John Y. C. Chan

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.

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.

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.

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.

Data Mining of Building Electrical Information Based on Radial Basis Function Neural Network

This paper presents a neural network algorithm for data mining in building LV electrical power information. The power information is recorded by web-based power quality monitoring system. Power information is recorded continuously and stored in a central server system. Presently events were identified by power engineers but in the prototype, an expert system will be used to identify events instead. Neural network approach based on the Radial Basis Function Neural Network (RBFNN) was developed to predict power events in the building LV electrical network. The approach provides useful information for facility managers to conduct planning and operation. The proposed algorithm was tested with power data of a commercial building in Hong Kong. The prediction result by using one week of data achieved 75% accuracy. Further works would be conducted to test the algorithm with more data.

A Practical Multi-Sensor Cooling Demand Estimation Approach Based on Visual, Indoor and Outdoor Information Sensing

The operating efficiency of heating, ventilation and air conditioning (HVAC) system is critical for building energy performance. Demand-based control is an efficient HVAC operating strategy, which can provide an appropriate level of HVAC services based on the recognition of actual cooling “demand.” The cooling demand primarily relies on the accurate detection of occupancy. The current researches of demand-based HVAC control tend to detect the occupant count using cameras or other sensors, which often impose high computation and costs with limited real-life applications. Instead of detecting the occupant count, this paper proposes to detect the occupancy density. The occupancy density (estimated by image foreground moving pixels) together with the indoor and outdoor information (acquired from existing sensors) are used as inputs to an artificial neural network model for cooling demand estimation. Experiments have been implemented in a university design studio. Results show that, by adding the occupancy density, the cooling demand estimation error is greatly reduced by 67.4% and the R value is improved from 0.75 to 0.96. The proposed approach also features low-cost, computationally efficient, privacy-friendly and easily implementable. It shows good application potentials and can be readily incorporated into existing building management systems for improving energy efficiency.

Switched-Capacitor-Based Current Compensator for Mitigating the Effect of Long Cable Between PWM Driver and LED Light Source

It is sometimes unavoidable to have light-emitting-diode (LED) light sources and their pulsewidth modulation (PWM) drivers connected by long cables in large-scale illuminations. However, long-cable inductance delays the rate of rise of the driving current pulses and thus leads to the reduction of luminous flux output. It also causes the off-state voltage across the light sources negative, which would deteriorate the life expectancy of the LEDs. A switched-capacitor-based current compensator for correcting the wave shape of the driving current pulses is presented. The methodology is based on transferring the energy stored in the cable to a capacitor at the end of the current pulse and then momentarily boosting the voltage with the capacitor applying to the cable at the beginning of the next current pulse. Thus, the rise time of the current pulses can be shortened. The topological states and operations of the compensator will be described. A simplified design procedure will be given. A prototype for a 12-V, 3-A PWM driver has been built and evaluated. Performance comparisons between the proposed current compensator and prior art and between the systems with and without the compensators will be conducted.

A switched-capacitor-based current compensator for mitigating the effect of long cable connecting between LED driver and light source

In large-scale LED lighting installation, it is sometimes unavoidable to use a long cable to connect light sources to LED drivers. Since LED drivers deliver pulse-width-modulated current, such long cable inductance effect prolongs the rise time of the current pulse and hence adversely affects the luminous output. In addition, the energy stored in cable will be discharging to the LEDs during the off state, giving rise a negative voltage across the terminals of light source, and eventually shortening the lifetime of the light sources. A switched-capacitor-based current compensator is proposed to suppress the current pulse distortion and maintain the LED voltage positive. The idea is based on recycling the energy stored in the cable with a switched capacitor network at the end of a current pulse, and then drives the light source synchronously with the driver at the beginning of the next current pulse. Topological states, operations and experimental results will be given.

A current compensator for mitigating the influence of long cable inductance between the LED driver and the light source

It is sometimes unavoidable to use a long cable to connect the light source to the driver when they are placed far apart in large scale LED lighting installation. Since LED driver typically delivers pulse-width-modulated current pulses, the long cable inductance will delay the rate of rise of the current pulses and will also cause negative off-state voltage across the light source, reducing luminous output and vitiating the life expectancy of the light source. This paper will present a current compensator, which can mitigate the distortion of the current pulses caused by the long cable. The concept is based on recycling the energy stored in the cable at the end of a current pulse and then driving the light source synchronously with the driver at the beginning of the next current pulse. A prototype for a 12V, 4.5A LED driver has been built and evaluated. Topological states, operations and experimental results will be given.