Osama A. Mahgoub

Developed algorithm of maximum power tracking for stand-alone photovoltaic system

The rapid increase in the cost of conventional energy sources leads to the use of nonconventional energy sources. The photovoltaic (PV) is one nonconventional source that is safe, reliable, and environmentally healthy. However, the PV system is expensive and needs a large area to operate. To solve these disadvantages, it is necessary to operate at the maximum power point (MPP) of the array. This article presents a new maximum power tracking algorithm based on the incremental conductance algorithm, which successfully operates even in cases of rapidly changing atmospheric conditions. The developed algorithm depends on the relationship between the load line and the tangent line angles of the I-V characteristic curve. A simulation program was designed to investigate the performance of the developed algorithm using mathematical models for the different system components. The simulation led to a good realization of the algorithm.

Microcontroller-based switch for three-phase transformer inrush current minimization

This paper presents a novel method for the minimization of three-phase transformer inrush current in the case of sustained switching-on operations. First, a simple mathematical model of the three-phase transformer was derived taking the residual flux and the switching-on instant into consideration. A table of optimum switching-on instants corresponding to different residual fluxes was constructed for a specified three-phase transformer. Based on an 8031 microcontroller a controlled-switch was built using the mentioned table. Experimental results using the controlled-switch were obtained and compared with others found by direct switching-on which gave good results.

Simple neuro-controller with a modified error function for a synchronous generator

A simple neuro-controller for a synchronous generator is presented in this paper. The controller consists of a single neuron trained on-line using the back propagation algorithm based on a modified error function. The modified error function uses the controlled variable and its derivatives. Based on the variables used in the modified error function, the controller performs the functions of terminal voltage control and power system stabilizer. Simulation studies for a single-machine and multi-machine power system environment are presented to demonstrate the effectiveness of using the simple neuro-controller.

Improved Active Power Filter Performance Based on an Indirect Current Control Technique

This paper presents a method for the performance improvement of a shunt active power filter (SAPF) using the indirect current control (ICC) scheme. Compared to the conventional direct current control (DCC) scheme, the ICC gives better performance with a lower number of sensors. A simplified and efficient control algorithm using a low cost Intel 80C196KC microcontroller is implemented using only two current sensors for the source current and one voltage sensor for the DC-link voltage of the SAPF circuit. The objective is to eliminate harmonics and to compensate the reactive power produced by non-linear loads such as an uncontrolled rectifier feeding an inductive load. The APF is realized using a three phase voltage source inverter (VSI) with a dc bus capacitor. Experimental results are presented to prove the better performance of the ICC method over the DCC one.

Microprocessor control system for maximum power operation of PV arrays

The proposed PV system consists of four subsystems; the PV array subsystem, the power conditioning subsystem, the control subsystem, and the DC load subsystem. Experimental realization of the proposed system is carried out. The control of the switching duty cycle of the used DC–DC converter is achieved through the 180° algorithm, where a conventional PI controller is used to provide the implemented system with the suitable control action. Experimental results are found to satisfactorily track the MPP of the PV array. Copyright

Studies on a multi-machine power system with a neural network based excitation controller

A feed forward neural network based generating unit excitation controller, its implementation and experimental studies on a single-machine infinite bus system have been reported earlier. The proposed excitation controller integrates the AVR and PSS functions. It is trained on-line from the inputs and outputs of the generator on which it is installed. The error function used for training the neural network by the back propagation algorithm is modified by supplementary signals (speed and acceleration) to provide the stabilizing function. The proposed algorithm has fast convergence rate and high accuracy during on-line training. The performance of the proposed excitation controller to damp multimodal oscillations has been investigated on a five-machine power system without infinite bus. The generating units are connected through a transmission network to form two areas. The model multimachine system configuration is such that it exhibits multi-modal oscillations when subjected to a disturbance. Simulation studies described in the paper show the effectiveness of the proposed integrated controller. It provides a good AVR function of effective terminal voltage control and also damps both the local and inter-area modes of oscillations very effectively.

Experimental verification of a generating unit excitation neuro-controller

A feedforward neural network (FFNN) based excitation neuro-controller (ENC), which integrates the functions of both the AVR and the PSS, has been implemented and experimentally verified on-line on a physical model of a single-machine infinite-bus power system. The FFNN has a simple structure and needs only the terminal voltage and generator speed to be measured. The ENC output signal depends on the on-line training and a modified error function used in training. The performance of the proposed ENC has been investigated by a number of experimental tests for a variety of operating conditions and disturbances.

Generating Unit Excitation Neuro-Controller

Abstract An excitation neuro-controller (ENC) that integrates the automatic voltage regulator (AVR) and the power system stabilizer (PSS) functions using an artificial neural network (ANN) is described in this paper. The input to the controller is the terminal voltage and the output is the field control signal. The PSS action is obtained by using a modified error function that includes speed error and acceleration to update the ENC weights on-line. Simulation studies show that the ENC can provide good dynamic performance for the single-machine infinite-bus system over a wide range of operating conditions.

Simulation Study of a New Approach for Field Weakening Control of PMSM

In this paper, the different techniques for the field weakening, also known as constant power speed range (CPSR) operation, for permanent magnet synchronous motor (PMSM) will be introduced and analysed. Field weakening of PMSM, can be done using either vector control (VC) or conventional phase in advance (CPA). Implementation of these techniques depending on some features and constrains. Most of these features and constrains came from the motor parameters. One of these constrains is the motor inductance which determining whether the motor can be driven in the CPSR or not. A new approach for the field weakening will be discussed and to be verified to overcome this constrain. The new approach will be verified through both techniques VC and CPA.

New techniques for battery charger and SOC estimation in photovoltaic hybrid power systems

Two new techniques of the state of charge (SOC) estimation and battery charger are used to improve the lead-acid battery performance in a photovoltaic (PV) diesel-generator hybrid power system. The ability to estimate the SOC as a control signal is very important for system management and controllers. A new technique for SOC estimation on-line based on the pH meter probe uses is designed and implemented. The charging current must be controlled to avoid the unnecessary overcharging states, so a new battery charger has been designed based on a series pulse width modulation (PWM) switch. The PWM technique is implemented using a microcomputer as a system controller. The two new techniques improve the performance of the battery operation in PV hybrid system, increase the battery lifetime and decrease the maintenance and costs.