Simulación de la influencia del STATCOM en las pérdidas del sistema de potencia

The supply of growing electricity demand is possible through continuous technological advances and the expansion of national and international electrical systems. This scenario could introduce voltage drops and consequent changes in the reactive power flow throughout the electrical network. In order to control these problems, various strategies have been developed as a solution to improve the transport and distribution of electrical energy. One of them is the Flexible Alternating Current Transmission System (FACTS), and more specifically the STATic synchronous COMpensator (STATCOM). This paper investigates the influence and effectiveness of STATCOM to mitigate the losses in the transmission lines and its impacts on bus voltage drops. The simulations are performed using the software DIgSILENT PowerFactory and the results showed that STATCOM reduces the power system losses in an interval of 23.86% until 32.86%, and in addition, the STATCOM decreases the annual energy cost by 7.82% in the implemented test case.El abastecimiento de la creciente demanda eléctrica es posible a través de los continuos avances tecnológicos y la expansión de los sistemas eléctricos nacionales e internacionales. Este escenario podría introducir caídas de tensión y los consiguientes cambios en el flujo de potencia reactiva en toda la red eléctrica. Para controlar estos problemas se han desarrollado diversas estrategias como solución para mejorar el transporte y distribución de energía eléctrica. Uno de ellos es el Sistema Flexible de Transmisión de Corriente Alterna (FACTS), y más concretamente el STATic synchronous COMpensator (STATCOM). Este artículo investiga la influencia y efectividad del STATCOM para mitigar las pérdidas en las líneas de transmisión y sus impactos en las caídas de tensión de las barras. Las simulaciones se realizan utilizando el software DIgSILENT PowerFactory y los resultados mostraron que el STATCOM reduce las pérdidas del sistema de potencia en un intervalo de 23,86% hasta 32,86%, y además, el STATCOM disminuye el costo anual de energía en 7,82% en el caso de prueba implementado.

Simulación de la Influencia del STATCOM en las Pérdidas del Sistema de Potencia

The supply of growing electricity demand is possible through continuous technological advances and the expansion of national and international electrical systems. This scenario could introduce voltage drops and consequent changes in the reactive power flow throughout the electrical network. In order to control these problems, various strategies have been developed as a solution to improve the transport and distribution of electrical energy. One of them is the Flexible Alternating Current Transmission System (FACTS), and more specifically the STATic synchronous COMpensator (STATCOM). This paper investigates the influence and effectiveness of STATCOM to mitigate the losses in the transmission lines and its impacts on bus voltage drops. The simulations are performed using the software DIgSILENT PowerFactory and the results showed that STATCOM reduces the power system losses in an interval of 23.86% until 32.86%, and in addition, the STATCOM decreases the annual energy cost by 7.82% in the implemented test case.El abastecimiento de la creciente demanda eléctrica es posible a través de los continuos avances tecnológicos y la expansión de los sistemas eléctricos nacionales e internacionales. Este escenario podría introducir caídas de tensión y los consiguientes cambios en el flujo de potencia reactiva en toda la red eléctrica. Para controlar estos problemas se han desarrollado diversas estrategias como solución para mejorar el transporte y distribución de energía eléctrica. Uno de ellos es el Sistema Flexible de Transmisión de Corriente Alterna (FACTS), y más concretamente el STATic synchronous COMpensator (STATCOM). Este artículo investiga la influencia y efectividad del STATCOM para mitigar las pérdidas en las líneas de transmisión y sus impactos en las caídas de tensión de las barras. Las simulaciones se realizan utilizando el software DIgSILENT PowerFactory y los resultados mostraron que el STATCOM reduce las pérdidas del sistema de potencia en un intervalo de 23,86% hasta 32,86%, y además, el STATCOM disminuye el costo anual de energía en 7,82% en el caso de prueba implementado.

An integrated optimization approach to locate the D-STATCOM in power distribution system to reduce the power loss and total cost

The optimization problem with a single objective can obtain a single solution, called an optimal solution. It maximizes or minimizes the performance of a particular objective function to a given constraint. But, in the case of the multi-objective optimization, different objectives can be simultaneously optimized. Thus, this paper recommends a multi-objective optimization methodology for simultaneously perform the two objective functions such as resizing and optimal placement of Distributed Static Compensator (DSTATCOM) for reducing the power loss, total cost and enhancing the voltage profile. For these purposes, an integrated approach of two optimization algorithm called Multi-objective Ant Colony Optimization (MACO) and Bacterial Foraging Optimization Algorithm (BFOA) are used. The prime intention of this work is to bring down the power loss, total cost and enhance the voltage profile by placing the DSTATCOM device in an optimal location. Here, IEEE-30 and IEEE-69 bus systems are considered to appraise the recital of the recommended approach. Moreover, the effectiveness of the MACO-BFOA approach is evaluated and compared with other multi-objective algorithms. From this analysis, it is observed that when compared to these techniques, the proposed system provides the minimized power loss and total cost

Performance Analysis of Flexible A.C. Transmission System Devices for Stability Improvement of Power System

