Optimum Network Reconfiguration and DGs Sizing With Allocation Simultaneously by Using Particle Swarm Optimization (PSO)

This paper presents three stages of methodology. The first stage is to identify the switching operation for radial network configuration while observe the power losses and the voltage profile without Distributed Generation (DG). The second stage is based on previous paper which is feeder reconfiguration for loss reduction with DGs. The last stage is sizing and allocation DGs at buses with low voltage profile resulted from the first stage to improve the power losses and voltage profile also comparing the result with the second stage. The objective of this method proposed is to show that allocation of DGs simultaneously based on low voltage profile can improve network power losses and improvement of voltage profile. The result shows that improvement on network power losses is 54.92% from Distribution Network Reconfiguration (DNR) method. All three stages were tested on standards IEEE 33 bus system by using Particle Swarm Optimization (PSO) technique in MATLAB software. This method proved that improvement of power losses and voltage profile by switching and DGs allocation method

Solar PV Project Implementation Feasibility Study based on Feed-in Tariff in Malaysia

This paper illustrates the solar PV project implementation feasibility study based on Feed-in tariff embark by Malaysian government. The objectives of this study are to increase the awareness about the benefit of Feed-in Tariff (FiT) and to design a framework for solar PV project implementation in Malaysia. FIT is established to offer a guaranteed pricing structure for renewable energy production such as wind, solar, biogas and biogas. This could encourage greater investments in a renewable energy field in Malaysia. The framework is started by explaining the project lifecycle to set the milestone follow by explain the project Work Breakdown Structure (WBS) and Organization Breakdown Structure (OBS). Finally a proper project scheduling is established ensure a success project implementation

Solar PV Project Implementation Feasibility Study based on Feed-in Tariff in Malaysia

This paper illustrates the solar PV project implementation feasibility study based on Feed-in tariff embark by Malaysian government. The objectives of this study are to increase the awareness about the benefit of Feed-in Tariff (FiT) and to design a framework for solar PV project implementation in Malaysia. FIT is established to offer a guaranteed pricing structure for renewable energy production such as wind, solar, biogas and biogas. This could encourage greater investments in a renewable energy field in Malaysia. The framework is started by explaining the project lifecycle to set the milestone follow by explain the project Work Breakdown Structure (WBS) and Organization Breakdown Structure (OBS). Finally a proper project scheduling is established ensure a success project implementation

Classification of EMG Signal Based on Human Percentile using SOM

Electromyography (EMG) is a bio signal that is formed by physiological variations in the state of muscle fibre membranes. Pattern recognition is one of the fields in the bio-signal processing which classified the signal into certain desired categories with subject to their area of application. This study described the classification of the EMG signal based on human body percentile using Self Organizing Mapping (SOM) technique. Different human percentile definitively varies the arm circumference size. Variation of arm circumference is due to fatty tissue that lay between active muscle and skin. Generally the fatty tissue would decrease the overall amplitude of the EMG signal. Data collection is conducted randomly with fifteen subjects that have numerous percentiles using non-invasive technique at Biceps Brachii muscle. The signals are then going through filtering process to prepare them for the next stage. Then, five well known time domain feature extraction methods are applied to the signal before the classification process. Self Organizing Map (SOM) technique is used as a classifier to discriminate between the human percentiles. Result shows that SOM is capable in clustering the EMG signal to the desired human percentile categories by optimizing the neurons of the technique

Development of Automatic Load-Shedding Strategy for Stand-Alone Photovoltaic System

Nowadays, the use of solar energy are extremely developed and delivered worldwide. This paper presents the development of automatic load-shedding strategy for stand-alone photovoltaic system. The design of this project shows the characteristics of solar energy and operation of load-shedding strategy. The main objective of this project is to implement the load-shedding strategy as an emergency controller for stand-alone photovoltaic system. To achieve the objective, research of basic understanding related to this project is very important to understand more about the characteristics of each element in this project. The circuit of the load-shedding system is designed in the SoftCad Eagle PCB Design software. The algorithm controlling the load-shedding scheme is developed in the Arduino IDE. Then, the coding programmed is burn in the microcontroller board and installed with the hardware. Output of this project can support the DC loads and load-shedding strategy scheme is performed based on the designed algorithm

Multi population evolutionary programming approach for distributed generation installation

