Shyh-Jier Huang

Short-term load forecasting via ARMA model identification including non-Gaussian process considerations

In this paper, the short-term load forecast by use of autoregressive moving average (ARMA) model including non-Gaussian process considerations is proposed. In the proposed method, the concept of cumulant and bispectrum are embedded into the ARMA model in order to facilitate Gaussian and non-Gaussian process. With embodiment of a Gaussianity verification procedure, the forecasted model is identified more appropriately. Therefore, the performance of ARMA model is better ensured, improving the load forecast accuracy significantly. The proposed method has been applied on a practical system and the results are compared with other published techniques.

An immune-based optimization method to capacitor placement in a radial distribution system

An immune algorithm (IA) based optimization approach for solving the capacitor placement problem is proposed in this paper. In the capacitor placement problem, those practical capacitor operating constraints, load profiles, feeder capacities and allowable voltage limits at different load levels are all considered while the investment cost and energy loss are minimized. In the proposed method, objective functions and constraints are represented as antigens. Through the genetic evolution, an antibody that most fits the antigen becomes the solution. In this IA computation, an affinity calculation process is also embedded to guarantee the diversity. The process stagnation can be thus better prevented. The proposed method has been applied to a test system and the results are compared with other published techniques.

Application of Morlet wavelets to supervise power system disturbances

A wavelet transform approach using a Morlet basis function is proposed to supervise power system disturbances in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring various disturbances as time varies. The method has been tested on the detection of various simulated disturbances including voltage sag, voltage swell, momentary interruption and oscillatory transients and on the harmonic analysis of the arc furnace from the field test data. Testing results demonstrated the practicality and advantages of the proposed method for the applications.

High-impedance fault detection utilizing a Morlet wavelet transform approach

An application of Morlet wavelets to the analysis of high-impedance fault generated signals is proposed in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring fault signals as time varies. The proposed method has been applied to discriminate the high-impedance faults from the normal switching events, and to examine the faults under various grounds including Portland cement, wet soil and grass. Testing results have demonstrated the practicality and advantages of the proposed method for the applications.

A control algorithm for three-phase three-wired active power filters under nonideal mains voltages

In this paper, a control algorithm for the performance improvement of three-phase three-wired active power filters under nonideal mains voltages is proposed and analyzed. It begins with an analysis of an instantaneous reactive power algorithm that was previously applied to the three-phase active power filter design. In that design, the circuit performance was found unsatisfactory under nonideal test scenarios. Our proposed design was, therefore, motivated in order to solve such problems. In the proposed scheme, not only was the control circuit simplified, but it also served as a potential candidate for the performance improvement of active filter design. The proposed algorithm has been implemented as a prototype. Results of experimental verification under various scenarios are presented.

A Detection Algorithm for Islanding-Prevention of Dispersed Consumer-Owned Storage and Generating Units

One of critical concerns in the operation of grid-connected dispersed generating units is the occurrence of islanding. Islanding may pose hazards to utility personnel and complicate the orderly reconnection of the grid. Hence, in this paper, a new algorithm based on the monitoring of the change in dfldPL to detect the islanding is proposed. By the proposed method, a detection index can be evaluated that serves as a useful reference to activate the protective relays. This approach has been applied to investigate different scenarios, including the loss of grid and the parallel operation. Effects of load change and power-quality disturbances to the detection performance are also examined. From these test results, they help solidify the feasibility and effectiveness of the approach for the applications considered.

Enhancement of damage-detection of wind turbine blades via CWT-based approaches

In this paper, a continuous wavelet transform-based approach is applied to enhance the damage-detection capability of wind turbine blades. With the time--frequency localization features embedded in wavelets, the time and scale information of the acquired signals can be presented as a visualization scheme, where the condition monitoring of turbine blades can be better realized. Based on these sensor signals, this proposed approach was applied to discriminate the damaged structure from the healthy one under several scenarios. Test results have demonstrated the practicality and advantages of the proposed method for the application considered

Application of wavelets to classify power system disturbances

The wavelet transform approach is proposed in this paper to classify various power system disturbances. On encountering various disturbances, the proposed method is useful to categorize these shortfalls into different groups so that operators can decide on strategies to suppress or eliminate them effectively. Different from those Fourier-based transforms, the wavelet transform approach is more efficient in tracking signal dynamics as time varies. The method has been tested through the classification of various simulated disturbances, including voltage sag, voltage swell, momentary interruption, oscillatory transients and flat-tops. Testing results showed the feasibility and practicality of the method for the applications.

FPGA Realization of Wavelet Transform for Detection of Electric Power System Disturbances

Realization of wavelet transform on field-programmable gate array (FPGA) devices for the detection of power system disturbances is proposed in this paper. This approach provides an integral signal-processing paradigm, where its embedded wavelet basis serves as a window function to monitor the signal variations very efficiently. By using this technique, the time information and frequency information can be unified as a visualization scheme, facilitating the supervision of electric power signals. To improve its computation performance, the proposed method starts with the software simulation of wavelet transform in order to formulate the mathematical model. This is followed by the circuit synthesis and timing analysis for the validation of the designated circuit. Then, the designated portfolio can be programmed into the FPGA chip through the download cable. The completed prototype will be tested through software-generated signals and utility-sampled signals, in which test scenarios covering several kinds of electric power quality disturbances are examined thoroughly. From the test results, they support the practicality and advantages of the proposed method for the applications.

An adaptive load shedding method with time-based design for isolated power systems

When an isolated power system encounters a serious disturbance or a large generator unit trip, the system frequency may drop if total generating power is not able to supply the load demand sufficiently. Since an isolated power system possesses a lower inertia with limited reserves, load shedding becomes a critical solution to restore system frequency. In this paper, the initial rate of change of frequency is first detected. A designated time interval and a modification algorithm that considers the maximum frequency change at the last step are integrated to complete a load shedding task. Features of the method include the easy determination of shedding loads and fast trip of the load in anticipation of avoiding the occurrence of over-shedding or under-shedding. Numerical simulations have solidified the effectiveness of the proposed method for the application.