Norman C. F. Tse

Hybrid Wavelet and Hilbert Transform With Frequency-Shifting Decomposition for Power Quality Analysis

The wavelet transform, the S-transform, the Gabor transform, and the Wigner distribution function are popular techniques for power quality (PQ) analysis in electrical power systems. They are mainly used to identify power harmonics and power disturbances and to estimate power quantities in the presence of nonstationary power components such as root-mean-square values and total harmonic distortions. Recently, the Hilbert-Huang transform has been also used in PQ analysis. These techniques have proven to be useful in PQ analysis; however, their performances depend on the types of PQ events. In this paper, a novel frequency-shifting wavelet decomposition via the Hilbert transform is introduced for PQ analysis. The proposed algorithm overcomes the spectra leakage problem in the discrete wavelet packet transform and can be used for estimating power quantities accurately and for detecting flickers. The effectiveness of the proposed algorithm was verified by computer simulations and experimental tests.

Wavelet-based algorithm for signal analysis

This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform (CWT) using the complex Morlet wavelet (CMW) is adopted to detect the harmonics presented in a power signal. A frequency detection algorithm is developed from the wavelet scalogram and ridges. A necessary condition is established to discriminate adjacent frequencies. The instantaneous frequency identification approach is applied to determine the frequencies components. An algorithm based on the discrete stationary wavelet transform (DSWT) is adopted to denoise the wavelet ridges. Experimental work has been used to demonstrate the superiority of this approach as compared to the more conventional one such as the fast Fourier transform.

Practical application of wavelet to power quality analysis

This paper presents a computational algorithm for identifying power frequency variations, sub-harmonics, integer harmonics and inter-harmonics, by using wavelet-based transform. The continuous wavelet transform (CWT) using the complex morlet wavelet is adopted to detect the harmonic frequencies presented in a power signal. The frequency detection algorithm is developed from the wavelet ridges and scalogram. A necessary condition is established to discriminate adjacent frequencies. The instantaneous frequency identification approach is applied for the determination of frequencies components presented in a power signal. An algorithm based on the discrete stationary wavelet transform (SWT) is developed to determine the amplitudes of the harmonic frequencies presented in the power signal from the coefficients computed by the CWT

Real-Time Power-Quality Monitoring With Hybrid Sinusoidal and Lifting Wavelet Compression Algorithm

This paper presents a novel algorithm for real-time continuous electrical waveform compression and transmission. The proposed algorithm achieves a high data compression ratio by processing the stationary and non-stationary components of a power waveform separately. It works on integer data which simplifies the computation process, and can be run on a low-cost digital signal processor. The proposed algorithm has been implemented on a prototype meter successfully. Experimental and extensive field tests have confirmed the effectiveness of the algorithm. The prototype smart meter can communicate through a low-power, low-bit-rate sensor network protocol such as ZigBee.

An initial study on computational intelligence for smart grid

This paper proposes a framework on how computational intelligence may be applied in developing smart grid to improve reliability and security of power system. Some examples will be used to demonstrate the feasibility.

A Coreless Electric Current Sensor With Circular Conductor Positioning Calibration

This paper presents a novel coreless current sensor unit for measuring electrical current of circular conductors. The proposed sensor unit consists of three magnetic field sensors and a microcontroller unit (MCU). The new sensor unit does not need a bulky magnetic core necessary for magnetic field concentration, and can be used in the same way as conventional current transformers (CTs). An algorithm is developed to calibrate the outputs of the magnetic field sensors (e.g., Hall effect integrated circuits (ICs) with respect to the relative position of the current-carrying circular conductor. The algorithm can be implemented on a low-cost MCU for automatic real-time operation. Unlike other coreless magnetic field sensors that need to be fixed onto the conductor for accurate current measurement, the proposed sensor unit affords a more flexible installation option. A hardware prototype is constructed for the proposed coreless current sensor unit. The performance evaluation results show that the accuracy of the proposed sensor unit is comparable to the conventional magnetic core CTs.

Hybrid behaviors analysis of photovoltaic array performance

Photovoltaic cells would operate as a load when local solar irradiation declines in series connection, which would result in damage easily. Nowadays modules are often configured with bypass diodes to provide energy releasing route. Furthermore, blocking diode is connected in series before parallel connection in order to prevent inverse power injection. Based on such configurations, this paper was mainly devoted to present a simplified method for characterizing hybrid photovoltaic performance. Newton-Raphson method was adopted for numerical simulations. It was proven to be suitable and effective in model validation coinciding with manufacturer specification. Furthermore, MPP peak positions were reviewed roundly via simulations of the total characteristic curves, especially the operation mismatches caused by random shadows. Different abilities under diverse series/parallel patterns were also investigated for comparison. Researches indicate that: firstly, traditional monotone algorithms of MPPT could be invalid for detecting false maximum only; secondly, the “doorsill effect” of local irradiation intensities, namely that global power output might not be influenced by changes of local shadows; finally, suggestions are put forward that parallel connection should be ranked prior consideration with whole array design, to boost power output relatively.

ZigBee based smart metering network for monitoring building integrated electric vehicle charging circuits

This paper presents a smart metering network for monitoring energy consumption and power quality of building integrated electric vehicle charging network. The smart metering network consists of smart metering devices, a ZigBee communication network, and a central system for power calculation and power quality analysis. The smart metering device captures current and/or voltage waveform and performs waveform compression function and feature extraction. The waveform compression and feature extraction algorithm is developed from FFTW algorithm and DWPT algorithm.

Extending the GMR Current Measurement Range with a Counteracting Magnetic Field

Traditionally, current transformers are often used for current measurement in low voltage (LV) electrical networks. They have a large physical size and are not designed for use with power electronic circuits. Semiconductor-based current sensing devices such as the Hall sensor and Giant Magnetoresistive (GMR) sensor are advantageous in terms of small size, high sensitivity, wide frequency range, low power consumption, and relatively low cost. Nevertheless, the operational characteristics of these devices limit their current measurement range. In this paper, a design based on using counteracting magnetic field is introduced for extending the GMR current measurement range from 9 A (unipolar) to ±45 A. A prototype has been implemented to verify the design and the linear operation of the circuit is demonstrated by experimental results. A microcontroller unit (MCU) is used to provide an automatic scaling function to optimize the performance of the proposed current sensor.

Wavelet-Based Algorithm for Power Quality Analysis

This paper presents a computational algorithm for identifying power frequency harmonics and oscillatory transients by using wavelet-based transform. The Continuous Wavelet Transform (CWT) using the Complex Morlet Wavelet (CMW) is adopted. A frequency detection algorithm is developed from the wavelet scalogram and ridges. A necessary condition is established to discriminate adjacent frequencies. By using adaptive wavelet filters, the instantaneous frequency identification approach is applied to determine the frequencies components and the oscillatory transient. Simulated data was used to demonstrate the accuracy of this approach.