Future Solar Irradiance Prediction Using Least Square Support Vector Machine

Support vector machine (SVM) based on statistical learning theory has shown its advantage in regression and prediction. This paper presents the future prediction of the solar irradiance using least square support vector machine (LSSVM) which is a kind of SVM with quadric loss function. SVM has greater generalization ability and guarantee global minima for given training data set which will give good performance for solar irradiance with time series prediction. In order to improve the prediction performance of the LSSVM, the experimental data have to be normalized and appropriate parameters are selected by generic algorithm. In this research, solar irradiance data are collected daily at monitoring station located at Green Energy Research Centre (GERC) UiTM, Shah Alam. This related information will be used in prediction of the future data which useful for designing new PV systems and monitoring existing systems performance. The results show good agreement between the predicted against the actual values measured.  The proposed solar irradiance time series prediction method is considerable practical value which can be used in other datasets

System Performance Modelling of a Grid-Connected Photovoltaic System in UiTM, Malaysia

This paper presents the prediction of grid-connected photovoltaic (GCPV) system installed at Green Energy Research Center, Universiti Teknologi MARA, Shah Alam, Malaysia located at latitude of 2 °N 101°E. By using Mathematical approach and climate variations of Malaysia such as module temperature and solar irradiance, the prediction of power systems performance parameters were analyzed. The parameter of the study is limited to 26 consecutive days with filter data of 80W/m2 irradiance. This study conducted by using monocrystalline and polycrystalline solar cell technologies. The actual and the predicted data measurement of these solar cell technologies were analyzed. The empirical models were compared according to the coefficient of determination (R2) and percentage error.  MathCAD software was used in order to calculate the prediction and detail analysis of electrical parameters. Finally, the results show a good accuracy between actual and prediction data

Hybrid Stand-alone Photovoltaic Systems Sizing Optimization Based on Load Profile

This paper presents a sizing optimization technique for Hybrid Stand-Alone Photovoltaic (HSAPV). In this research, three optimization techniques have been developed, namely Dolphin Echolocation Algorithm (DEA), Fast Evolutionary Programming (FEP), and Classical Evolutionary Programming (CEP). These techniques have been incorporated into the sizing process to maximize the technical performance of the SAPV system. The components of PV modules, charge controllers, inverters, and batteries are used to determine the optimum value. These components are used as the control parameters to maximize the expected performance ratio (PR) of the SAPV system. The Iterative Sizing Algorithm (ISA) is the benchmarking technique to conduct the optimization technique achieving maximum PR value and minimal computation time. Results obtained from the research show that DE overcomes FEP and CEP. In addition, the optimization techniques also demonstrated comparatively fast with respect to ISA as the benchmark technique.

Development of an automated biaxial solar photovoltaic tracking system / Ahmad Maliki Omar ... [et al.]

This paper presents and describes a prototype product code-named SolT2A which is a system that tracks the position of the sun automatically across the celestial vault in two axes. This kind of system is typically used in a solar photovoltaic (PV) system in terrestrial applications to provide electrical power. It is designed and fabricated due to Malaysia’s location near the equator, thus the solar altitude crosses the zenith and the azimuth reverses direction during the year. Thus the use of a static PV system is not maximised during half of the year. This situation can be addressed by using a two-axes solar tracking system. So far, Malaysia has not implemented such powertracking systems. Thus SolT2A has been designed and fabricated to address the problem by using a combination of electro-mechanical devices with an element of programming ingenuity and intelligence. Basically SolT2A measures solar irradiance at four points and makes comparisons in terms of the intensity received. These data are then analysed and processed by a controller before being sent to a DC motor that ensures the maximum amount of solar irradiance received on the PV panels all the time. Thus SolT2A is a system that maximises the power output of the PV panels to obtain the highest power output continuously. Based on field data, the maximum output open circuit voltage produced by the SolT2A tracking system and that with a static PV system is as much as 82 %. The overall increase in open circuit voltage production is between 15 to 20 % daily. With the technical know-how and proven prototype, Malaysia can look into joining the small and limited but niche pool of expertise in this area. This will not only give immediate socioeconomic impact to the population, but will give an upgrade to Malaysia as a country with expertise in the area. This concept could also be applied to defence systems. With further testing and improvement, SolT2A system can be further upgraded to reach a commercial stage. This will definitely be of commercial interest to the country

Hardware design of magnetically isolated gate driver using insulated gate bipolar transistor (IGBT)

This paper presents the hardware design of compact H-bridge magnetically isolated gate driver using Insulated Gate Bipolar Transistor (IGBT) as power device. The new Gate Driver (GD) circuit is tested experimentally with various switching frequency to observe the performance of the circuit. The compact H-Bridge is design using Proteus in one circuit board with two layers Printed Circuit Board (PCB). Switching transients of the IGBT is analyzed based on the capabilities of the GD circuit

A new fuel cell powered aerospace propulsion system / Thomas Arthur Ward … [et al.]

A fuel cell powered unmanned air vehicle (UAV) named Kenyalang-1 ("Hornbill") was designed, built, and flight-tested at the Universiti Teknologi MARA (UiTM) in Shah Alam, Malaysia. The project was funding under a grant from the Malaysian Ministry of Science, Technology, and Innovation (MOSTI). The UAV is propeller-driven by a DC brushless motor, powered by a 500 W proton exchange membrane (PEM) hydrogen fuel cell. The objective was to demonstrate the design and technological challenges involved and determine the relative merits or shortcomings that fuel cell electrically-powered propulsion systems have over conventional systems. This final project report describes the UAV design and power plant's performance. The results of this analysis will be used to improve the UAV and power plant system for future research and production models

COMPARISON OF NUMERICAL AND EXPERIMENTAL RESULTS FOR OVERTOPPING DISCHARGE OF THE OBREC WAVE ENERGY CONVERTER

OBREC is the latest innovation of overtopping wave energy converter (WEC) which is coalesced with the rubble mound breakwaters. The acquisition of wave overtopping in a front reservoir and consequently releasing process through turbine is the concept of energy production in OBREC. The physical scale model studies of overtopping discharge of the OBREC have recently been done by previous researcher in wave flume at Aalborg University. This paper demonstrates the overtopping behavior of OBREC device using a VOF method with capabilities to solve RANS equation in the numerical suite Flow3D. The purpose of this research is to validate the overtopping discharge performance of the numerical model against the experiments of the OBREC. Based on the observation, the results have shown a good agreement between the validation and physical experiment

Single stage string inverter for grid connected Photovoltaic system with Modified Perturb and Observe (P&O) Fuzzy Logic Control (FLC)-based MPPT technique

This paper presents an implementation of Single-phase Single stage String inverter for Grid connected Photovoltaic (PV) system. The proposed system uses Modified Perturb and Observe (P&O) algorithm implemented using Fuzzy Logic Control (FLC) as Maximum Power Point Tracking (MPPT). The inverter is designed for 340W system using two series of STP170s-24/Ac PV modules. The MPPT unit keeps tracking the maximum power from the PV array by changing the modulation index and the phase angle of inverter's output voltage. The simulation model is developed using Matlab/Simulink to evaluate the performance of the converter. Selected experimental results are also presented in this paper