292 research outputs found

    A deterministic agent-based path optimization method by mimicking the spreading of ripples

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    Inspirations from nature have fundamentally contributed to the development of evolutionary computation (EC). This paper, by learning from the natural ripple-spreading phenomenon, proposes a novel ripple-spreading algorithm (RSA) for the path optimization problem (POP). In nature, a ripple spreads at a constant speed in all directions, and the node closest to the source will be the first to be reached. This very simple principle forms the foundation of the proposed RSA. In contrast to most deterministic top-down centralized path optimization methods, such as Dijkstra's algorithm, the RSA is a bottom-up decentralized agent-based simulation model. Moreover, it is distinguished from other agent-based algorithms, such as genetic algorithms and ant colony optimization, by being a deterministic method that can always guarantee the global optimal solution with very good scalability. Here, the RSA is specifically applied to four different POPs. The comparative simulation results presented clearly illustrate the advantages of the RSA in terms of effectiveness and efficiency. Thanks to the combination of both agent-based and deterministic features, the RSA opens new opportunities to attack some problems, such as calculating the exact complete Pareto front in multi-objective optimization and determining the kth shortest project time in project management, which are very difficult, if not impossible, for existing methods to resolve. The ripple-spreading optimization principle, aswell as the new distinguishing features and capacities of RSA, enriches the theoretical foundations of EC

    Multiple Objective Co-Optimization of Switched Reluctance Machine Design and Control

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    This dissertation includes a review of various motor types, a motivation for selecting the switched reluctance motor (SRM) as a focus of this work, a review of SRM design and control optimization methods in literature, a proposed co-optimization approach, and empirical evaluations to validate the models and proposed co-optimization methods. The switched reluctance motor (SRM) was chosen as a focus of research based on its low cost, easy manufacturability, moderate performance and efficiency, and its potential for improvement through advanced design and control optimization. After a review of SRM design and control optimization methods in the literature, it was found that co-optimization of both SRM design and controls is not common, and key areas for improvement in methods for optimizing SRM design and control were identified. Among many things, this includes the need for computationally efficient transient models with the accuracy of FEA simulations and the need for co-optimization of both machine geometry and control methods throughout the entire operation range with multiple objectives such as torque ripple, efficiency, etc. A modeling and optimization framework with multiple stages is proposed that includes robust transient simulators that use mappings from FEA in order to optimize SRM geometry, windings, and control conditions throughout the entire operation region with multiple objectives. These unique methods include the use of particle swarm optimization to determine current profiles for low to moderate speeds and other optimization methods to determine optimal control conditions throughout the entire operation range with consideration of various characteristics and boundary conditions such as voltage and current constraints. This multi-stage optimization process includes down-selections in two previous stages based on performance and operational characteristics at zero and maximum speed. Co-optimization of SRM design and control conditions is demonstrated as a final design is selected based on a fitness function evaluating various operational characteristics including torque ripple and efficiency throughout the torque-speed operation range. The final design was scaled, fabricated, and tested to demonstrate the viability of the proposed framework and co-optimization method. Accuracy of the models was confirmed by comparing simulated and empirical results. Test results from operation at various torques and speeds demonstrates the effectiveness of the optimization approach throughout the entire operating range. Furthermore, test results confirm the feasibility of the proposed torque ripple minimization and efficiency maximization control schemes. A key benefit of the overall proposed approach is that a wide range of machine design parameters and control conditions can be swept, and based on the needs of an application, the designer can select the appropriate geometry, winding, and control approach based on various performance functions that consider torque ripple, efficiency, and other metrics

    Demonstration of High Power Density kW Converters utilizing Wide-Band Gap Devices

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    System level performance and yield optimisation for analogue integrated circuits

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    Advances in silicon technology over the last decade have led to increased integration of analogue and digital functional blocks onto the same single chip. In such a mixed signal environment, the analogue circuits must use the same process technology as their digital neighbours. With reducing transistor sizes, the impact of process variations on analogue design has become prominent and can lead to circuit performance falling below specification and hence reducing the yield.This thesis explores the methodology and algorithms for an analogue integrated circuit automation tool that optimizes performance and yield. The trade-offs between performance and yield are analysed using a combination of an evolutionary algorithm and Monte Carlo simulation. Through the integration of yield parameter into the optimisation process, the trade off between the performance functions can be better treated that able to produce a higher yield. The results obtained from the performance and variation exploration are modelled behaviourally using a Verilog-A language. The model has been verified with transistor level simulation and a silicon prototype.For a large analogue system, the circuit is commonly broken down into its constituent sub-blocks, a process known as hierarchical design. The use of hierarchical-based design and optimisation simplifies the design task and accelerates the design flow by encouraging design reuse.A new approach for system level yield optimisation using a hierarchical-based design is proposed and developed. The approach combines Multi-Objective Bottom Up (MUBU) modelling technique to model the circuit performance and variation and Top Down Constraint Design (TDCD) technique for the complete system level design. The proposed method has been used to design a 7th order low pass filter and a charge pump phase locked loop system. The results have been verified with transistor level simulations and suggest that an accurate system level performance and yield prediction can be achieved with the proposed methodology

