Zulkifli Othman

Performance analysis of dual-axis solar tracking system

This paper presents the performance analysis of dualaxis solar tracking system using Arduino. The ultimate objective of this project is to investigate whether static solar panel is better than solar tracker, or the opposite. This project is divided into two stages namely, hardware and software development. In hardware development, five light dependent resistors (LDR) were utilized to capture the maximum light source from the sun. Two servo motors also were employed to move the solar panel to maximum light source location sensed by the LDRs. As for the software part, the code was constructed by using C programming language and was targeted to the Arduino UNO controller. The performance of the solar tracker was analyzed and compared with the static solar panel and the result showed that the solar tracker is better than the static solar panel in terms of voltage, current and power. Therefore, the solar tracker is proven more effective for capturing the maximum sunlight source for solar harvesting applications.

A hybrid bat Algorithm Artificial Neural Network for grid-connected photovoltaic system output prediction

This research have been conducted to predict the output power of grid-connected photovoltaic (GCPV) system using hybrid Bat Algorithm-Artificial Neural Network (BA-ANN) in this paper. In this project, ANN utilized data from GCPV database includes Solar Irradiance (SI), Ambient Temperature (AT) and Module Temperature (MT) as the inputs and apply output power as a single output. More importantly, bat algorithm optimization was apply to minimize Root Mean Square Error (RMSE) by optimized the number of neurons in the hidden layer, learning rate and momentum rate. After training steps, testing will take a part for affirm the ANN training. The results obtained have been compared with the results from Evolutionary Programming-Artificial Neural Network (EP-ANN) with the similar input and output configurations. It is observed that result for BA-ANN had performed more than EP-ANN in term of producing lower RMSE. Besides that, optimal learning algorithm, time taken, and population were also take part in this research.

Harmony search-based optimization of artificial neural network for predicting AC power from a photovoltaic system

Grid-Connected Photovoltaic (GCPV) system is a type of photovoltaic (PV) systems which has been widely used as a renewable-based electricity generation. Nevertheless, the intermittency and fluctuation in weather conditions have caused inconsistent and varying output performance of a GCPV system. This paper presents a Multi-Layer Feedforward Neural Network (MLFNN) model for predicting the AC power from a GCPV system. Harmony Search (HS) was also employed to optimize several MLFNN parameters such that the prediction error could be minimized. The AC Watt-output of a GCPV system was predicted using MLFNN with solar irradiance, ambient temperature and operating PV module temperature as its inputs. These data were collected from a GCPV system located at Green Energy Research Centre (GERC), Universiti Teknologi MARA, Malaysia. In optimizing the MLFNN, HS was introduced to determine the optimal number of neurons in hidden layer, the learning rate and the momentum rate during training. After the training, testing process was conducted to validate the training process. In both training and testing, the prediction performance was quantified using Root Mean Square Error (RMSE). The performance of the HS-MLFNN was later compared with the performance of an Evolutionary Programming (EP)-MLFNN in predicting the AC power. The results showed that the hybrid HS-MLFNN had outperformed the hybrid EP-MLFNN by producing lower RMSE during both training and testing.

Bees algorithm technique for loss minimization in power transmission network using Static Var Compensator

This paper presents the application of Bees Algorithm (BA) technique for loss minimization in power transmission network. The loss minimization technique is implemented through Static Var Compensator (SVC) installation and the optimization technique is the Bees Algorithm. Bees Algorithm was developed to optimally determine the SVC values to be installed in the power transmission network. In this study, SVC was modeled as an effective capacitive reactance equivalent which aims to alter the transmission lines properties in the system. In order to perform validation process, a 26-bus IEEE Reliability Test System (RTS) will be utilized and tested in minimizing total transmission loss in the system.

