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Source publication
Purpose
– This paper aims to focus on the trade-off between losses and converter cost.
Design/methodology/approach
– The continual development of power electronic converters, for a wide range of applications such as renewable energy systems (interfacing photovoltaic panels via power converters), is characterized by the requirements for higher effi...
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Citations
... Once the Pareto diagram is obtained with the best solutions, it is necessary to select the solution that is considered the best according to the case and the conditions of the company. This paper proposes a method to select a solution based on the proximity to origin index (POI), similar to the approach of Mejbri et al. (2014), Jaimes et al. (2009) andDumedah et al. (2010). In this method, a single solution should be selected from the set of points or solutions belonging to the Pareto front, evaluating the proximity of each point to the ideal point, which was defined as the point whose coordinates are the minimum value of each of the models evaluated separately. ...
This article considers the optimisation problem of a multi-objective mass-consumption supply chain network considering cost minimisation and environmental criteria, as well as the analysis of scenarios with variable demand. This study seeks to determine the closure and consolidation of distribution centres and the identification of product flows in the network. The efficiency of the mathematical model has been tested with real information obtained from a Colombian multinational company manufacturing products of mass-consumption. The results confirm the efficiency of the model and its positive impact on determining the environmental impact of gas emissions related to the type of transportation used and the appropriate cost for the case study company.
... The stochastic optimization methods are based on mathematical functions with random variables, which have been used in power electronic system design. A genetic algorithm (GA) and particle swarm optimization (PSO) based constrained optimization framework were presented to understand the trade-off involved in the converter design [18], [19], [20], [21]. The PSO algorithm is notable for its quick convergence rate and simple implementation. ...
Design methodology of power electronics converters is critical to fully explore the potential of wide-bandgap power semiconductors at the converter level. However, existing design methods largely rely on complex mathematical models which significantly increases the computational time, complexity and further leads to problems including poor constraint handling capabilities, inaccurate design, difficult parameter tuning and inadequate problem dimension. These all could generate sub-optimal designs that make the whole design process meaningless. To overcome the aforementioned problems, in this paper, an artificial neural network (ANN)-based multi-objective design approach is proposed, which offers significant advantages in reducing the repetitive usage of complex mathematical models and hence the computational time of design. The computational time was reduced by up to around 78% and 67% compared to the numerical modeling and geometric program (GP) methods as validated through a hardware design process. The proposed method was implemented in MATLAB/Simulink to design a 1 kW single-phase inverter, resulting in a design with an optimized efficiency (98.4%) and power density
$\mathbf {(\mathrm{\text{4.57}~kW/dm^{3}})}$
. The accuracy of the design is verified through experimental prototyping and the measured efficiency and power density are 98.02% and
$\mathrm{\text{4.54}~kW/dm^{3}}$
, respectively, so the errors of efficiency and power density are both less than 1%.
... Once the Pareto diagram is obtained with the best solutions, it is necessary to select the solution that is considered the best according to the case and the conditions of the company. This paper proposes a method to select a solution based on the proximity to origin index (POI), similar to the approach of Mejbri et al. (2014), Jaimes et al. (2009) andDumedah et al. (2010). In this method, a single solution should be selected from the set of points or solutions belonging to the Pareto front, evaluating the proximity of each point to the ideal point, which was defined as the point whose coordinates are the minimum value of each of the models evaluated separately. ...
... The obtained results showed that the best solution is a topology with two boosts converters in cascade. References [7]- [9] set out a design methodology based on the multi-objective genetic algorithm of DC/DC converters for grid-connected PV systems to minimize losses, size and cost. Multi-objective optimization was used to obtain the optimal design of a distributed maximum power point tracking synchronous boost converter in [10]. ...
... The used models are simplified and the behavior of the power electronic converter is mistreated. The control strategy is shortened, even limited to a constant duty cycle for DC/DC converters [6]- [9]. This paper presents a modeling and optimization approach to reveal the optimal design of the DC/AC converter in a grid-connected photovoltaic system using the popular and effective multi-objective algorithm NSGA-II. ...
Power converter optimization by genetic algorithm (GA) is used to provide simpler and more reliable converter design for high efficiency, small size and low cost. This paper presents a Computer-Aided Design Optimization Tool based on GA to determine the optimal structure of single-phase voltage source inverter devoted to grid-connected photovoltaic applications. An accurate non-linear averaged model was used to model the power converter. The hysteresis technique was used to control the output sine wave current of the inverter while the Elitist Non-dominated Sorting Genetic Algorithm NSGA-II was used to search the Pareto optimal front and the best design in terms of efficiency, volume and cost under electrical constraints. The converter model and the NSGA-II algorithm are developed in the MATLAB/Simulink environment. The problem formulation was detailed. It was shown that the optimization of a power converter, working in a given application without the need of tedious and expensive experimental tests classically used to build this converter, is possible by mean of simulation. This will decrease time to market phase for manufacturers.
... Genetic algorithms and Pareto optimality concept starts to be a common solution in the design of electromagnetic devices in the last decade [11][12][13][14][15][16][17][18][19][20][21][22]. The main feature of the GAs is their capability to handle numerous optimization variables and objective functions without losing accuracy in the convergence to the optimum Pareto front. ...
... The selection of the switching frequency and the duty cycle is defined arbitrarily. However, it was shown in the literature that the duty cycle presents a great effect on the core loss and the winding loss [22][23][24][25][26][27][28][29][30][31][32]. The frequency has also an important role in the transformer loss and volume. ...
... These models, which are the modified Steinmetz equation, the generalized Steinmetz equation (GSE), the improved GSE and the improved 2 GSE, are derived from the Steinmetz equation [23][24][25][26][27]. They present some limitations which are explained in [22]. The model given in [22] [Eq. ...
Design and optimization of high-frequency inductive components is a complex task because of the huge number of variables to manipulate, the strong interdependence and the interaction between variables, the nonlinear variation of some design variables as well as the problem nonlinearity. This paper proposes a multi-objective design methodology of a 200-W flyback transformer in continuous conduction mode using genetic algorithms and Pareto optimality concept. The objective is to minimize loss, volume and cost of the transformer. Design variables such as the duty cycle, the winding configuration and the core shape, which have great effects on the former objectives but were neglected in previous works, are considered in this paper. The optimization is performed in discrete research space at different switching frequencies. In total, 24 magnetic materials, 6 core shapes and 2 winding configurations are considered in the database. Accurate volume and cost models are also developed to deal with the optimization in the discrete research space. The bi-objective (loss–volume) and tri-objective (loss–volume–cost) optimization results are presented, and the variations of the design variables are analyzed for the case of 60 kHz. An example of a design (30 kHz) is experimentally verified. The registered efficiency is 88% at full load.
... However, operating the dc/dc converter at higher frequency will result in more switching losses. The optimal switching frequency and other converter parameters were the focus of [4]. To gain these technical and economic benefits in terms of power density and smoother current and voltage with lower ripple; the converter switches should operate at higher frequency to attenuate current and voltage ripples while still gaining better power density. ...
... Design parameters are the parameters which can be altered in order to obtain the objectives [13]. The available variables for this optimization problem are listed in the Table I. ...
... Design parameters are the parameters which can be altered in order to obtain the objectives [13]. The available variables for this optimization problem are listed in the Table I. ...
This paper suggests a design methodology based on the use of Genetic Algorithm (GA) for optimizing a DC/AC converter scheme used for grid-connected photovoltaic system. The converter design is optimized to reach either maximum efficiency, or minimum size, or lowest cost. To achieve such requirements, Genetic Algorithm is used to search optimal design while a non-ideal averaged model is used to model the inverter. A simulation model is developed in MATLAB/Simulink environment for the overall system. The GA is implemented in MATLAB. All optimal results show the features of the modeling and optimization technique.
... In [10] and [18], multiobjective optimization algorithms are used to minimize/maximize PV converter parameters. In detail, the DMPPT boost inductor size and mass are minimized and the energy captured by the PV module is maximized in [10]. ...
Optimal design of switching converters for the integration and optimal exploitation of renewable energy sources (RES) represents a crucial issue often debated in the recent power electronics literature. The design problem required to carry out a multiobjective optimization characterized by simultaneous conflicting objectives, such as efficiency, reliability, and price, where the best compromise solution should be found by the decision maker among Pareto-optimal solutions. In this paper, a novel design method for distributed maximum power point tracking (DMPPT) synchronous boost converter is proposed. The method is based on nondominated sorting genetic algorithm with the aim to obtain the best synchronous rectification (SR) boost topology while considering different targets such as converter efficiency and reliability maximization, as well as converter price minimization. New weighted indices are also proposed for a more realistic characterization of the devices.
... Plusieurs méthodes ont été adoptées pour la conception des systèmes multi-physiques [AlLa08,BrBr07,CTEB11,HaBr03,Hane14,HeBr08,Vivi02,Wu12]. La plupart se basent sur une architecture et un choix technologique prédéfinis grâce à l'expérience du concepteur et ne considèrent l'aspect intégration 3D que tard dans le processus de conception. ...
Les travaux présentés dans cette thèse s’inscrivent dans le cadre de l’électrification des sous-systèmes embarqués notamment pour des véhicules électriques/hybrides. Dans ce domaine, un des objectifs permanents est la réduction des coûts et des délais lors de la conception de chaînes d’actionnement mécatroniques. Pour y parvenir, il est nécessaire de doter le concepteur de méthodologies et d’outils adaptés lui permettant de fiabiliser sa démarche de conception et de lever le maximum de risques avant de réaliser les premiers prototypes. Ces systèmes mécatroniques embarqués mobilisent des briques technologiques essentielles dont fait partie le convertisseur d’électronique de puissance. Les performances de ce système reposent sur la capacité des méthodologies de conception à considérer les contraintes pluridisciplinaires liées à son environnement, l’adéquation des technologies, des topologies et des lois de commandes. Ces travaux de thèse montrent comment nous pouvons répondre à ces exigences et besoins à travers le développement d’une méthodologie de conception multi-physique et multi-niveau de convertisseurs multicellulaires (entrelacés) prédisposés par essence à une reconfiguration aisée. Cette méthodologie, basée sur une optimisation sous contraintes multi-physiques, permet des choix systématiques d’architecture optimale et des technologies de composants à partir d’une base de données constructeurs. Elle intègre l’aspect fiabilité dans la conception dès la phase de pré-dimensionnement au même niveau que les autres contraintes (électriques, rendement, thermiques, encombrement, compatibilité électromagnétique). Afin de bien profiter des avantages de ce type de convertisseurs entrelacés, cette intégration de la fiabilité dans la conception «fiabilisation par conception» est parachevée par l’élaboration d’une architecture de commande tolérante aux défauts «fiabilisation par la commande» permettant, une fois le convertisseur conçu, d’augmenter sa disponibilité par reconfiguration matérielle ou logicielle (loi de commande).
