Estimates of the time-varying standard deviation of the surface EMG signal (EMGσ) are extensively used in the field of EMG-torque estimation. The use of a whitening filter can substantially improve the accuracy of EMGσ estimation by removing the signal correlation and increasing the statistical bandwidth. However, a subject-specific whitening filter which is calibrated to each subject, is quite complex and inconvenient. To solve this problem, we first calibrated a 60th-order “Universal” FIR whitening filter by using the ensemble mean of the inverse of the square root of the power spectral density (PSD) of the noise-free EMG signal. Pre-existing data from elbow contraction of 64 subjects, providing 512 recording trials were used. The test error on an EMG-torque task based on the “Universal” FIR whitening filter had a mean error of 4.80% maximum voluntary contraction (MVC) with a standard deviation of 2.03% MVC. Meanwhile the subject-specific whitening filter had performance of 4.84±1.98% MVC (both have a whitening band limit at 600 Hz). These two methods had no statistical difference. Furthermore, a 2nd-order IIR whitening filter was designed based on the magnitude response of the “Universal” FIR whitening filter, via the differential evolution algorithm. The performance of this IIR whitening filter was very similar to the FIR filter, with a performance of 4.81±2.12% MVC. A statistical test showed that these two methods had no significant difference either. Additionally, a complete theory of EMG in additive measured noise contraction modeling is described. Results show that subtracting the variance of whitened noise by computing the root difference of the square (RDS) is the correct way to remove noise from the EMG signal.

Nowadays modern electric power systems consist of large-scale and highly complex interconnected transmission systems, thus transmission expansion planning (TEP) is now a significant power system optimisation problem. The TEP problem is a large-scale, complex and nonlinear combinatorial problem of mixed integer nature where the number of candidate solutions to be evaluated increases exponentially with system size. The accurate solution of the TEP problem is essential in order to plan power systems in both an economic and efficient manner. Therefore, applied optimisation methods should be sufficiently efficient when solving such problems. In recent years a number of computational techniques have been proposed to solve this efficiency issue. Such methods include algorithms inspired by observations of natural phenomena for solving complex combinatorial optimisation problems. These algorithms have been successfully applied to a wide variety of electrical power system optimisation problems. In recent years differential evolution algorithm (DEA) procedures have been attracting significant attention from the researchers as such procedures have been found to be extremely effective in solving power system optimisation problems. The aim of this research is to develop and apply a novel DEA procedure directly to a DC power flow based model in order to efficiently solve the TEP problem. In this thesis, the TEP problem has been investigated in both static and dynamic form. In addition, two cases of the static TEP problem, with and without generation resizing, have also been investigated. The proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computation time. The analyses have been performed within the mathematical programming environment of MATLAB using both DEA and conventional genetic algorithm (CGA) procedures and a detailed comparison has also been presented. Finally, the sensitivity of DEA control parameters has also been investigated.

The increasing penetration of distributed generation, responsive loads and emerging smart metering technologies will continue the transformation of distribution systems from passive to active network conditions. In such active networks, State Estimation (SE) tools will be essential in order to enable extensive monitoring and enhanced control technologies. In future distribution management systems, the novel electrical power distribution system SE requires development in a scalable manner in order to accommodate small to massive size networks, be operable with limited real time measurements and a restricted time frame. Furthermore, a significant phase of new sensor deployment is inevitable to enable distribution system SE, since present-day distribution networks lack the required level of measurement and instrumentation. In the above context, the research presented in this thesis investigates five SE optimization solution methods with various case studies related to expected scenarios of future distribution networks to determine their suitability. Hachtel's Augmented Matrix method is proposed and developed as potential SE optimizer for distribution systems due to its potential performance characteristics with regard to accuracy and convergence. Differential Evolution Algorithm (DEA) and Overlapping Zone Approach (OZA) are investigated to achieve scalability of SE tools; followed by which the network division based OZA is proposed and developed. An OZA requiring additional measurements is also proposed to provide a feasible solution for voltage estimation at a reduced computation cost. Realising the requirement of additional measurements deployment to enable distribution system SE, the development of a novel meter placement algorithm that provides economical and feasible solutions is demonstrated. The algorithm is strongly focused on reducing the voltage estimation errors and is capable of reducing the error below desired threshold with limited measurements. The scalable SE solution and meter placement algorithm are applied on a multi-processor system in order to examine effective reduction of computation time. Significant improvement in computation time is observed in both cases by dividing the problem into smaller segments. However, it is important to note that enhanced network division reduces computation time further at the cost of accuracy of estimation. Different networks including both idealised (16, 77, 356 and 711 node UKGDS) and real (40 and 43 node EG) distribution network data are used as appropriate to the requirement of the applications throughout this thesis.

Philosophiae Doctor - PhD / Cloud Computing enables users achieve ubiquitous on-demand , and convenient access to a variety of shared computing resources, such as serves network, storage ,applications and more. As a business model, Cloud Computing has been openly welcomed by users and has become one of the research hotspots in the field of information and communication technology. This is because it provides users with on-demand customization and pay-per-use resource acquisition methods.

The aim of this diploma thesis is to survey the area of multiobjective genetic algorithms and cartesian genetic programming. In detail the NSGAII algorithm and integration of multiobjective optimalization into cartesian genetic programming are described. The method of multiobjective CGP was tested on selected problems from the area of digital circuit design.

Feeder reconfiguration is performed by changing the open/close status of two types of switches: normally open tie switches and normally closed sectionalizing switches. A whole feeder or part of a feeder may be served from another feeder by closing a tie switch linking the two while an appropriate sectionalizing switch must be opened to maintain the radial structure of the system. Feeder reconfiguration is mainly aiming to reduce the system overall power losses and improve voltage profile. In this dissertation, several approaches have been proposed to reconfigure the radial distribution networks including the potential impact of integrating Distributed Energy Resources (DER) into the grid. These approaches provide a Fast-Genetic Algorithm “FGA” in which the size and convergence speed is improved compared to the conventional genetic algorithm. The size of the population matrix is also smaller because of the simple way of constructing the meshed network. Additionally, FGA deals with integer variable instead of a binary one, which makes FGA a unique method. The number of the mesh/loop is based on the number of tie switches in a particular network. The validity of the proposed FGA is investigated by comparing the obtained results with the one obtained from the most recent approaches. The second the approach is the implementation of the Differential Evolution (DE) algorithm. DE is a population-based method using three operators including crossover, mutation, and selection. It differs from GA in that genetic algorithms rely on crossover while DE relies on mutation. Mutation is based on the differences between randomly sampled pairs of solutions in the population. DE has three advantages: the ability to find the global optimal result regardless of the initial values, fast convergence, and requirement of a few control parameters. DE is a well-known and straightforward population-based probabilistic approach for comprehensive optimization. In distribution systems, if a utility company has the right to control the location and size of distributed generations, then the location and size of DGs may be determined based on some optimization methods. This research provides a promising approach to finding the optimal size and location of the planned DER units using the proposed DE algorithm. DGs location is obtained using the sensitivity of power losses with respect to real power injection at each bus. Then the most sensitive bus is selected for installing the DG unit. Because the integration of the DG adds positive real power injections, the optimal location is the one with the most negative sensitivity in order to get the largest power loss reduction. Finally, after the location is specified, the proposed Differential Evolution Algorithm (DEA) is used to obtain the optimal size of the DG unit. Only the feasible solutions that satisfy all the constraints are considered. The objective of installing DG units to the distribution network is to reduce the system losses and enhance the network voltage profile. Nowadays, these renewable DGs are required to equip with reactive power devices (such as static VAR compensators, capacitor banks, etc.), to provide reactive power as well as to control the voltage at their terminal bus. DGs have various technical benefits such as voltage profile improvement, relief in feeder loading, power loss minimization, stability improvement, and voltage deviation mitigation. The distributed generation may not achieve its full potential of benefits if placed at any random location in the system. It is necessary to investigate and determine the optimum location and size of the DG. Most distribution networks are radial in nature with limited short-circuit capacity. Therefore, there is a limit to which power can be injected into the distribution network without compromising the power quality and the system stability. This research is aiming to investigate this by applying DG technologies to the grid and keeping the system voltage within a defined boundary [0.95 - 1.05 p.u]. The requirements specified in IEEE Standard 1547 are considered. This research considers four objectives related to minimization of the system power loss, minimization of the deviations of the nodes voltage, minimization of branch current constraint violation, and minimization of feeder’s currents imbalance. The research formulates the problem as a multi-objective problem. The effectiveness of the proposed methods is demonstrated on different revised IEEE test systems including 16 and 33-bus radial distribution system.