    Reliability-Oriented Design and Optimization of Photovoltaic Microinverters

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    Development of a multidisciplinary and optimized design methodology for surface permanent magnets synchronous machines

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    Electric energy is one of the supports of modern civilization. In the actual context, the electrical machines are of capital importance since most of power plants, from nuclear plants to wind turbines, need an electrical machine working as a generator. Moreover, it is estimated that nowadays the 65% of the total energy supplied by the grid is consumed by electric motors working in an industrial environment. Electrical machines are complex systems where a great amount of physical phenomena are produced simultaneously; that is why a proper design requires detailed multidisciplinary models. However, most of the design methodologies and tools are only focused on machine electromagnetic performance in order to achieve power, efficiency and mass to volume ratio goals, performing an adequate more than an optimized design. In the best cases, the features related with other physical domains are taken into account through figures or merit or rules of the thumb based on designer particular experience (e.g. thermal sizing); or even they are treated as an afterthought if needed (typical case of the machine vibro-acoustic performance). These approaches are only suitable for very well-known applications where machine features are perfectly known and characterized. However, these methodologies are unsystematic by nature so they have serious difficulties in order to extrapolate the obtained results to a new set of specifications or to more challenging applications where not only electromagnetic criteria but other physical domains, such as vibro-acoustic, should be taken into account. More precisely, since the advent of neodymium iron boron (NdFeB) magnets, permanent magnets synchronous machines (PMSM) has become a suitable option both in industrial and domestic applications such as aircraft industry, elevation, electric vehicle or power generation. Due to their attractive features (e.g. high efficiency, compactness and power density) PMSMs are an emerging technology and an attractive field of study, as it is highlighted by the great amount of publications devoted to that topic in the last years. Therefore, the thesis main goal is the development of a pioneering PMSM design methodology based on a holistic, multidisciplinary and optimized approach. Moreover, this proposed methodology takes into account not only the electromagnetic and thermal conventional aspects but also the machine vibro-acoustic behaviour. In order to fulfil this aim, a complete multiphysical analytical model has been carried out, including a detailed study of the electromagnetic, thermal and vibro-acoustics PMSM features, paying a special attention to these physical domains interactions. The developed models have been used in order to implement a PMSM design optimized methodology based on an innovative heuristic algorithm labelled Direct Multisearch (DMS). In order to validate the physical models, a 75 kW PMSM prototype (IkerMAQ) has been designed and built. A huge amount of tests were carried out and the analytical models have been exhaustively validated, including electromagnetic, thermal and vibro-acoustic domains

    Multi-level-objective design optimization of permanent magnet synchronous wind generator and solar photovoltaic system for an urban environment application

