• Journal of IKEEE
• /
• v.22 no.2
• /
• pp.460-475
• /
• 2018

In the variable-speed wind energy system, to achieve maximum power point tracking (MPPT), the wind turbine should run close to its optimal angular speed according to the wind speed. Non-linear control methods that consider the dynamic behavior of wind speed are generally used to provide maximum power and improved efficiency. In this perspective, the mechanical power is estimated using Kalman filter. And then, from the estimated mechanical power, the wind speed is estimated with Newton-Raphson method to achieve maximum power without anemometer. However, the blade shape and air density get changed with time and the generator efficiency is also degraded. This results in incorrect estimation of wind speed and MPPT. It causes not only the power loss but also incorrect wind resource assessment of site. In this paper, the adaptive maximum power point tracking control algorithm for wind turbine system based on the estimation of wind speed is proposed. The proposed method applies correction factor to wind turbine system to have accurate wind speed estimation for exact MPPT. The proposed method is validated with numerical simulations and the results show an improved performance.

• Journal of Power Electronics
• /
• v.2 no.3
• /
• pp.155-161
• /
• 2002

This paper presents a maximum power point tracking algorithm for Photovoltaic array using only instantaneous output current information. The conventional Hill climbing method of peak power tracking has a disadvantage of oscillations about the maximum power point. To overcome this problem, we have developed an algorithm that will estimate the duty ratio corresponding to maximum power operation of solar cell. The estimation of the optimal duty ratio involves, finding the duty ratio at which integral value of output current is maximum. For the estimation, we have used the well know Lagrange's interpolation method. This method can track maximum power point quickly even for changing solar isolation and avoids oscillations after reaching the maximum power point.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.617-621
• /
• 2001

This paper presents a maximum power point tracking algorithm for Photovoltaic array using only instantaneous output current information. The conventional Hill climbing method of peak power tracking has a disadvantage of oscillations about the maximum power point. To overcome this problem, we have developed a algorithm, that will estimate the duty ratio corresponding to maximum power operation of solar cell. The estimation of the optimal duty ratio involves, finding the duty ratio at which integral value of output current is maximum. For the estimation, we have used the well know Lagrange's interpolation method. This method can track maximum power point quickly even for changing solar insolations and avoids oscillations after reaching the maximum power point.

• Communications for Statistical Applications and Methods
• /
• v.20 no.4
• /
• pp.311-319
• /
• 2013

Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1317-1326
• /
• 1999

As the integration ratio and operation speed increase, it has become an important problem to estimate the dissipated power during the design procedure as a method to reduce the TTM(time to market). This paper proposed a prediction model to estimate the maximum dissipated power of a CMOS logic gate. This model uses a calculational method. It was formed by including the characteristics of MOSFETs of which a CMOS gate consists, the operational characteristics of the gate, and the characteristics of the input signals. As the modeling process, a maximum power estimation model for CMOS inverter was formed first, and then a conversion model to convert a multiple input CMOS gate into a corresponding CMOS inverter was proposed. Finally, the power model for inverter was applied to the converted result so that the model could be applied to a general CMOS gate. For experiment, several CMOS gates were designed in layout level by $0.6{\mu}m$ layout design rule. The result by comparing the calculated results with those from HSPICE simulations for the gates showed that the gate conversion model has within 5% of the relative error rate to the SPICE and the maximum power estimation model has within 10% of the relative error rate. Thus, the proposed models have sufficient accuracies. Also in calculation time, the proposed models was more than 30 times faster than SPICE simulation. Consequently, it can be said that the proposed model could be used efficiently to estimate the maximum dissipated power of a CMOS logic gate during the design procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.12
• /
• pp.4099-4113
• /
• 2022

