STUDI EFEKTIFITAS INDIKATOR KESTABILAN TEGANGAN PADA MODEL DINAMIS SISTEM TENAGA LISTRIK

TITe pape7- presents the effectiveness of voltage stability indices for dynamic povver system modelling study in providing information about the proximity of voltage IN] collapse in power system. Four simple stability indices as Voltage Instability Predictor (VIP), Inpedance Stability Index (ISI), Line Index (L index) and Voltage Collapse Prediction hadex (V(-PI) are conapared using WS(-C9 bus testsystem. The Em comparison show the ISI and VCPI are much More reliable indicator, give the fast Ind indication and fast time computation than L index for voltage collapse in dynamics voltage collapse prediction. Kata Kunci: : Dynamics Voltage Collapse, Voltage Instability Predictor Impedance Stability Index, Line Index, Voltage Collapse Prediction Index

A STATIC AND DYNAMIC TECHNIQUE CONTINGENCY RANKING ANALYSIS IN VOLTAGE STABILITY ASSESSMENT

The objective of the research is to compare between technique for determine the weak bus of the power system using static and dynamic contingency ranking analysis. Identification of the weak bus is very important for providing a proper control system to prevent for voltage collapse. Test system of this research is using the New England (IEEE 39 bus) power system. A severity ranking of the system is carried out on the study system to specify weak buses, in term of voltage instability. A contingency as a load increment is employed to examine the network buses condition and stability margin in the system. Three methods techniques as eigenvalue analysis of jacobian matrix is used as a static methods and a voltage collapse prediction index, and power transfer stability index as a dynamic methods are investigated. The result showed that the static analysis is giving more optimistic in evaluating loadability limit than dynamic. For the contingency ranking both static and dynamic give same trend in every bus. But for final decisions involving several consideration both planning and operation should be confirm by more accurate time domain simulation (dynamic) in which different characteristics of load, multiple controller, protection relays and coordinated them taken into account Key words: contingency analysis, static and dynamic analysis, voltage stabilit

Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System

Abstract—This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN. Keywor ds —Dynamic voltage collapse, prediction, artificial neural network, support vector machines

Performance Evaluation of Fuel Cell and Microturbine as Distributed Generators in a Microgrid

This paper presents dynamic models of distributed generators (DG) and investigates dynamic behaviour of the DG units within a microgrid system. The DG units include micro turbine, fuel cell and the electronically interfaced sources. The voltage source converter is adopted as the electronic interface which is equipped with its controller to maintain stability of the microgrid during small signal dynamics. This paper also introduces power management strategies and implements the DG load sharing concept to maintain the microgrid operation in standalone, grid-connected and islanding modes of operation. The results demonstrate the operation and performance of the microturbine and SOFC as distributed generators in a microgrid. Keywords: Microgrid, Distributed Generation, Microturbine, Fuel Cel

Studi Efektifitas Indikator Kestabilan Tegangan Pada Model Dinamis Sistem Tenaga Listrik

The paper presents the effectiveness of voltage stability indices for dynamic power system modelling study in providing information about the proximity of voltage collapse in power system. Four simple stability indices as Voltage Instability Predictor (VIP), Impedance Stability Index (ISI), Line Index (L index) and Voltage Collapse Prediction Index (VCPI) are compared using WSCC 9 bus test system. The comparison show the ISI and VCPI are much more reliable indicator, give the fast indication and fast time computation than L index for voltage collapse in dynamics voltage collapse prediction

KOHONEN NEURAL NETWORK CLUSTERING FOR VOLTAGE CONTROL IN POWER SYSTEMS

Clustering a power system is very useful for the purpose of voltage stability control. However, the methods have developed usually have computational inefficiency. This paper presents a new cluster bus technique using Kohonen neural network for the purpose of forming bus clusters in power systems from the voltage stability viewpoint. This cluster formation will simplify voltage control in power system. With this proposed Kohonen algorithm, a large bus system will be partitioned into a small bus groups that have a coherence V, �, P and Q. The maximum number of area clusters will be formed need for voltage stability needed. The proposed technique was tested on IEEE 39 bus system by considering two contingency namely load increased and line outage by using voltage collapse analysis. This formation will be compared with the Learning Vector Quantization (LVQ) algorithm. The results showed the proposed technique produces four clusters on contingency load load increased and three clusters online outage contingency on IEEE 39 bus system as shown by the LVQ. Keywords: clustering, Kohonen, learning vector quantization, voltage stabilit

