A. A. Mohd Zin

MATLAB/Simulink based modeling and simulation of power quality disturbances

The continuous monitoring of power quality (PQ) disturbances in electrical power distribution system has become an important issue for utilities and customers. The power system operation can be improved and maintained by analyzing the PQ disturbances systematically. In this paper, an attempt has been made to review the modeling and simulation of the PQ disturbances due to the exploitation of various types of loads. The PQ disturbances are created by using parametric equations as well as electrical power distribution system models in MATLAB/SIMULINK environment. The PQ disturbances of voltage magnitude variation such as sag, swell and interruption are created by applying different types of faults and heavy load in the power distribution model. The frequency variation types of PQ disturbances like harmonics are generated by applying power electronic converter. The non-stationary or transient PQ disturbances are produced by applying a capacitor switching bank in distribution model. The results of PQ disturbance waveforms obtained by both techniques are very similar to realtime PQ signals. The PQ waveforms obtained are suitable for checking the performance of the new automatic classification algorithms.

Steady state analysis of power transmission using unified power flow controller

This paper presents the application of UPFC in steady-state analysis and demonstrates the capabilities of UPFC in controlling real and reactive power flow within any electrical network. The PWM based UPFC model is implemented in Single Machine Infinite Bus system and 22-bus IEEE test system. To demonstrate the performance of PWM based UPFC model in power system, both power system networks have been simulated using PSCAD/EMTDC. From the simulation results, it has been shown that the UPFC controller is capable of controlling independently real and reactive power flow through the transmission line. It has also been shown that UPFC can be used for voltage support.

Application of neural network observer for on-line estimation of salient-pole synchronous generators' dynamic parameters using the operating data

Parameter identification is critical for modern control strategies in electrical power systems which is considered both dynamic performance and energy efficiency. This paper presents a novel application of ANN observers in estimating and tracking Salient-Pole Synchronous Generator Dynamic Parameters using time-domain, on-line disturbance measurements. The data for training ANN Observers are obtained through off-line simulations of a salient-pole synchronous generator operating in a one-machine-infinite-bus environment. The Levenberg-Marquardt algorithm has been adopted and assimilated into the back-propagation learning algorithm for training feed-forward neural networks. The inputs of ANNs are organized in conformity with the results of the observability analysis of synchronous generator dynamic parameters in its dynamic behavior. A collection of ANNs with same inputs but different outputs are developed to determine a set of the dynamic parameters. The ANNs are employed to estimate the dynamic parameters by the measurements which are carried out within each kind of fault separately. The trained ANNs are tested with on-line measurements to identify the dynamic parameters. Simulation studies indicate the ANN observer has a great ability to identify the dynamic parameters of salient-pole synchronous generator. The results also show that the tests which have given better results in estimation of each dynamic parameter can be obtained.

Controlling and modeling power-electronic interface DERs in islanding mode operation micro grid

Distributed energy resources (DERs) such as micro turbine, wind turbine, fuel cell, photovoltaic system and so on, which are high-efficient, high quality and high reliable electrical sources, are been able to create flexible control on power generation during the islanded mode operation of micro grid by power-electronic interface. Performances of two types of inverter controller (PQ controller and VSI controller) show the important role of each model in balancing and power sharing within the islanded network. PQ controller prepares constant active power at specified power factor and VSI controller regulates frequency and voltage through system. This paper is prepared to model two kinds of controller and then investigated the role of controllers through changing load demand and output power of DERs during the islanded network. Moreover appropriate method for handling DERs such as PQ and VSI controller will be proposed in a simulation program which is developed using MATLAB® for one case study. The results are shown and compared in an abbreviated manner.

An Integrated Method for under Frequency Load Shedding Based on Hybrid Intelligent System-Part I: Dynamic Simulation

Security is one of the most vital requirements in the operation of power systems. Frequency is a reliable indicator to determine instability condition in power system, i.e. the stability of power system is closely dependent on the value of system frequency. Under Frequency Load Shedding (UFLS) is one of the most important protection systems as in many cases it is the last action taken to prevent a system blackout after a serious disturbance occurs in power system. The first part of this two part paper presents various factors in modern power systems which have significant contribution on Under Frequency Load Shedding (UFLS). A high-order multi-machine frequency response model is utilized as it the best strategy of power system dynamic simulation. Classification of modern power system components and using an equal unit for each class is proposed in this work. The results show that ANN models can also be implemented as well as a fast dynamic simulator of electric power system. This assessment includes a review of significant researches on power system dynamic simulation and frequency response model leading to an integrated UFLS system design.

