calculating the roots of the new polynomial, it is possible to estimate the common modes that exist in each time interval. The accuracy of the proposed parameter estimation method has been proven by using appropriate test signals.

• Journal of Information Processing Systems
• /
• v.16 no.2
• /
• pp.394-405
• /
• 2020

The parameters of transmission lines have an influence on the electromagnetic environment surrounding the line. This paper proposes a method based on phasor measurement unit (PMU) and supervisory control and data acquisition (SCADA) to achieve online estimation of transmission line full parameters, such as resistance, reactance and susceptance. The proposed full parameter estimation method is compared with the traditional method of estimating resistance independently based on SCADA system. Then, the electromagnetic environment is analyzed based on the different parameter estimation methods. The example results illustrate that online estimation of transmission line full parameters is more accurate in the analysis of electromagnetic environment, which further confirms its necessity and significance in engineering application.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.503-506
• /
• 2003

In this paper, we present the results of parameter estimation for do-dc converter model by system identification. The parameter estimation for dc-dc converter aims at the diagnosis of its operating status. we applied the system identification method for parameter estimation. For verification of estimated parameter, we compare bode plot of estimated system transfer function and measurement results of HP4194 instrument.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.785-787
• /
• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1183-1189
• /
• 1999

This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management program. Bass diffusion model was applied in this paper, which has different values according to the following parameters; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameters precisely, there has been no empirical way in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints can be empirical results or expert's decision. Case studies show the diffusion curves and forecasted values of the peak for the high-efficient lighting. The feedback and nonlinear least-square parameter estimation methods used in this paper enable us to evaluate the status and to predict the effect of DSM program.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.4
• /
• pp.380-385
• /
• 1990

This Paper presents a general algorithm for the parameter estimation of an antoregressive moving average process observed in additive white noise. The algorithm is based on the Gauss-Newton recursive prediction error method. For the parameter estimation, the output measurement is modelled as an innovation process using the spectral factorization, so that noise free RPE ARMA estimation can be used. Using apriori known properties leads to algorithm with smaller computation and better accuracy be the parsimony principle. Computer simulation examples show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.408-412
• /
• 2009

In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.