This work introduces a brief summary of softcomputing and the solutions to NP-hard problems. It especially deals with evolution algorithms and their basic types. The next part involves the study of cartesian genetic programming, which belongs to the field of evolution algorithms, used mainly in the evolution of digital circuits, symbolic regression, etc. A special chapter is devoted to the studies of new technique Age layered population structure, which deals with the problems of premature convergence, which suggests the way of how the population could be divided into subpopulations split up according to the age criteria. Thanks to the maintaining of sufficient diversity, it achieves substantially better solutions in comparison to the classical evolution algorithms. This papier includes the suggestion of two ways of incorporation of the ALPS technique into CGP. In the next part of work there were carried out tests on the classic problems, that would be solved with evolution algorithms. These tests were made with and without using ALPS technique. In the part of work "Experimental results" there was discussed a contribution of using ALPS technique in CGP against the classic CGP.

Cette thèse s’intéresse à l’étude d’une structure de moteur électrique à aimants permanents afin de réduire l’utilisation d’aimants à basse de terres rares et qui puisse être utilisée pour des applications industrielles. Il est montré dans la première partie de ce travail de recherche que la machine synchro-réluctante à aimants permanents est une bonne solution potentielle. Une analyse paramétrique est alors réalisée en utilisant une modélisation par éléments finis pour mettre en évidence les particularités de son comportement électromagnétique. Puis, une modélisation analytique multi-physique innovante du système convertisseur-moteur est détaillée dans le but de calculer les performances de ce dernier en un temps raisonnable. Les modèles multi-physiques présentés dans ces travaux concernent l’onduleur et le moteur. Ils intègrent les aspects électromagnétique, électrique, énergétique, thermique, mécanique et technico-économique. Le modèle multi-physique de la machine électrique est validé par comparaison à des résultats d’essais sur un prototype. Le modèle du système qui a été développé est ensuite utilisé dans une procédure de conception par optimisation de systèmes d’entrainements. Pour cela, une démarche d’optimisation originale est présentée pour le dimensionnement conjoint de deux applications en imposant la contrainte d’utiliser la même tôlerie magnétique. Il s’agit d’une part d’une application à vitesse fixe et d’autre part d’une application de type traction électrique. La méthode d’optimisation employée est à évolution différentielle. Les résultats des optimisations réalisées permettent de déterminer des conceptions optimales ou des compromis optimaux aux sens de Pareto qui répondent aux deux applications visées. Finalement, cette thèse a permis de positionner la machine synchro-réluctante à aimants permanents parmi les structures de machines à fort potentiel industriel. / This thesis focuses on the study of a structure of permanent magnet electric motor which reduces the amount used of permanent magnets composed of rare earths and which can be used in industrial applications. In the first part of the research work, it is shown that the permanent magnet assisted synchronous reluctance machine is a good alternative. A parametric analyse is realised using a finite element modelling in order to highlight the peculiarities of its electromagnetic behaviour. Then, an innovative multi-physic analytical modelling for the system inverter-motor is detailed in order to evaluate its performances in a reasonable computational time. The multi-physic models presented in this work concern the inverter and motor. They integrate the electromagnetic, electric, energetic, thermal, mechanic, and techno-economic aspects. The multi-physical model of the electric machine is validated by means of tests carried out on a prototype. The model of the system which has been developed is used in a design procedure by optimization of drive systems. For this purpose, an original optimization approach is presented for the simultaneous design of two applications by imposing the constraint of using the same magnetic lamination. On one hand it is an application of fixed speed and on the other hand an application of electric traction. The optimization method used is a type of differential evolution optimization. The results of the optimizations realised determine the optimal designs or the optimal compromise with Pareto front which deal with both applications. Finally, this thesis has placed the permanent magnet assisted synchronous reluctance machine among structures of machines with great industrial potential.