Impact of fixed-speed wind turbine farm on radial distribution network

This paper presents the result of development wind farm as unpredictable renewable energy resource in radial distribution network. Wind farm consists of pitched regulated fixed-speed wind turbine which is developed in 24-hour forward-backward sweep load flow analysis. Through load flow analysis, some parameters of network such as voltage profiles, total real power fed of substation and total power loss are calculated for each internal period hour of day. Procedure for capacity allocation of wind farm is determined by both network and wind turbine characteristics for one hourly wind speed for one day. The proposed method is developed for one case-study using MATLAB® software. The results are shown and compared in an abbreviated manner.

LOAD SHEDDING SCHEME IN LARGE PULP MILL BY USING ANALYTIC HIERARCHY PROCESS

Pulp mill is one of the heavy industries that consumes large amount of electricity in its production. In particular, the breakdown of the generator would cause other generators to be overloaded. Thus, load shedding scheme is the best way in handling such condition. Selected load will be shed under this scheme in order to protect the generators from being damaged. In the meantime, the subsequence loads will be shed until the generators are sufficient to provide the power to other loads. In order to determine the sequences of load shedding scheme, analytic hierarchy process (AHP) is introduced. Analytic Hierarchy Process is one of the multi‐criteria decision making methods. By using this method, the priority of the load can be determined. This paper presents the theory of the alternative methods to choose the load priority in load shedding scheme for a large pulp mill.

Automatic classification of single and hybrid power quality disturbances using Wavelet Transform and Modular Probabilistic Neural Network

Power Quality (PQ) monitoring in a systematic and automated way is the important issue to prevent detrimental effects on power system. The development of new methods for the automatic classification of PQ disturbances is at present a major concern. This paper presents a novel approach of automatic detection and classification of single and hybrid PQ disturbances using Discrete Wavelet Transform (DWT) and Modular Probabilistic Neural Network (MPNN). The automatic classification of the PQ disturbances consists of three stages i) data generation, ii) feature extraction and iii) disturbance classification. The data is generated by synthetic models of single and hybrid PQ disturbance signals based on IEEE 1159 standard. DWT with multiresolution analysis was applied for feature extraction from the PQ waveforms. The entropy and energy features extracted from the detail and approximation coefficients were applied as the training and testing data to MPNN in order to accomplish the automatic classification process. The effectiveness of the proposed algorithm has been validated by using a typical real-time underground distribution network in Malaysia which was simulated in PSCAD/EMTDC power system software to generate PQ disturbances. The simulation results show that the classifier has an excellent performance in terms of accuracy and reliability even in the case of PQ signals under noisy condition.

An advanced current control compensation scheme to improve the microgrid power quality without using dedicated compensation devices

For grid-connected inverters (GCI), switching harmonics can be effectively attenuated through some methods. This paper present an advanced current control method for GCI of distributed generators (DGs), which responsible for the DG to controlling the power injection to the grid and the cancellation of the harmonics in Microgrid (MG) and between MG and Power Common Coupling (PCC). The current harmonics in the grid and MG are compensated without using dedicated compensation devices, such as active power filters (APFs), by the proposed current controller which is contain an advanced synchronous reference frame (ASRF) controllers. The merged control methods are proposed for the interface inverter to perform the comprehensive activity of compensating for the harmonics, such as a correction of the system imbalance and the removal of the harmonics. The simulation results are presented to demonstrate the effective performance of the proposed method.

Control of compensation devices by synchronous reference frame and fourier control methods to improve the power quality in a microgrid

The present study used passive filters (PF) and designed Active Power Filters (APFs) with two control methods: synchronous reference frame control and Fourier methods. Studies in the domain of microgrids include distributed generation sources and non-linear loads. Distributed Generation Sources (DGs) include Micro-Turbine (MT) and Fuel Cell (FC), which act as a source of harmonic currents with non-linear loads. To achieve this goal, passive filters are applied to cancel the main harmonics and to provide reactive power, whereas SAPFs are applied to adjust system imbalances and remove the remaining harmonics in the system. The results show that the method can reduce the harmonic disturbances of the system from 24.27% to less than 5%. In addition, this study analyzes how the various control methods operate on active filters. The proposed method has been validated experimentally, and the results are in agreement with the simulation results.