This paper describes the impact of development distribution in order to identify optimum location and size for distribution generation (DG) in power system network. High demand on the load will cause unstable control power distributed through power loss via power transmition. Therefore smallscale electricity generation is required to ensure large power generated can be used for particular location to minimize power losses. In addition, the implementation of distribution generation will help to reduce the capital cost compared to the existing power plant due to space, speed and power requirement. Thus proper DG location will significantly improve the impact of the power flow analysis by considering the source of energy which is easily obtained. This study will be conducted by using Matlab and the proposed algorithm (MPEP) will be applied on IEEE 30 buses radial distribution system network. As a result, the DG can be located at optimal location and size depending on the losses consume in various type of DG technology systems used in the network. On the other hand, the condition and location DG itself will generate optimal power contribution depending on design strategies that have been implemented

CLASSIFICATION OF ARM MOVEMENT BASED ON UPPER LIMB MUSCLE SIGNAL FOR REHABILITATION DEVICE

Rehabilitation device is used as an exoskeleton for people who experience limb failure. Arm rehabilitation device may ease the rehabilitation programme for those who suffer arm dysfunctional. The device used to facilitate the tasks of the program should improve the electrical activity in the motor unit by minimising the mental effort of the user. Electromyography (EMG) is the techniques to analyse the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person are failed to contract the muscle for movements. To prevent the muscles from paralysis becomes spasticity or flaccid the force of movements has to minimise the mental efforts. To minimise the used of cerebral strength, analysis on EMG signals from normal people are conducted before it can be implement in the device. The signals are collect according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The implementation of EMG signals is to set the movements’ pattern of the arm rehabilitation device. The filtered signal further the process by extracting the features as follows; Standard Deviation(STD), Mean Absolute Value(MAV), Root Mean Square(RMS), Zero Crossing(ZCS) and Variance(VAR). The extraction of EMG data is to have the reduced vector in the signal features for minimising the signals error than can be implement in classifier. The classification of features is by SOMToolbox using MATLAB. The features extraction of EMG signals is classified into several degree of arm movement visualize in U- Matrix form

A Feasibility Study of Internal and External Based System for Pipeline Leak Detection in Upstream Petroleum Industry

Offshore underwater pipelines leaks begin at poor joints, corrosions and cracks and slowly progress to a major leakage. Accidents, terror, sabotage, or theft are some of human factor of pipeline leak. The primary purpose of Pipeline Leak Detection Systems(PLDS) is to assist pipeline managers in detecting and locating leaks earlier. PLDS provides an alarm and display other related data to the pipeline engineers for their decision-making. It is also beneficial because of PLDS can enhance their productivity by reduced downtime and inspection time. PLDS can be divided into internally base PLDS and external hardware base PLDS. The purpose of this paper is to study the various types of leak detection systems based on internal and externally system simultaneously.Meanwhile to define a set of key criteria for evaluating the characteristics of this system and provide an evaluation method of leak detection technology as a guideline of choosing the appropriate system in the future

Power Distribution Network Reconfiguration by Using EPSO for Loss Minimizing

Due to the complexity of modern power distribution network, a hybridization of heuristic method which is called as Evolutionary Particle Swarm Optimization (EPSO) is introduced to identify the open and closed switching operation plans for network reconfiguration. The objectives of this work are to reduce the power losses and improve the voltage profile in the overall system meanwhile minimizing the computational time. The proposed combination of Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) is introduced to make it faster in order to find the optimal solution. The proposed method is applied and it impacts to the network reconfiguration for real power loss and voltage profiles is investigated respectively. The proposed method is tested on a IEEE 33-bus system and it is compared to the traditional PSO and EP method accordingly. The results of this study is hoped to help the power engineer to configure the smart and less lossed network in the future

A 33kV Distribution Network Feeder Reconfiguration by Using REPSO for Voltage Profile Improvement

The complexity of modern power system has contributed to the high power losses and over load in the distribution network. Due to that reason, Feeder Reconfiguration (FR) is required to identify the best topology network in order to fulfill the power demand with reduced power losses while stabilizing the magnitude of voltage. This paper addresses a new optimization method which is called as Rank Evolutionary Particle Swarm Optimization (REPSO). It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. The main objective of this paper is to improve the voltage profile while solves the overload problem by reducing the power losses respectively. The proposed method has been implemented and the real power losses in the 33kVdistribution system has been investigated and analyzed accordingly. The results are compared to the conventional Genetic Algorithm (GA), EP and PSO techniques and it is hoped to help the power system engineer in securing the network in the future