Simulation-based coyote optimization algorithm to determine gains of PI controller for enhancing the performance of solar PV water-pumping system

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on theCanis latransspecies, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler-Nichols and trial-error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities

Evolution of Controllers for the Speed Control in Thyristor Fed Induction Motor Drive

Induction Motors (IMs) are now becoming the pillar of almost all the motoring applications related to the industry and household. The practical applications of IMs usually require constant motoring speed. As a result, different types of control systems for IM's speed controlling have been shaped. One of the important techniques is the utilization of thyristor fed drive. Although, the thyristor fed induction motor drive (TFIMD) offers stable speed performance, the practical speed control demand is much more precise. Hence, this drive system utilizes additional controllers to attain precise speed for practical applications. This paper offers a detailed review of the controllers utilized with the thyristor fed IM drive in the past few decades to achieve good speed control performance. The clear intent of the paper is to provide a comprehensible frame of the pros and cons of the existing controllers developed for the TFIMD speed control requirements. Keywords: Thyristor Fed Drives, Induction Motors, Speed Controller, Conventional Controllers, and Soft Computing Techniques

Design and Analysis of Electric Powertrains for Offshore Drilling Applications

Doktorgradsavhandling ved Institutt for ingeniørvitenskap, Universitetet i Agder, 2016The global energy market is challenged with an ever increasing need for resources to meet the growing demands for electric power, transportation fuels, etc. Although we witness the expansion of the renewable energy industry, it is still the fossil fuels, with oil and gas dominating the scene of global energy supply sector, that provide majority of worldwide power generation.However, many of the easily accessible hydrocarbon reserves are depleted which requires from the producers of drilling equipment to focus on cost-effective operations and technology to compete in a challenging market. Particularly high level of activity is observed in both industry and academia in the field of electrical actuation systems of drilling machines, as control methods of alternating current (AC) motor drives have become an industrially mature technology over the past few decades. In addition, state-of-the-art AC motors manufacturing processes allow to conform to the strict requirements for safe operation of electrical equipment in explosive atmospheres. These two main reasons made electric actuation systems a tough competitor to hydraulic powertrains used traditionally by the industry. However, optimal design of induction motor drives and systematic analysis of factors associated with operation in harsh offshore conditions are still considered as a major challenge. In this thesis, effective methods for design and analysis of induction motor drives are proposed, including aspects of optimization and simulation-based engineering. The first part of the thesis is devoted to studying methods for modeling, control, and identification of induction machines operating in offshore drilling equipment with the focus to improve their reliability, extend lifetime, and avoid faults and damage, whereas the second part introduces more general approaches to the optimal selection of components of electric drivetrains and to the improvement of the existing dimensioning guidelines. A multidisciplinary approach to design of actuation systems is explored in this thesis by studying the areas of motion control, condition monitoring, and thermal modeling of electric powertrains with an aspiration to reach the level of design sophistication which goes beyond what is currently considered an industrial standard. We present a technique to reproduce operation of a full-scale offshore drilling machine on a scaled-down experimental setup to estimate the mechanical load that the designed powertrain must overcome to meet the specification requirements. The same laboratory setup is used to verify the accuracy of the estimation and control method of an induction motor drive based on the extended Kalman filter (EKF) to confirm that the sensorless control techniques can reduce the number of data acquisition devices in offshore machines, and thus decrease their failure rate without negatively affecting their functionality. To address the challenge of condition monitoring of induction motor drives, we propose a technique to assess the expected lifetime of electric drivetrain components when subjected to the desired duty cycles by comparing the effects of a few popular motion control signals on the cumulative damage and vibrations. As a result, the information about the influence of a given control strategy on drivetrain lifecycle is made available early in the design stage which can significantly affect the choice of the optimal powertrain components. The results show that some of the techniques that have a well-proven track record in other industries can be successfully applied to solve challenges associated with operation of offshore drilling machines. One of the most essential contributions of this thesis, optimal selection of drivetrain components, is based on formulating the drivetrain dimensioning problem as a mixed integer optimization program. The components of powertrain that satisfy the design constraints and are as cost-effective as possible are found to be the global optimum, contrary to the functionality offered by some commercially available drivetrain sizing software products. Another important drawback of the dimensioning procedures recommended by the motor drives manufacturers is the inability to assess if the permissible temperature limits given in the standards do not become violated when the actuation system experiences overloads different than these tabulated in the catalogs. Hence, the second most significant contribution is to propose a method to monitor thermal performance of induction motor drives that is based exclusively on publicly available catalog data and allows for evaluating whether the standard thermal performance limits are violated or not under arbitrary load conditions and at any ambient temperature. Both these solutions can effectively enrich the industrially accepted dimensioning procedures to satisfy the level of conservatism that is demanded by the offshore drilling business but, at the same time, provide improved efficiency and flexibility of the product design process and guarantee optimality (quantitatively, not qualitatively, measurable) of the final solution. An attractive direction for additional development is to further integrate knowledge from different fields relevant to electric powertrains to enable design of tailored solutions without compromising on their cost and performance

Nonlinear Systems

Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in physics and mathematics, as well as in many other fields, as highly correlated nonlinear phenomena, evolving over a large range of time scales and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods. The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects. Potential topics include, but are not limited to: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

An investigation into the utilization of swarm intellingence for the control of the doubly fed induction generator under the influence of symmetrical and assymmetrical voltage dips.