High-sensitivity gas detection and monitoring system for high-risk welding activity

This study attempted to investigate and design a new mechanism in monitoring safety by detecting gas concentration levels to prevent an explosion during welding activities at a high-risk site. The objective of this project was to design and develop a new safety precaution monitoring system during welding activity using a low-cost microcontroller to improve the current practice. The study was conducted by dividing the project into three stages: sensing, controlling, and notification. At the sensing stage, different gas concentration levels have been tested and analyzed to determine the safety range or level. However, the controller part managed the responses based on the detection of gas in the environment. Indicator and secure digital memory have been used to notify and record the activity during the operation. In the environment test, the system starts to trigger when sensing the level produced at 1.416 V, which represents 30% of the gas concentration. Nevertheless, the gas sensor required a 10-second initialized time to stabilize and produce the desired sensing level. At the end of this paper, the system has been successfully designed, developed, and tested at the prototype level.

Implementation of Real-Time Kinematic Data to Determine the Ionospheric Total Electron Content

Ionosphere layer is an important medium in communication system. At this layer where the total electron content exist because of ionization by the Suns extreme ultraviolet radiation, meanwhile the night side ionosphere electron content is reduced by chemical recombination. Maximum Total Electron Content (TEC) was detected at 0500 Local Time Clock (LTC) and will decrease gradually and reached its minimum at 2200 LTC. TEC during the day is higher than at night. The ultraviolet (UV) radiation from the sun ionizes fractions of the neutral atmosphere and forms the ionosphere. The elevation angle of satellite will also influence the TEC value. The higher elevation angle, the value of vertical TEC will also increase. The data from GPS Stations in RINEX format is supplied by Department of Survey and Mapping Malaysia (JUPEM). The data is taken from two different stations located at GPS Station Arau, Perlis and GPS Station Universiti Teknologi Malaysia Skudai, Johor.

Pico-hydro power generation using dual pelton turbines and single generator

Pico-hydro generation system is the effective way to help the remote communities by generates electricity using water as a main source. The main objective of this project is to introduce the green technology for the society in order to reduce the cost of fuel consumption. Green technology is an alternative energy whereas it is cheap, effective and reliable. It can reduce sources of fuel, capital costs and pollution. Furthermore, the idea of this project is to generate electricity by develop a prototype of pico-hydro generation system that produce low capacity to be used in rural communities. Generally, this project focused on designing and producing a pico-hydro system that can be used for small capacity equipments such as motor and bulb. Besides, this project able to analyze the output of generator based on the rotation of turbine. Water flow in the high-pressure PVC pipe has potential to drive the turbine where it is connected with a generator to convert mechanical energy to electrical energy. In this project, it can be found that the pulley system can increase the efficiency of the turbine. The turbine that connected to the pulley system required lower speed compared to the turbine that connected directly to the generator.

Optimal Sizing Stand Alone Photovoltaic System Using Evolutionary Programming

The project is about development of Optimal Sizing Software of Stand-alone Photovoltaic System at minimum cost. The software has the capabilities to optimize the PV configuration array and battery bank configuration array at lowest cost using Evolutionary Programming (EP) algorithm. This software also can calculate the system design cost, and the maintenance cost. The result showed best system cost reduction has been achieved using EP algorithm. This method provides a fast solution to give the best result.

Optimal design of stand alone photovoltaic system using evolutionary programming

This paper proposes the optimization of Photovoltaic-Battery system with MPPT-based charge controller using Evolutionary Programming in MATLAB. Therefore, this research includes the determination of appropriate system voltage, battery bank, Photovoltaic array and inverter needed in order to fulfill the required load. On the other hand, the selected photovoltaic module will be identified from different type of photovoltaic modules with and without using Evolutionary Programming which plays an important role in this system to get more efficient of photovoltaic module. Thus, the result is obtaining the cost of Stand Alone Photovoltaic system components. The data of load profile and solar irradiation are classified known from location in Tawau, Sabah.

Sizing Software of a Solar Farm System

This paper presents sizing software for the design of a solar farm system. The sizing software provides few guidelines to the designer for the planning procedure before the final of optimum array configuration is decided. Some specifications that the designer may consider are the type of PV module, the type of inverter, the available space for installation, the required energy per year and also the sum of money to be allocated for the instalment. The output result of this software will be the suggestion of possible configuration of the total number of modules in series per string with the total number of strings in parallel. This software also does the prediction of the system performances such as final yield, specific yield and performance ratio. The expected income is provided by the software is based on the Feed-in Tariff rates and the energy generated by the system.