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    This Ph.D. thesis illustrates a novel study on the analytical and numerical design optimization of radial-flux permanent magnet synchronous wind generators (PMSGs) for small power generation in an urban area, in which an outer rotor topology with a closed-slot stator is employed. The electromagnetic advantages of a double-layer fractional concentration non-overlapping winding configuration are discussed. The analytical behavior of a PMSG is studied in detail; especially for magnetic flux density distribution, time and space harmonics, flux linkages, back-EMF, cogging torque, torque, output power, efficiency, and iron losses computation. The electromagnetic behavior of PMSGs are evaluated when a number of various Halbach array magnetization topologies are presented to maximize the generator’s performance. In addition, the thermal behavior of the PMSG is improved using an innovative natural air-cooling system for rated speed and higher to decrease the machine’s heat mainly at the stator teeth. The analytical investigation is verified via 2-D and 3-D finite element analysis along with a good experimental agreement. Design optimization of electrical machines plays the deterministic role in performance improvements such as the magnetization pattern, output power, and efficiency maximization, as well as losses and material cost minimization. This dissertation proposes a novel multi-objective design optimization technique using a dual-level response surface methodology (D-RSM) and Booth’s algorithm (coupled to a memetic algorithm known as simulated annealing) to maximize the output power and minimize material cost through sizing optimization. Additionally, the efficiency maximization by D-RSM is investigated while the PMSG and drive system are on duty as the whole. It is shown that a better fit is available when utilizing modern design functions such as mixed-resolution central composite (MR-CCD) and mixed-resolution robust (MR-RD), due to controllable and uncontrollable design treatments, and also a Window-Zoom-in approach. The proposed design optimization was verified by an experimental investigation. Additionally, there are several novel studies on vibro-acoustic design optimization of the PMSGs with considering variable speed analysis and natural frequencies using two techniques to minimize the magnetic noise and vibrations. Photovoltaic system design optimization considered of 3-D modeling of an innovative application-oriented urban environment structure, a smart tree for small power generation. The horizon shading is modeled as a broken line superimposed onto the sun path diagram, which can hold any number of height/azimuth points in this original study. The horizon profile is designed for a specific location on the Barcelona coast in Spain and the meteorological data regarding the location of the project was also considered. Furthermore, the input weather data is observed and stored for the whole year (in 2016). These data include, ambient temperature, module’s temperature (open and closed circuits tests), and shading average rate. A novel Pareto-based 3-D analysis was used to identify complete and partial shading of the photovoltaic system. A significant parameter for a photovoltaic (PV) module operation is the nominal operating cell temperature (NOCT). In this research, a glass/glass module has been referenced to the environment based on IEC61215 via a closed-circuit and a resistive load to ensure the module operates at the maximum power point. The proposed technique in this comparative study attempts to minimize the losses in a certain area with improved output energy without compromising the overall efficiency of the system. A Maximum Power Point Track (MPPT) controller is enhanced by utilizing an advanced perturb & observe (P&O) algorithm to maintain the PV operating point at its maximum output under different temperatures and insolation. The most cost-effective design of the PV module is achieved via optimizing installation parameters such as tilt angle, pitch, and shading to improve the energy yield. The variation of un-replicated factorials using a Window-Zoom-in approach is examined to determine the parameter settings and to check the suitability of the design. An experimental investigation was carried out to verify the 3-D shading analysis and NOCT technique for an open-circuit and grid-connected PV module.Esta tesis muestra un novedoso estudio referente al diseño optimizado de forma analítica y numérica de un generador síncrono de imanes permanentes (PMSGs) para una aplicación de microgeneración eólica en un entorno urbano, donde se ha escogido una topología de rotor exterior con un estator de ranuras cerradas. Las ventajas electromagnéticas de los arrollamientos fraccionarios de doble capa, con bobinas concentradas se discuten ampliamente en la parte inicial del diseño del mismo, así como las características de distribución de la inducción, los armónicos espaciales y temporales, la fem generada, el par de cogging así como las características de salida (par, potencia generada, la eficiencia y la distribución y cálculo de las pérdidas en el hierro que son analizadas detalladamente) Posteriormente se evalúan diferentes configuraciones de estructuras de imanes con magnetización Halbach con el fin de maximizar las prestaciones del generador. Adicionalmente se analiza la distribución de temperaturas y su mejora mediante el uso de un novedoso diseño mediante el uso de ventilación natural para velocidades próximas a la nominal y superiores con el fin de disminuir la temperatura de la máquina, principalmente en el diente estatórico. El cálculo analítico se completa mediante simulaciones 2D y 3D utilizando el método de los elementos finitos así como mediante diversas experiencias que validan los modelos y aproximaciones realizadas. Posteriormente se desarrollan algoritmos de optimización aplicados a variables tales como el tipo de magnetización, la potencia de salida, la eficiencia así como la minimización de las pérdidas y el coste de los materiales empleados. En la tesis se proponen un nuevo diseño optimizado basado en una metodología multinivel usando la metodología de superficie de respuesta (D-RSM) y un algoritmo de Booth (maximizando la potencia de salida y minimizando el coste de material empleado) Adicionalmente se investiga la maximización de la eficiencia del generador trabajando conjuntamente con el circuito de salida acoplado. El algoritmo utilizado queda validado mediante la experimentación desarrollada conjuntamente con el mismo. Adicionalmente, se han realizado diversos estudios vibroacústicos trabajando a velocidad variable usando dos técnicas diferentes para reducir el ruido generado y las vibraciones producidas. Posteriormente se considera un sistema fotovoltaico orientado a aplicaciones urbanas que hemos llamado “Smart tree for small power generation” y que consiste en un poste con un generador eólico en la parte superior juntamente con uno o más paneles fotovoltaicos. Este sistema se ha modelado usando metodologías en 3D. Se ha considerado el efecto de las sombras proyectadas por los diversos elementos usando datos meteorológicos y de irradiación solar de la propia ciudad de Barcelona. Usando una metodología basada en un análisis 3D y Pareto se consigue identificar completamente el sistema fotovoltaico; para este sistema se considera la temperatura de la célula fotovoltaica y la carga conectada con el fin de generar un algoritmo de control que permita obtener el punto de trabajo de máxima potencia (MPPT) comprobándose posteriormente el funcionamiento del algoritmo para diversas situaciones de funcionamiento del sistemaLa tesis desenvolupa un nou estudi per al disseny optimitzat, analític i numèric, d’un generador síncron d’imants permanents (PMSGs) per a una aplicació de microgeneració eòlica en aplicacions urbanes, on s’ha escollit una configuració amb rotor exterior i estator amb ranures tancades. Es discuteixen de forma extensa els avantatges electromagnètics dels bobinats fraccionaris de doble capa així com les característiques resultats vers la distribució de les induccions, els harmònics espacials i temporals, la fem generada, el parell de cogging i les característiques de sortida (parell, potencia, eficiència i pèrdues) Tanmateix s’afegeix l’estudi de diferents estructures Halbach per als imants permanents a fi i efecte de maximitzar les característiques del generador. Tot seguit s’analitza la distribució de temperatures i la seva reducció mitjançant la utilització d’una nova metodologia basada en la ventilació natural. Els càlculs analítics es complementen mitjançant anàlisi en 2 i 3 dimensions utilitzant elements finits i diverses experiències que validen els models i aproximacions emprades. Una vegada fixada la geometria inicial es desenvolupen algoritmes d’optimització per a diverses variables (tipus de magnetització dels imants, potencia de sortida, eficiència, minimització de pèrdues i cost dels materials) La tesi planteja una optimització multinivell emprant la metodologia de superfície de resposta i un algoritme de Booth; a més, es realitza la optimització considerant el circuit de sortida. L’algoritme resta validat per la experimentació realitzada. Finalment, s’han considerat diversos estudis vibroacústic treballant a velocitat variable, emprant dues tècniques diferents per a reduir el soroll i les vibracions desenvolupades. Per a finalitzar l’estudi es considera un sistema format per una turbina eòlica instal·lada sobre un pal de llum autònom, els panells fotovoltaics corresponents i el sistema de càrrega. Per a modelitzar l’efecte de l’ombrejat s’ha emprat un model en 3D i les dades del temps i d’irradiació solar de la ciutat de Barcelona. El model s’ha identificat completament i s’ha generat un algoritme de control que considera, a més, l’efecte de la temperatura de la cèl·lula fotovoltaica y la càrrega connectada al sistema per tal d’aconseguir el seguiment del punt de màxima potenciaPostprint (published version