ANALISIS PERFORMATAPIS PELEWATRENDAH PITA LEBAR PADAPENANGGULANGAN HARMONISA BEBAN TIGAFASA TIDAK SEIMBANG

Abstract: Keywords : Harmonics are caused by non linear load. When more harmonics-producing loads are being connected to systems which are unbalanced, effect of single phase harmonics-producing loads are also becoming important. Unbalance load in three phases system increases non linear affected energy consumption in power system. This research aims to know how much harmonics affecting unbalance three phase load, to know reduction harmonics by using Broadband L w Pass Filter. Modelling created and simulated using mathlab to know broadband ter parameter base on harmonics characteristic in three phases load. Measurements are done to know current and voltage harmonics level at source and system before and after filter installed, and calculated percentagesaving ofpower consumption. This research shows that effect of increasing percenta current harmonic level on load side will increase percentage level of load unbalanced. Installing filter will increase percentage of current harmonic although the f amental value rms is decrease. The unbalanced current load average increase 22.5% after filter installed, when currents consumption system reduces by 42% in average,power factor increase to 88.3%, Reactive power reduce up to 88.5% and appare power reduce up to 48.3%. Harmonics, broadband low pass filter, unbalanced loa

KOHONEN NEURAL NETWORK CLUSTERING FOR VOLTAGE CONTROL IN POWER SYSTEMS

 Clustering a power system is very useful for the purpose of voltage stability control. However, the methods have developed usually have computational inefficiency. This paper presents a new cluster bus technique using Kohonen neural network for the purpose of forming bus clusters in power systems from the voltage stability viewpoint. This cluster formation will simplify voltage control in power system. With this proposed Kohonen algorithm, a large bus system will be partitioned into a small bus groups that have a coherence V, θ, P and Q. The maximum number of area clusters will be formed need for voltage stability needed. The proposed technique was tested on IEEE 39 bus system by considering two contingency namely load increased and line outage by using voltage collapse analysis. This formation will be compared with the Learning Vector Quantization (LVQ) algorithm. The results showed the proposed technique produces four clusters on contingency load load increased and three clusters online outage contingency on IEEE 39 bus system as shown by the LVQ

KOHONEN NEURAL NETWORK CLUSTERING FOR VOLTAGE CONTROL IN POWER SYSTEMS

Clustering a power system is very useful for the purpose of voltage stability control. However, the methods have developed usually have computational inefficiency. This paper presents a new cluster bus technique using Kohonen neural network for the purpose of forming bus clusters in power systems from the voltage stability viewpoint. This cluster formation will simplify voltage control in power system. With this proposed Kohonen algorithm, a large bus system will be partitioned into a small bus groups that have a coherence V, �, P and Q. The maximum number of area clusters will be formed need for voltage stability needed. The proposed technique was tested on IEEE 39 bus system by considering two contingency namely load increased and line outage by using voltage collapse analysis. This formation will be compared with the Learning Vector Quantization (LVQ) algorithm. The results showed the proposed technique produces four clusters on contingency load load increased and three clusters online outage contingency on IEEE 39 bus system as shown by the LVQ. Keywords: clustering, Kohonen, learning vector quantization, voltage stabilit

Job satisfaction of secondary school teachers in Tawau, Sabah

In order for the teachers to function effectively in a school system, it is important that teachers need to seek satisfaction and happiness not only in the intrinsic aspects of teaching job but also in other dimensions related to the teacher work experience in the wider social environment. This paper examines the level and differences in the job satisfaction of 200 Sabah secondary school teachers with respect to the various teachers characteristics identified as gender, service category, job title, tenure and place of origin. Data was collected through survey questionnaire. The finding reveals that secondary school teachers in Tawau, Sabah are generally satisfied with their job. There is significant relationship between job satisfaction and gender, whereby the male teachers are generally more satisfied than female teachers. The graduate teachers are more satisfied than non-graduate teachers. The higher ranking teachers are more satisfied than the ordinary teachers. Also, older teachers are more satisfied than younger teachers. However, there is no significant relationship between places of origin of teachers with job satisfaction. Based on the findings, several recommendations are proposed