Doctoral Degree. University of KwaZulu-Natal, Durban.The rapid depletion of fossil, fuels, increase in population, and birth of various industries has put a severe strain on conventional electrical power generation systems. It is because of this, that Wind Energy Conversion Systems has recently come under intense investigation. Among all topologies, the Doubly Fed Induction Generator is the preferred choice, owing to its direct grid connection, and variable speed nature. However, this connection has disadvantages. Wind turbines are generally placed in areas where the national grid is weak. In the case of asymmetrical voltage dips, which is a common occurrence near wind farms, the operation of the DFIG is negatively affected. Further, in the case of symmetrical voltage dips, as in the case of a three-phase short circuit, this direct grid connection poses a severe threat to the health and subsequent operation of the machine. Owing to these risks, there has been various approaches which are utilized to mitigate the effect of such occurrences. Considering asymmetrical voltage dips, symmetrical component theory allows for decomposition and subsequent elimination of negative sequence components. The proportional resonant controller, which introduces an infinite gain at synchronous frequency, is another viable option. When approached with the case of symmetrical voltage dips, the crowbar is an established method to expedite the rate of decay of the rotor current and dc link voltage. However, this requires the DFIG to be disconnected from the grid, which is against the rules of recently grid codes. To overcome such, the Linear Quadratic Regulator may be utilized. As evident, there has been various approaches to these issues. However, they all require obtaining of optimized gain values. Whilst these controllers work well, poor optimization of gain quantities may result in sub-optimal performance of the controllers. This work provides an investigation into the utilization of metaheuristic optimization techniques for these purposes. This research focuses on swarm-intelligence, which have proven to provide good results. Various swarm techniques from across the timeline spectrum, beginning from the well-known Particle Swarm Optimization, to the recently proposed African Vultures Optimization Algorithm, have been applied and analysed

Aplicação de controladores fracionários em algoritmos de sincronismo com a rede elétrica

Cada vez mais existe a necessidade de uma transição energética para um modelo mais sustentável, resiliente e descarbonizado devido ao aumento dos preços dos combustíveis fósseis, às mudanças climáticas e à crescente preocupação ambiental. Essa transição implica a passagem de um sistema elétrico sustentado por combustíveis fósseis para um sistema elétrico baseado em energias renováveis. Por sua vez, para ser integrada na rede de distribuição, a energia elétrica descentralizada tem de cumprir determinadas normas e padrões. Estas normas ditam os princípios operacionais básicos, operação da rede de distribuição e resposta do sistema a condições anormais de funcionamento da rede elétrica. Recomendam ainda que a interligação dos recursos com a rede de distribuição deve ocorrer com um fator de potência unitário. Assim, para garantir o funcionamento destes recursos é necessário o uso de algoritmos de sincronização com a rede elétrica. Concretamente, é realizado um estudo comparativo que considera os modelos comummente usados na literatura (Notch-PLL e SOGI-PLL). Nesta dissertação, para mitigar algumas desvantagens associadas a estes algoritmos de sincronismo com a rede são usados controladores fracionários. Estes controladores consistem numa generalização dos controladores clássicos, sendo caraterizados por uma função transferência de ordem fracionária. De modo a determinar os valores dos ganhos de cada controlador, bem como as suas respetivas ordens fracionárias, foi considerado um problema de otimização. Portanto, para resolver este problema diferenciadamente foram selecionados quatro métodos meta-heurísticos: Differential Evolution, Grey Wolf Optimizer, Particle Swarm Optimization e Whale Optimization Algorithm. Para cada destes métodos os resultados obtidos para os ganhos dos controladores foram analisados em função da integral do erro absoluto (IAE). Já para realizar as aproximações das ordens fracionárias foi utilizada a técnica de aproximação Oustaloup. Para avaliar e comparar o desempenho dos controladores clássicos e fracionários nos algoritmos de sincronização com a rede elétrica, os algoritmos usados nesta dissertação foram submetidos a três casos de estudo em ambiente de simulação e ambiente real de operação.There is an increasing need for an energy transition to a more sustainable, resilient, and decarbonized model due to fossil prices, climate change and growing environmental concerns. This transition implies the transition from an electrical system sustained by fossil fuels to an electrical system based on renewable energies. In turn, to be integrated into the distribution grid, decentralized electrical energy must comply with certain norms and standards. These standards dictate the basic operating principles, operation of the distribution grid and the system's response to abnormal operating conditions of the electrical grid. They also recommend that the interconnection of resources with the distribution grid should occur with a unity power factor. Thus, to guarantee the functioning of these resources, it is necessary to use synchronization algorithms with the electrical grid. Specifically, a comparative study is carried out that considers the models commonly used in the literature (Notch-PLL and SOGI-PLL). In this dissertation, to mitigate some disadvantages associated with these network synchronization algorithms, fractional controllers are used. These controllers consist of a generalization of the classical controllers, being characterized by a fractional order transfer function. To determine the gains values of each controller, as well as their respective fractional orders, an optimization problem was considered. Therefore, to solve this problem differently, four metaheuristic methods were selected: Differential Evolution, Gray Wolf Optimizer, Particle Swarm Optimization and Whale Optimization Algorithm. For each of these methods, the results obtained for the controller gains were analysed as a function of the absolute error integral (IAE). To perform the approximations of the fractional orders, the Oustaloup approximation technique was used. To evaluate and compare the performance of classical and fractional controllers in the synchronization algorithms with the electrical grid, the algorithms used in this dissertation were submitted to three case studies in a simulation environment and a real operating environment

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen