Mohamad Na'im Mohd Nasir

A Distribution Network Reconfiguration based on PSO: Considering DGs sizing and allocation evaluation for voltage profile improvement

The optimized network reconfiguration and Distributed Generations (DG) sizing with allocation instantaneously via Particle Swarm Optimization (PSO) proposed a new way of allocation DG based on low voltage profile. This method consists of three steps. It started with categorized the switching sequences for radial network configuration while observe the P losses and the profile of voltage without DG. The second step is reconfiguration feeder for reduce losses via DGs allocation based on substations geographical location. The final step is sizing and allocation DGs at each bus with low voltage profile produced from the first step, used to mend the voltage profile and minimize the Plosses also compared the result with the geographical based allocation results. The objective of this study is to mend the voltage profile while decreasing the Plosses by using optimization technique considering network reconfiguration, DGs Sizing and allocation concurrently. Four cases are compared which is case 1 is the initial case and taken as a reference. All three stages are tested on standards IEEE 33 bus system by using Particle Swarm Optimization (PSO) technique in MATLAB software. This method proved that improvement of Plosses and voltage profile has been made by change of the switching topology with DGs sizing and allocation technique respectively.

Wind farm layout optimization by using Definite Point selection and genetic algorithm

At present, wind energy industry is facing major design constraints in boosting the power output. These can be overcome by setting up the right turbine at the right place. This paper proposes an optimized layout design of a wind farm by using Definite Point selection(DPS) and genetic algorithm, which can minimize the cost per unit power and minimum wake effects, while sustaining the obligatory space between adjacent turbines for operation safety. The existing cost per unit power can be reduced by changing the dimensions of wind farm with constant area. In this study, the velocity deficits caused by the wakes of each turbine were calculated by using Jensens wake model. The total area of wind farm 2 Km × 2 Km was divided into 10×10 cells with each cell having dimensions 200 m × 200 m. The results showed that power output of the wind farm by using the same area in different dimension was increased even when the total numbers of wind turbines were the same. It was observed that 32 wind turbines in 2 Km × 2 Km area could produce a total power of 16,251.56 kW with fitness value of 0.001537. The present research results had been validated using the results from previous studies.

Pattern recognition of EMG signal during load lifting using Artificial Neural Network (ANN)

This paper describes pattern recognition of electromyography (EMG) signal during load lifting using Artificial Neural Network (ANN). EMG is a method to measure and record the muscle activity when individuals perform certain operation and actions. This research will classify the EMG signal based on force apply to the arm due to the gravity act on it during load lifting. Recognizing pattern based on EMG signal is not an easy task because of the nonlinearities behavior of the signal. It required a good classifier to distinguish each pattern. The motivation of this project is to help the person suffer with hemiparesis to perform daily activities as well as to improve the lifestyle. It is important for patients to realize the hopes of hemiparesis after experiencing their inability to do activity as a normal human. Recognizing EMG pattern is crucially important for rehabilitation control that enables the patients to lift the heavy load despite of their muscle weaknesses. Therefore, a proper analysis of muscle behavior is necessary. The objectives of this research are to extract the important features of EMG signal using time domain analysis and to classify EMG signal based on load lifting using ANN. The experiment was performed to five subjects that were selected mainly based on criteria specified. The EMG signals are acquired at long head biceps brachii. Then, the subjects were asked to lift the loads of 2kg, 5kg, and 7kg. It is expected an accurate classifier which can recognize the pattern precisely and could be further used for arm rehabilitation control.

PSO-tuned PID controller for coupled tank system via priority-based fitness scheme

The industrial applications of Coupled Tank System (CTS) are widely used especially in chemical process industries. The overall process is require liquids to be pumped, stored in the tank and pumped again to another tank. Nevertheless, the level of liquid in tank need to be controlled and flow between two tanks must be regulated. This paper presents development of an optimal PID controller for controlling the desired liquid level of the CTS. Two method of Particle Swarm Optimization (PSO) algorithm will be tested in optimizing the PID controller parameters. These two methods of PSO are standard Particle Swarm Optimization (PSO) and Priority-based Fitness Scheme in Particle Swarm Optimization (PFPSO). Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). It has been demonstrated that implementation of PSO via Priority-based Fitness Scheme (PFPSO) for this system is potential technique to control...

Optimal sizing of solar FV/battery and biogas generator in remote microgrid

It is now becoming increasingly clear that supplying electricity to rural areas is often more economical and cost-effective when it is generated via renewable energy sources rather than grid extension due to prohibitively high costs associated with the latter approach. This paper espouses a better alternative to grid extension for remote communities based on a self-sustaining local economic ecosystem for electrical supply. The proposed supply consists of an optimally sized Hybrid Renewable Energy System (HRES) operating as a remote micro-grid comprised of a Solar PV/Battery and Biogas generator as the main sources. Account is also taken of the utilization of biogas for cooking because energy for cooking is a major requirement for remote communities. Mixed-integer linear optimization is applied to identify the most cost-effective mix of the energy technologies by comparing several combinations among renewable energy sources using a dedicated commercial software package. The optimization aims to minimise the total cost of the system while respecting each energy sources potential constraints and load demand. The performance of each model component is evaluated. It was found that renewable energy combined with energy storage helps reduce the cost of energy.

Novel Rehab Devices’ Feature Extraction Analysis Using EMG Signal via Self-Organizing Maps (SOM)

Rehabilitation device is designed to be an exoskeleton for people who had limb failure that proven beneficial toward rehab program. The device used to facilitate the tasks of the program is able to improve the electrical activity in the motor unit and minimize the mental effort of the user. Electromyography (EMG) is the technique to analyze the presence of electrical activity in musculoskeletal systems related to muscle movement. To prevent from the muscle paralyzed, it is becoming spasticity that the force of movements should minimize the mental efforts needed. To achieve this, the rehab device should analyze the surface EMG signal of normal people to be implemented to the rehab device. The EMG signal collected using noninvasive method is implemented to set the movements’ pattern of the arm rehab device. The signal is filtered and extracted for three time-domain features of standard deviation (STD), mean absolute value (MAV), and root mean square (RMS). The features’ combinations are important to produce the best classification result with less error. To determine the best combination features for any movements, several trials of movements are used by determining the right combination using self-organizing maps (SOM) for the classification process.

Support vector machine for day ahead electricity price forecasting

Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Mac...

Performance evaluation of stand alone hybrid PV-wind generator

This paper presents the performance evaluation of standalone hybrid system on Photovoltaic (PV)-Wind generator at Faculty of Electrical Engineering (FKE), UTeM. The hybrid PV-Wind in UTeM system is combining wind turbine system with the solar system and the energy capacity of this hybrid system can generate up to charge the battery and supply the LED street lighting load. The purpose of this project is to evaluate the performance of PV-Wind hybrid generator. Solar radiation meter has been used to measure the solar radiation and anemometer has been used to measure the wind speed. The effectiveness of the PV-Wind system is based on the various data that has been collected and compared between them. The result shows that hybrid system has greater reliability. Based on the solar result, the correlation coefficient shows strong relationship between the two variables of radiation and current. The reading output current followed by fluctuate of solar radiation. However, the correlation coefficient is shows moder...

Analysis the configuration of earthing system based on high-low and low-high soil structure

Each TNB transmission tower requires a tower footing resistance (TFR) with a lower grounding resistance value that depends on the transmission line voltage. For 132kV and 275kV tower, the TFR must less than 10Ω and 500kV tower must less than 5Ω. The TFR is changeable with variable factors such as soil resistivity. Low TFR provides essential protection to the fault such as lightning strike that may occur at any time. The fault current flow to the lowest resistance path and easily disperses to earth. Back flashover voltage across the insulator of transmission lines may occur when the TFR is high. The TFR is influenced by soil resistivity. There are three parameters affecting the soil resistivity; moisture content, salt content and temperature of the soil. High moisture content in soil will reduce the soil resistivity and resultant low TFR. Small scale moisture control by using Micro Reservoir (MR) irrigation with semi-permeable membranes have the power to offer the stable moisture in soil. By using osmosis ...

Development of Novel Fire Alarm Warning System Using Automated Remote Messaging Method

This paper discussed on design and development of fire warning system using automated remote messaging method. This device enables to alert the owner whenever fire occur that need rapid attention towards the building. This is maybe due to carelessness of user or gas leakage. Fire warning system is an existing project but it will be enhanced. This project discussed the design and implementation of a fire alarm system using the microcontroller which controlled the entire system. This system comprised of smoke detector that linked to PIC and GSM Modem. When smoke detected, the fire alarm will triggered and send a signal to the PIC. The PIC will process the data and transmit the signal to the GSM modem. The GSM modem will send message to alert the building owner. The owner can make further action by informing the nearest fire department. This module is applied for transferring of GSM SMS message to the owner mobile number. The devices can be the early and fast prevention system for building owner.