When large power systems are interconnected by relatively weak tie line, low-frequency oscillations are observed. Recent developments in power electronics have led to the development of the Flexible AC Transmission Systems (FACTS) devices in power systems. FACTS devices are capable of controlling the network condition in a very fast manner and this feature of FACTS can be exploited to improve the stability of a power system. To damp electromechanical oscillations in the power system, the supplementary controller can be applied with FACTS devices to increase the system damping. The supplementary controller is called damping controller. The damping controllers are designed to produce an electrical torque in phase with the speed deviation. The objective of this thesis is to develop some novel control techniques for the FACTS based damping controller design to enhance power system stability. Proper selection of optimization techniques plays an important role in for the stability enhancement of power system. In the present thesis Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Gravitational search algorithm (GSA) along with their hybrid form have been applied and compared for a FACTS based damping controller design. Important conclusions have been drawn on the suitability of optimization technique. The areas of research achieved in this thesis have been divided into two parts: The aim of the first part is to develop the linearized model (Philip-Hefron model) of a single machine infinite bus power system installed with FACTS devices, such as Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC). Different Damping controller structures have been used and compared to mitigate the system damping by adding a component of additional damping torque proportional to speed change through the excitation system. The various soft-computing techniques have been applied in order to find the controller parameters. The recently developed Gravitational Search Algorithm (GSA) based SSSC damping controller, and a new hybrid Genetic Algorithm and Gravitational Search Algorithm (hGA-GSA) based UPFC damping controller seems to the most effective damping controller to mitigate the system oscillation. The aim of second part is to develop the Simulink based model (to over-come the problem associated with the linearized model) for an SMIB as well as the multi-machine power system. Coordinated design of PSS with various FACTS devices based damping controllers are carried out considering appropriate time delays due to sensor time constant and signal transmission delays in the design process. A hybrid Particle Swarm Optimization and Gravitational Search Algorithm (hPSO-GSA) technique is employed to optimally and coordinately tune the PSS and SSSC based controller parameters and has emerged as the most superior method of coordinated controller design considered for both single machine infinite bus power system as well as a multi-machine power system. Finally, the damping capabilities of SSSC based damping controllers are thoroughly investigated by considering a new derived modified signal known as Modified Local Input Signal which comprises both the local signal (speed deviation) and remote signal (line active power). Appropriate time delays due to sensor time constant and signal transmission delays are considered in the design process. The hybrid Particle Swarm Optimization and Gravitational Search Algorithm (hPSO-GSA) technique is used to tune the damping controller parameters. It is observed that the new modified local input signal based SSSC controller provides the best system performance compared to other alternatives considered for a single machine infinite bus power system and multi-machine power system

Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy

Detection of Driver Drowsiness and Distraction Using Computer Vision and Machine Learning Approaches

Drowsiness and distracted driving are leading factor in most car crashes and near-crashes. This research study explores and investigates the applications of both conventional computer vision and deep learning approaches for the detection of drowsiness and distraction in drivers. In the first part of this MPhil research study conventional computer vision approaches was studied to develop a robust drowsiness and distraction system based on yawning detection, head pose detection and eye blinking detection. These algorithms were implemented by using existing human crafted features. Experiments were performed for the detection and classification with small image datasets to evaluate and measure the performance of system. It was observed that the use of human crafted features together with a robust classifier such as SVM gives better performance in comparison to previous approaches. Though, the results were satisfactorily, there are many drawbacks and challenges associated with conventional computer vision approaches, such as definition and extraction of human crafted features, thus making these conventional algorithms to be subjective in nature and less adaptive in practice. In contrast, deep learning approaches automates the feature selection process and can be trained to learn the most discriminative features without any input from human. In the second half of this research study, the use of deep learning approaches for the detection of distracted driving was investigated. It was observed that one of the advantages of the applied methodology and technique for distraction detection includes and illustrates the contribution of CNN enhancement to a better pattern recognition accuracy and its ability to learn features from various regions of a human body simultaneously. The comparison of the performance of four convolutional deep net architectures (AlexNet, ResNet, MobileNet and NASNet) was carried out, investigated triplet training and explored the impact of combining a support vector classifier (SVC) with a trained deep net. The images used in our experiments with the deep nets are from the State Farm Distracted Driver Detection dataset hosted on Kaggle, each of which captures the entire body of a driver. The best results were obtained with the NASNet trained using triplet loss and combined with an SVC. It was observed that one of the advantages of deep learning approaches are their ability to learn discriminative features from various regions of a human body simultaneously. The ability has enabled deep learning approaches to reach accuracy at human level.

Online Control of Modular Active Power Line Conditioner to Improve Performance of Smart Grid

This thesis is explored the detrimental effects of nonlinear loads in distribution systems and investigated the performances of shunt FACTS devices to overcome these problems with the following main contribution: APLC is an advanced shunt active filter which can mitigate the fundamental voltage harmonic of entire network and limit the THDv and individual harmonic distortion of the entire network below 5% and 3%, respectively, as recommended by most standards such as the IEEE-519