The demand for electrical energy is increasing in most areas in the world. Unstab le fossil fuel price and its rapid depletion have led to an intensive research on new energy source and energy conversion. This paper presents the performance of the energy harvesting which focuses on the experimental work to emulate energy harvesting from the rainwater b y utilizing a Pico-hydro approach installed to a high b uilding. NACuM core DB-370F DC generators, 1000 litres water tank, 0.5 inch diameter piping system used in two different configurations with three different head setups. The result shows a huge energy harvesting potential ob tained from the system and rainwater with maximum 261 milliwatts despite the hardware's limitation in the setup. Hance, contrib utes to the cost-efficient due to its small in size, environmentally friendly, and hassle-free maintenance.
<span lang="EN-GB">The importance of supplying undisturbed electricity keep increasing due to modernization and lifestyle. Any disturbance in the power system may lead to discontinuation and degradation in the power quality. Therefore, detecting fault, fault type and fault location is a major issue in power transmission system in order to ensure reliable power delivery system. This paper will compare two prominent methods to estimate the fault location of double circuit transmission line. Those methods are Discrete Wavelet Transform algorithm and Fast Fourier Transform algorithm. Simulations has been carried out in MATLAB/Simulink and a variety of fault has been imposed in order to analyse the capability and accuracy of the fault location detection algorithm. Results obtained portrayed that both algorithms provide good performance in estimating the fault location. However, the maximum percentage error produced by the Discrete Wavelet Transform is only 0.25%, 0.6% lower than maximum error produces by Fast Fourier Transform algorithm. As a conclusion, Discrete Wavelet Transform possesses better capability to estimate fault location as compared to Fast Fourier Transform algorithm.</span>
Silicon (Si) based power devices have been employed in most high power applications since decades ago. However, nowadays, most major applications demand higher efficiency and power density due to various reasons. The previously well-known Si devices, unfortunately, have reached their performance limitation to cover all those requirements. Therefore, Silicon Carbide (SiC) with its unique and astonishing characteristic has gained huge attention, particularly in the power electronics field. Comparing both, SiC presents a remarkable ability to enhance overall system performance and the transition from Si to SiC is crucial. With regard to its importance, this paper provides an overview of the characteristics, advantages, and outstanding capabilities in various application for SiC devices. Furthermore, it is also important to disclose the system design challenges, which are discussed at the end of the paper.
<span lang="EN-US">Recently, <em>LCL</em> has become amongst the most attractive filter used for grid-connected flyback inverters. Nonetheless, the switching of power devices in the inverter configuration creates harmonics that affect the end application behavior and might shorten its lifetime. Furthermore, the resonance frequencies produced by the <em>LCL</em> network contribute to the system instability. This paper proposes a step-by-step guide to designing an <em>LCL</em> filter by considering several key aspects such as the resonance frequency and maximum current ripple. A single-phase grid-connected flyback microinverter with an <em>LCL</em> filter was designed then constructed in the MATLAB/Simulink environment. Several different parameter variations and damping solutions were used to analyze the performance of the circuit. The simulation result shows a promising total harmonic distortion (THD) value below 5% and harmonic suppression up to 14%.</span>
<span lang="EN-GB">This work is a review on previous research and studies on the solar disturbance activities and faults that occur on the electric power transmission line. Research has shown that low latitude regions could also be affected by solar disturbance events. The effects of these events on earth are considerable and may cause electric power transmission failure. Geomagnetically induced current is one of the ground impacts to the transmission line, which may cause fault or disturbance and consequently power system failure. Solar disturbance data from magnetometers and electric power transmission line fault data from a digital fault recorder are reviewed in this work. These data would be valuable in determining the characteristics and effects of solar disturbances on Malaysia’s electric power transmission lines.</span>
<p>Living in the 21st century, electricity has become a need in every society level. However, numbers of the remote area, especially in third world countries still facing difficulty to reach a grid-connected electricity due to various reasons. As such, this paper presents a prospective study of generating an electrical energy that is converted by utilizing natural resources from the sky. It is realized by implementing a hybrid solar-rainwater harvesting system. Combination of 12Vdc 3Watt solar cells and 3.7 Vdc 129mW pico-hydro implemented in the work has given a great yield reaching average 921 milliwatts of energy produced by the natural resources.</p>
<p>The methods used to quantify finger range of motion significantly influence how hand disability is reported. To date, the accuracy of sensors being utilized in data gloves from the literature has been ascertained yet need further analysis. This paper presents an inertial measurement unit sensor-based data glove for finger joint measurement developed for collecting a range of motion data of distal interphalangeal, proximal interphalangeal and metacarpophalangeal finger joints of an index finger. In this study, three inertial measurement sensors, MPU-6050 and two flexible bend sensors which are capable to detect angle displacement were attached to the distal interphalangeal, proximal interphalangeal and metacarpophalangeal finger joint points on the glove. The data taken from inertial measurement unit sensors and flexible bend sensors were acquired using Arduino and MATLAB software interface. The data obtained were compared with the reference data measured from goniometer to allow for accurate comparative measurement. The percentage of error resulted from MPU-6050 sensor unit were ranged from 0.81 % to 5.41 % were very low which indicates high accuracy when compared with the measurements obtained using goniometer. On the other hand, flexible bend sensor shows low accuracy (11.11 % to 19.35 % error). In conclusion, the inertial measurement unit sensor-based data glove using MPU-6050 sensors can be a reliable solution for tracking the progress of finger rehabilitation exercises. In order to motivate patients to adhere to the therapy exercises, interactive rehabilitation game will be developed in the future incorporating MPU-6050 sensors on all five fingers.</p>
Concern towards power quality (PQ) has increased immensely due to the growing usage of high technology devices which are very sensitive towards voltage and current variations and the de-regulation of the electricity market. The impact of these voltage and current variations can lead to devices malfunction and production stoppages which lead to huge financial loss for the production company. The deregulation of electricity markets has made the industry become more competitive and distributed. Thus, a higher demand on reliability and quality of services will be required by the end customers. To ensure the power supply is at the highest quality, an automatic system for detection and localization of PQ activities in power system network is required. This paper proposed to use Slantlet Transform (SLT) with Support Vector Machine (SVM) to detect and localize several PQ disturbance, i.e. voltage sag, voltage swell, oscillatory-transient, odd-harmonics, interruption, voltage sag plus odd-harmonics, voltage swell plus odd-harmonics, voltage sag plus transient and pure sinewave signal were studied. The analysis on PQ disturbances signals was performed in two steps, which are extraction of feature disturbance and classification of the disturbance based on its type. To take on the characteristics of PQ signals, feature vector was constructed from the statistical value of the SLT signal coefficient and wavelets entropy at different nodes. The feature vectors of the PQ disturbances are then applied to SVM for the classification process. The result shows that the proposed method can detect and localize different type of single and multiple power quality signals. Finally, sensitivity of the proposed algorithm under noisy condition is investigated in this paper.
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