Le travail de recherche présenté s'inscrit pleinement dans les préoccupations énergétiques de la Réunion, en proposant d'évaluer le potentiel de la technologie solaire thermodynamique avec ou sans système à concentration en zone tropicale et les réseaux électriques non interconnectés. Le solaire thermodynamique désigne la production d'électricité à partir du rayonnement solaire via un cycle thermodynamique. En soumettant le cycle thermodynamique à une source « froide » (eau ou air ambiant) et une source « chaude » générée par des capteurs solaires l'on obtient un travail mécanique en sortie de turbine. En couplant la turbine à un alternateur de l'électricité est produite. Utilisation de capteurs à faible ou sans concentration permettent de diminuer le seuil de rentabilité des installations solaires thermodynamiques. Dans ce cas, ce type de technologie n'est plus réservé aux climats désertiques ou méditerranéens. Une étude préliminaire montre qu'elles sont exploitables en zone tropical. De plus, le couplage de l'installation à des systèmes de stockage thermique ou à des installations d'appoint utilisant de la biomasse par exemple permet de produire une énergie électrique de façon continue. Ce projet de recherche à pour but de définir les technologies adéquates, étudier finement les microclimats locaux propices à ces technologies et de réaliser un modèle numérique pour l'étude des conditions d'opération des installations solaires thermodynamiques. Ce projet permettra d'explorer une filière énergétique d'avenir et développer une expertise locale qui contribuera au rayonnement de la Réunion dans la zone océan Indien. / This thesis focuses on the study of the direct solar resource received in Reunion and numerical modeling of a solar power plant consists of: 1 / a field of linear Fresnel collectors in which circulates synthetic oil; 2 / two sensible heat storage tanks; 3 / an organic Rankine cycle. The main goal is to evaluate the performance of such power plant in the island area identified as suitable.To meet this goal, several studies have been conducted: (i) a beam solar radiation map of Reunion was made from satellite images of MeteoSat 7. This map was used to assess the availability of this resource; (ii) a new global-to-diffuse irradiance decomposition model was made from based-ground measurements at Saint-Pierre. This model is based on the representation of higher probabilities of occurrence of the diffuse fraction; (iii) the geometry of the solar collector and beam solar irradiance were modeled from an existing ray-tracing code. This code has been used, firstly, to dimension the collector using an optimization method. And secondly, to develop a fast method in order to simulate absorbed flux distribution on the linear receiver elements; (iv) unsteady-state heat transfers within the solar collector was modeled with a nodal approach; (v) annual electricity production of the power plant running in the south of the island was simulated with a monitoring and control strategy relevant for the demand of the local electricity grid.The models that have been developed during this thesis are design support tools and allow the study of control strategies control of solar power plants with linear Fresnel collector.

Cette thèse s’intéresse à l’étude d’une structure de moteur électrique à aimants permanents afin de réduire l’utilisation d’aimants à basse de terres rares et qui puisse être utilisée pour des applications industrielles. Il est montré dans la première partie de ce travail de recherche que la machine synchro-réluctante à aimants permanents est une bonne solution potentielle. Une analyse paramétrique est alors réalisée en utilisant une modélisation par éléments finis pour mettre en évidence les particularités de son comportement électromagnétique. Puis, une modélisation analytique multi-physique innovante du système convertisseur-moteur est détaillée dans le but de calculer les performances de ce dernier en un temps raisonnable. Les modèles multi-physiques présentés dans ces travaux concernent l’onduleur et le moteur. Ils intègrent les aspects électromagnétique, électrique, énergétique, thermique, mécanique et technico-économique. Le modèle multi-physique de la machine électrique est validé par comparaison à des résultats d’essais sur un prototype. Le modèle du système qui a été développé est ensuite utilisé dans une procédure de conception par optimisation de systèmes d’entrainements. Pour cela, une démarche d’optimisation originale est présentée pour le dimensionnement conjoint de deux applications en imposant la contrainte d’utiliser la même tôlerie magnétique. Il s’agit d’une part d’une application à vitesse fixe et d’autre part d’une application de type traction électrique. La méthode d’optimisation employée est à évolution différentielle. Les résultats des optimisations réalisées permettent de déterminer des conceptions optimales ou des compromis optimaux aux sens de Pareto qui répondent aux deux applications visées. Finalement, cette thèse a permis de positionner la machine synchro-réluctante à aimants permanents parmi les structures de machines à fort potentiel industriel. / This thesis focuses on the study of a structure of permanent magnet electric motor which reduces the amount used of permanent magnets composed of rare earths and which can be used in industrial applications. In the first part of the research work, it is shown that the permanent magnet assisted synchronous reluctance machine is a good alternative. A parametric analyse is realised using a finite element modelling in order to highlight the peculiarities of its electromagnetic behaviour. Then, an innovative multi-physic analytical modelling for the system inverter-motor is detailed in order to evaluate its performances in a reasonable computational time. The multi-physic models presented in this work concern the inverter and motor. They integrate the electromagnetic, electric, energetic, thermal, mechanic, and techno-economic aspects. The multi-physical model of the electric machine is validated by means of tests carried out on a prototype. The model of the system which has been developed is used in a design procedure by optimization of drive systems. For this purpose, an original optimization approach is presented for the simultaneous design of two applications by imposing the constraint of using the same magnetic lamination. On one hand it is an application of fixed speed and on the other hand an application of electric traction. The optimization method used is a type of differential evolution optimization. The results of the optimizations realised determine the optimal designs or the optimal compromise with Pareto front which deal with both applications. Finally, this thesis has placed the permanent magnet assisted synchronous reluctance machine among structures of machines with great industrial potential.