Tilt Integral Derivative Controller Optimized by Battle Royale Optimization for Wind Generator Connected to Grid

Globally the countries are focusing on reducing the carbon footprint leading to a greater effort for electrical energy generation by renewable energy sources, particularly wind. The wind turbines are invariably using doubly fed asynchronous generator. In this paper a controller has been designed for a doubly fed induction motor. The proposed Tilt Integral Derivate controller for was compared with commonly used PI, PID controllers. Several optimization algorithms were used for tuning of controllers and the best one was selected for each type of controller. The controller has been optimized using battlefield optimization. It had been compared with proportional integral controller, fractional order proportional integral derivative controller. Other controllers were optimized using meta heuristic algorithms. The controller enhanced the system response in terms of settling time, rise time and other parameters. The Tilt controller gave the overall superior performance in terms of parameters like rise time, settling time, settling minimum, peak, and peak time. The results were obtained using MATLAB. This paper discusses operation of doubly fed induction motor operation and optimization methods

Grey Wolf Optimizer-Based Approaches to Path Planning and Fuzzy Logic-based Tracking Control for Mobile Robots

This paper proposes two applications of Grey Wolf Optimizer (GWO) algorithms to a path planning (PaPl) problem and a Proportional-Integral (PI)-fuzzy controller tuning problem. Both optimization problems solved by GWO algorithms are explained in detail. An off-line GWO-based PaPl approach for Nonholonomic Wheeled Mobile Robots (NWMRs) in static environments is proposed. Once the PaPl problem is solved resulting in the reference trajectory of the robots, the paper also suggests a GWO-based approach to tune cost-effective PI-fuzzy controllers in tracking control problem for NWMRs. The experimental results are demonstrated through simple multiagent settings conducted on the nRobotic platform developed at the Politehnica University of Timisoara, Romania, and they prove both the effectiveness of the two GWO-based approaches and major performance improvement

A Practical Model and an Optimal Controller for Variable Speed Wind Turbine Permanent Magnet Synchronous Generator

The aim of this paper is the complete modeling and simulation of an optimal control system using practical setup parameters for a wind energy conversion system (WECS) through a direct driven permanent magnet synchronous generator (D-PMSG) feeding ac power to the utility grid. The generator is connected to the grid through a back-to-back PWM converter with a switching frequency of 10 KHz. A maximum power point tracking (MPPT) control is proposed to ensure the maximum power capture from wind turbine, and a PI controller designed for the wind turbine to generate optimum speed for the generator via an aerodynamic model. MATLAB/Simulink results demonstrate the accuracy of the developed control scheme

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

Gas turbine control and load sharing of a shipboard power system

The objective of this research is to design a controller for a gas turbine of an Electric Shipboard Power System (ESPS) and to develop a load sharing strategy for its energy management. A suitable model for the gas turbine is selected and the effects of the dynamics are investigated for the different loads of the ESPS. The gas turbine controller is a Proportional Integral Derivative (PID) controller, whose parameters are tuned using the Particle Swarm Optimization (PSO) technique. The load on the system has three components: a propulsion load, a pulsed load to simulate a high energy weapon system and a power supply load for the remaining loads such as pumps, lighting systems, etc. Load sharing is inevitable when demand exceeds the available power supply. In this case, based on the priorities of the loads and the available power, a strategy is presented to supply power to the most critical loads. To illustrate this, a load allocation algorithm is developed using stateflow diagrams. The potential of this algorithm is demonstrated by two case studies performed using the three loads, with the highest priority assigned to the propulsion load in case 1, and power supply load in case 2. The results of this research can be further extended to real time applications

Onduleur quasi-Z-source pour un système de traction de véhicules électriques à sources multiples : contrôle et gestion