    SALSA: A Formal Hierarchical Optimization Framework for Smart Grid

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    The smart grid, by the integration of advanced control and optimization technologies, provides the traditional grid with an indisputable opportunity to deliver and utilize the electricity more efficiently. Building smart grid applications is a challenging task, which requires a formal modeling, integration, and validation framework for various smart grid domains. The design flow of such applications must adapt to the grid requirements and ensure the security of supply and demand. This dissertation, by proposing a formal framework for customers and operations domains in the smart grid, aims at delivering a smooth way for: i) formalizing their interactions and functionalities, ii) upgrading their components independently, and iii) evaluating their performance quantitatively and qualitatively.The framework follows an event-driven demand response program taking no historical data and forecasting service into account. A scalable neighborhood of prosumers (inside the customers domain), which are equipped with smart appliances, photovoltaics, and battery energy storage systems, are considered. They individually schedule their appliances and sell/purchase their surplus/demand to/from the grid with the purposes of maximizing their comfort and profit at each instant of time. To orchestrate such trade relations, a bilateral multi-issue negotiation approach between a virtual power plant (on behalf of prosumers) and an aggregator (inside the operations domain) in a non-cooperative environment is employed. The aggregator, with the objectives of maximizing its profit and minimizing the grid purchase, intends to match prosumers' supply with demand. As a result, this framework particularly addresses the challenges of: i) scalable and hierarchical load demand scheduling, and ii) the match between the large penetration of renewable energy sources being produced and consumed. It is comprised of two generic multi-objective mixed integer nonlinear programming models for prosumers and the aggregator. These models support different scheduling mechanisms and electricity consumption threshold policies.The effectiveness of the framework is evaluated through various case studies based on economic and environmental assessment metrics. An interactive web service for the framework has also been developed and demonstrated
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