Kab-Ju Hwang

Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systems

In this paper, a hybrid model for short-term load forecast that integrates artificial neural networks and fuzzy expert systems is presented. The forecasted load is obtained by passing through two steps. In the first procedure, the artificial neural networks are trained with the load patterns corresponding to the forecasting hour, and the provisional forecasted load is obtained by the trained artificial neural networks. In the second procedure, the fuzzy expert systems modify the provisional forecasted load considering the possibility of load variation due to changes in temperature and the load behavior of holiday. In the test case of 1994 for implementation in the short term load forecasting expert system of Korea Electric Power Corporation (KEPCO), the proposed hybrid model provided good forecasting accuracy of the mean absolute percentage errors below 1.3%. The comparison results with exponential smoothing method showed the efficiency and accuracy of the hybrid model. >

A parameter estimation of Weibull distribution for reliability assessment with limited failure data

The Weibull distribution is a good candidate for accurate probabilistic model with its rich shape-forming ability and relatively simple CDF (cumulative distribution function). If there are sufficient information to get convincible mean and variance for a probabilistic event, reliable parameters of the Weibull distribution can be determined uniquely. However, sufficient information is not given as usual There needs more deliberate model building method for that case. This paper presents an effective parameter estimation technique for Weibull distribution with limited failure data.

Output Regulation of Uncertain Nonaffine in Control Systems via Singular Perturbation Technique

Abstract The problem of output regulation for nonlinear control systems with guaranteed transient performances in the presence of uncertainties is discussed, where the nonlinear systems are nonaffine in the control. The fast dynamical controller with the highest output derivative in feedback loop is used, where the controller is proper and can be implemented without ideal differentiation. Two-time-scale motions are induced in the closed-loop system and the method of singular perturbations is used to analyze the closed-loop system properties. Stability conditions imposed on the fast and slow modes and sufficiently large mode separation rate can ensure that the full-order closed-loop system achieves the desired properties in such a way that the output transient performances are desired and insensitive to external disturbances and variations of nonlinear system parameters. The problem of absolute stability analysis of the fast-motion subsystem for nonaffine systems with two-time-scale motions is considered in the presence of a sector-like condition in the control.

Development of moving target detection based on image processing techniques

In order to effectively detect moving targets in strong noise conditions, we proposed an image processing method based on wavelet and Hough transform (HT) for multiple moving targets detection. Firstly, the noise is removed from the received signal by the wavelet technique. We propose an improved wavelet threshold function. The new threshold function not only reduces constant error of soft thresholding but also improve the discontinuity of hard thresholding. Secondly, the image processing technique of the Hough transform is used. The benefits of this method include improved performance of detection, implementation flexibility, which indicates the effectiveness and robustness of the algorithm.

Optimal Power Flow based on Generation Rescheduling Priority for Transient Stability Enhancement

Abstract This paper presents an optimal power flow method based on the generation rescheduling priority to enhance transient stability in power systems. In order to determine the generation rescheduling priority the energy margin sensitivity indices are calculated. The candidate generators for generation rescheduling are determined by the energy margin sensitivity indices and then optimal power flow (OPF) is calculated. The OPF formulates the Lagrangian function with the power flow equations and the fuel cost function and searches the optimal solution of the Lagrangian function by using the Newtons approach. The method proposed is applied to a 6-bus 7-lines system to demonstrate its effectiveness.

A PWM-based scheme for Power Factor Correction

Power Factor Correction (PFC) is a technique to compensate the unwanted effects of reactive loads that make the power factor less than unity. The technique described in this paper clearly apparent as a simple and cost effective power factor (PF) measurement and correction scheme by using Programmable Interface Circuit (PIC) microcontroller. This system is especially applicable for industries and multi-storied buildings. The proposed design has the ability to sense power factor effectively and by using proper algorithm sufficient capacitors are switched on in order to compensate the reactive power. A preferred embodiment also includes a LCD display to show the lead-lag power factor and the number of capacitor banks that are switched on. The circuit in this design has been implemented and tested in the laboratory.

Vehicle Following Longitudinal Decentralized Feedback Control Based on Two-Time-Scale Motions

This paper is concerned with the problem of autonomous vehicle following control system design. Decentralized control scheme is used to provide the desired transient performances and spacing error given that an on-board equipment allows to measure the ego-vehicles relative position with respect to its preceding vehicle. The paper treats a question of controller design in presence of such uncertainties as mass of the vehicle, aerodynamic drag, and tire drag. The presented design methodology of continuous-time decentralized controller guarantees desired transients by inducing of two-time-scale motions in the closed-loop system. Stability conditions imposed on the fast and slow modes and sufficiently large mode separation rate between fast and slow modes can ensure that the full-order closed-loop autonomous vehicle following system achieves the desired properties in such a way that the transient performances are desired and insensitive to external disturbances and vehicles parameter variations. The method of singular perturbations is used throughout the paper. Numerical simulations for a three-vehicle platoon are presented.

A New Method for Improving the Detection Capability of RADAR in the Presence of Noise

A RADAR system deals with many different and diverse problems for the last few decades. The detection capability of radar is one of the most important factors. The main objective of radar target detection is to improve probability of detection while reducing probability of a false alarm at the same time. To improve the probability of detection of moving target, a new approach is proposed in this paper using wavelet and Hough transforms. The wavelet de-noising technique is used to remove noise from received signal. Then the image processing technique of the Hough transform is used to detect moving target. To reduce the noises form received signal, we propose a new wavelet threshold function that reduces constant error of soft thresholding and improves the discontinuity of hard thresholding. We present performances of our method on a basis of the new thresholding technique and compare with traditional method. It is shown that detection performance of proposed method is superior to that obtained through traditional method.

Generation Rescheduling Based on Energy Margin Sensitivity for Transient Stability Enhancement

This paper presents a generation rescheduling method for the enhancement of transient stability in power systems. The priority and the candidate generators for rescheduling are calculated by using the energy margin sensitivity. The generation rescheduling formulates the Lagrangian function with the fuel cost and emission such as x NO and x SO from power plants. The generation rescheduling searches for the solution that minimizes the Lagrangian function by using the Newtons approach. While the Pareto optimum in the fuel cost and emission minimization has a drawback of finding a number of non-dominated solutions, the proposed approach can explore the non-inferior solutions of the multiobjective optimization problem more efficiently. The method proposed is applied to a 4-machine 6-bus system to demonstrate its effectiveness.

Generation Rescheduling Considering Generation Fuel Cost and CO 2 Emission Cost

This paper presents a method of generation rescheduling using Newton`s Approach which searches the solution of the Lagrangian function. The generation fuel cost and emission cost functions are used as objective function to reallocate power generation while satisfying several equality and inequality constraints. The Pareto optimum in the fuel cost and emission objectives has a number of non-dominated solutions. The economic effects are analyzed under several different conditions, and emission reductions offered by the use of storage are considered. The proposed approach can explore more efficient and noninferior solutions of a Multiobjective optimization problem. The method proposed is applied to a 4-machine 6-buses system to demonstrate its effectiveness.