Abstract: Power electronics play a fundamental role and help to achieve the new goals of the automobiles in terms of energy economy and environment. The power electronic converters are the key elements which interface their power sources to the drivetrain of the electric vehicle (EV). They contribute to obtaining high efficiency and performance in power systems. However, traditional inverters such as voltage-source, current-source inverters and conventional two-stage inverters present some conceptual limitations. Consequently, many research efforts have been focused on developing new power electronic converters suitable for EVs application. In order to develop and enhance the performance of commercial multiple sources EV, this dissertation aims to select and to control the impedance source inverter and to provide management approaches for multiple sources EV traction system. A concise review of the main existing topologies of impedance source inverters has been presented. That enables to select QZSI (quasi-Z-source inverter) topology as promising architectures with better performance and reliability. The comparative study between the bidirectional conventional two-stage inverter and QZSI for EV applications has been presented. Furthermore, comparative study between different powertrain topologies regarding batteries aging index factors for an off-road EV has been explored. These studies permit to prove that QZSI topology represents a good candidate to be used in multi-source EV system. For improving the performance of QZSI applied to EVs, optimized fractional order PI (FOPI) controllers for QZSI is designed with the ant colony optimization algorithm (ACO-NM) to obtain more suitable aging performance index values for the battery. Moreover, this thesis proposes a hybrid energy storage system (HESS) for EVs to allow an efficient energy use of the battery for a longer distance coverage. Optimized FOPI controller and the finite control set model predictive controller (FCS-MPC) for HESS using bidirectional QZSI is applied for the multi-source EV. The flux-weakening controller has been designed to provide a correct operation with the maximum available torque at any speed within current and voltage limits. Simulation investigations are performed to verify the topologies studied and the efficacity of the proposed controller structure with the bidirectional QZSI. Furthermore, Opal-RT-based real-time simulation has been implemented to validate the effectiveness of the proposed HESS control strategy. The results confirm the EV performance enhancement with the addition of supercapacitors using the proposed control configuration, allowing the efficient use of battery energy with the reduction of root-mean-square value, the mean value, and the standard deviation by 57%, 59%, and 27%, respectively, of battery current compared to the battery-only based inverter.L'électronique de puissance joue un rôle fondamental et contribue à atteindre les nouveaux objectifs de l'automobile en termes d'économie d'énergie et d'environnement. Les convertisseurs d’électroniques de puissance sont considérés comme les éléments clés qui interfacent leurs sources d'alimentation avec la chaîne de traction du véhicule électrique (VE). Ils contribuent à obtenir une efficacité et des performances élevées dans les systèmes électriques. Cependant, les onduleurs traditionnels tels que les onduleurs à source de tension, les onduleurs à source de courant et les onduleurs conventionnels à deux étages qui constituent les onduleurs les plus couramment utilisés, présentent certaines limitations conceptuelles. Par conséquent, de nombreux efforts de recherche se sont concentrés sur le développement de nouveaux convertisseurs d’électroniques de puissance adaptés à l'application aux véhicules électriques. Afin de développer et d'améliorer les performances des VEs à sources multiples commerciales, cette thèse vise à sélectionner, contrôler l'onduleur à source impédante et fournit une approche de gestion pour l'application du système de traction du VE à sources multiples. Une revue concise des principales topologies existantes d'onduleur à source impédante a été présentée. Cela a permis de sélectionner la topologie de l’onduleur quasi-Z-source (QZS) comme architectures prometteuses pouvant être utilisées dans les véhicules électriques, avec de meilleures performances et de fiabilité. L'étude comparative entre l'onduleur bidirectionnel conventionnel à deux étages et de celui à QZS pour les applications du VE a été présentée. En outre, une étude comparative entre différentes topologies de groupes motopropulseurs concernant les facteurs d'indice de vieillissement des batteries pour une application du VE hors route a été explorée. Ces études ont permis de prouver que la topologie de l’onduleur QZS représente une bonne topologie candidate à utiliser dans un système de VE à sources multiples. Pour améliorer les performances de l’onduleur QZS appliquées aux véhicules électriques, des contrôleurs PI d'ordre fractionnaire (PIOF) optimisés pour l’onduleur QZS sont conçus avec l'algorithme de colonies de fourmis afin d'obtenir des valeurs d'indice de performance de vieillissement plus appropriées pour la batterie. De plus, cette thèse propose un système de stockage d'énergie hybride (SSEH) pour le VE afin de permettre une utilisation efficace de l'énergie de la batterie pour une couverture de distance plus longue et une extension de son autonomie. L’optimisation du contrôleur PIOF et du contrôleur par modèle prédictif d'ensemble de contrôle fini (CMP-ECF) pour l’onduleur QZS bidirectionnel a été appliqué au VE à sources multiples avec des approches de gestion appuyées par des règles. Le contrôleur d'affaiblissement de flux magnétique du moteur a été conçu pour fournir un fonctionnement correct avec le couple maximal disponible à n'importe quelle vitesse dans les limites de courant et de tension. Des investigations et des simulations sont effectuées pour vérifier les différentes topologies étudiées et l'efficacité de la structure de contrôleur proposée avec l’onduleur QZS bidirectionnel. De plus, une simulation en temps réel basée sur Opal-RT a été mise en œuvre pour valider l'efficacité de la stratégie de contrôle SSEH proposée. Les résultats confirment l'amélioration des performances du VE avec l'ajout d'un supercondensateur utilisant la configuration du contrôle proposée, permettant une utilisation efficace de l'énergie de la batterie avec une réduction de la valeur moyenne quadratique, de la valeur moyenne et de l'écart type de 57%, 59% et 27%, respectivement, du courant de la batterie par rapport à l'onduleur connecté directement à la batterie