In this paper, we propose improved maximum access delay time, noise variance, and power delay profile (PDP) estimation schemes for orthogonal frequency division multiplexing (OFDM) system in multipath fading channels. To this end, we adopt the approximate maximum likelihood (ML) estimation strategy. For the first step, the log-likelihood function (LLF) of the received OFDM symbols is derived by utilizing only the cyclic redundancy induced by cyclic prefix (CP) without additional information. Then, the set of the initial path powers is sub-optimally obtained to maximize the derived LLF. In the second step, we can select a subset of the initial path power set, i.e. the maximum access delay time, so as to maximize the modified LLF. Through numerical simulations, the benefit of the proposed method is verified by comparison with the existing methods in terms of normalized mean square error, erroneous detection, and good detection probabilities.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.1
• /
• pp.22-30
• /
• 1999

This paper presents an efficient algorithm to estimate the maximum load level for heavily loaded power systems with the load-generation vector obtained by ELD (Economic Load Dispach) and/or short term load forecasting while utilizing the elliptic pattern of the P-e curve. It is well known the power flow equation in the rectangular corrdinate is jully quadratic. However, the coupling between e and f makes it difficult to take advantage of this quadratic characteristic. In this paper, the elliptic characteristics of P-e curve are illustrated and a simple technique is proposed to reflect the e-f coupling effects on the estimation of maximum loadability with theoretical analysis. An efficient estimation algorithm has been developed with the use of the elliptic properties of the P-e curve. The proposed algorithm is tested on IEEE 14 bus system, New England 39 bus system and IEEE 118 bus system, which shows that the maximum load level can be efficiently estimated with remarkable improvement in accuracy.

• Communications for Statistical Applications and Methods
• /
• v.28 no.2
• /
• pp.99-118
• /
• 2021

In this paper, we introduce an extended form of the inverse power Lomax model via Marshall-Olkin approach. We call it the Marshall-Olkin inverse power Lomax (MOIPL) distribution. The four- parameter MOIPL distribution is very flexible which contains some former and new models. Vital properties of the MOIPL distribution are affirmed. Maximum likelihood estimators and approximate confidence intervals are considered under Type I censored samples. Maximum likelihood estimates are evaluated according to simulation study. Bayesian estimators as well as Bayesian credible intervals under symmetric loss function are obtained via Markov chain Monte Carlo (MCMC) approach. Finally, the flexibility of the new model is analyzed by means of two real data sets. It is found that the MOIPL model provides closer fits than some other models based on the selected criteria.

• Proceedings of the KIEE Conference
• /
• 2005.11b
• /
• pp.347-349
• /
• 2005

This paper presents an efficient algorithm to estimate the maximum load level for heavily loaded power systems with the load-generation variation vector obtained by ELD (Economic Load Dispatch) and/or short term load forecasting while utilizing the elliptic pattern of the P-e curve. It is well known the power flow equation in the rectangular coordinate is fully quadratic. However, the coupling between e and f makes it difficult to take advantage of this quadratic characteristic. In this paper, a simple technique is proposed to reflect the e-f coupling effects on the estimation of maximum loadability with theoretical analysis. An efficient estimation algorithm has been developed with the use of the elliptic properties of the P-e curve. The proposed algorithm is tested on IEEE 14 bus system, New England 39 bus system and IEEE 118 bus system, which shows that the maximum load level can be efficiently estimated with remarkable improvement in accuracy.

• The Journal of the Acoustical Society of Korea
• /
• v.13 no.4
• /
• pp.20-31
• /
• 1994

The maximum likelihood(ML) estimation has excellent accuracy for frequency estimation of multiple sinusoids, but the maximum likelihood function requires much loss owing to the high nonlinearity. This paper presents a simplified maximum likelihood estimation, in order to improve the nonlinearity of the maximum likelihood estimation for frequencies of sinusoids in signals. This method is applied to the frequency estimation of sinusoidal signals corrupted by white or colored measurement noise. Monte-carlo simulations are conducted for the comparison of ML method with the best MFBLP method, in terms of sampled mean, root mean square and relative bias. The power spectral density and the position of frequency in unit circle are appeared in figures.