scholarly journals Optimization of an On-Grid Inverter for PV Applications Using Genetic Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Anis Ammous ◽  
Abdulrahman Alahdal ◽  
Kaiçar Ammous
Keyword(s):  
Genetic Algorithms ◽  
Current Control ◽  
Output Current ◽  
Active Components ◽  
Nsga Ii ◽  
Hysteresis Current Control ◽  
Design Variables ◽  
Solar Inverter ◽  
Discrete Design Variables ◽  
Conversion Stage

A new approach to the optimal design of power inverters for on-grid photovoltaic systems that uses genetic algorithms (GA) is provided in this article. The nonlinear average model is adopted to model the conversion stage in order to accurately evaluate and quickly estimate the power losses of the power devices. The hysteresis current control that guarantees a quasi-sinusoidal output current is applied to generate the inverter control signals. The design of the solar inverter must meet three contradictory objectives that need to be optimized at the same time. In fact, the aim is to maximize the efficiency of the converter while minimizing its size and price under electrical constraints. The problem variables are the output current ripple and the passive and active components available on the market (IGBTs/MOSFETs, Diodes, Inductors). NSGA-II (Elitist Nondominated Sorting Genetic Algorithm) is appropriate in the case where discrete design variables are used to search for optimal Pareto solutions. It carries out a systematic and efficient search among the developed databases for a set of components which define the optimal structures of the inverter. The introduced method makes the design task easier since the best solutions depend on the components available on the market and significantly reduces the time to market for manufacturers.

Implementation of Coupled Inductor Based 7-level Inverter with Reduced Switches

2017 ◽  
Vol 8 (3) ◽  
pp. 1294 ◽  
Author(s):  
R. Palanisamy ◽  
K. Vijayakumar ◽  
Aishwarya Bagchi ◽  
Vachika Gupta ◽  
Swapnil Sinha
Keyword(s):  
Output Voltage ◽  
Control Algorithm ◽  
Harmonic Distortion ◽  
Current Control ◽  
Output Current ◽  
Hysteresis Current Control ◽  
Common Mode Voltage ◽  
Voltage Stress ◽  
Dsp Controller ◽  
Switching Devices

<p>This paper proposes implementation of coupled inductor based 7 level inverter with reduced number switches. The inverter which generates the sinusoidal output voltage by the use of coupled inductor with reduced total harmonic distortion. The voltage stress on each switching devices, capacitor balancing and common mode voltage can be minimized. The proposed system which gives better controlled output current and improved output voltage with diminished THD value. The switching devices of the system are controlled by using hysteresis current control algorithm by comparing the carrier signals with constant pulses with enclosed hysteresis band value. The simulation and experimental results of the proposed system outputs are verified using matlab/Simulink and TMS320F3825 dsp controller respectively.</p>

scholarly journals An Automated Structural Optimisation Methodology for Scissor Structures Using a Genetic Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Aushim Koumar ◽  
Tine Tysmans ◽  
Rajan Filomeno Coelho ◽  
Niels De Temmerman
Keyword(s):  
Genetic Algorithms ◽  
Search Space ◽  
Optimal Solutions ◽  
Multiobjective Optimisation ◽  
Nsga Ii ◽  
Design Variables ◽  
Depth Analysis ◽  
Making Choices ◽  
Optimisation Methods ◽  
Number Of Individuals

We developed a fully automated multiobjective optimisation framework using genetic algorithms to generate a range of optimal barrel vault scissor structures. Compared to other optimisation methods, genetic algorithms are more robust and efficient when dealing with multiobjective optimisation problems and provide a better view of the search space while reducing the chance to be stuck in a local minimum. The novelty of this work is the application and validation (using metrics) of genetic algorithms for the shape and size optimisation of scissor structures, which has not been done so far for two objectives. We tested the feasibility and capacity of the methodology by optimising a 6 m span barrel vault to weight and compactness and by obtaining optimal solutions in an efficient way using NSGA-II. This paper presents the framework and the results of the case study. The in-depth analysis of the influence of the optimisation variables on the results yields new insights which can help in making choices with regard to the design variables, the constraints, and the number of individuals and generations in order to obtain efficiently a trade-off of optimal solutions.

PARETO BASED MULTI-OBJECTIVE OPTIMIZATION OF SOLAR THERMAL ENERGY STORAGE USING GENETIC ALGORITHMS

2010 ◽  
Vol 34 (3-4) ◽  
pp. 463-474 ◽  
Author(s):  
Abolfazl Khalkhali ◽  
Mohamadhosein Sadafi ◽  
Javad Rezapour ◽  
Hamed Safikhani
Keyword(s):  
Genetic Algorithms ◽  
Solar System ◽  
Geometrical Parameters ◽  
Net Energy ◽  
Solar Thermal Energy ◽  
Nsga Ii ◽  
Multi Objective ◽  
Design Variables ◽  
Conflicting Objectives ◽  
Change Material

Net energy stored (Q net) and the discharge time of Phase Change Material (t PCM) in a solar system, are important conflicting objectives to be optimized simultaneously. In the present paper, multi-objective genetic algorithms (GAs) are used for Pareto approach optimization of a solar system using modified NSGA II algorithms. The competing objectives are Q net and t PCM and design variables are some geometrical parameters of solar system. It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of solar system can be discovered. These important results can be used for better design of a solar system.

Multiobjective optimization of hard coating parameters designing for damping of the bladed disk

2017 ◽  
Vol 232 (9) ◽  
pp. 1609-1619 ◽  
Author(s):  
Yugang Chen ◽  
Jingyu Zhai ◽  
Qingkai Han
Keyword(s):  
Pareto Front ◽  
Engineering Application ◽  
Front Surface ◽  
Model Material ◽  
Superior Performance ◽  
Hard Coating ◽  
Damping Capacity ◽  
Nsga Ii ◽  
Bladed Disk ◽  
Design Variables

In this paper, the damping capacity and the structural influence of the hard coating on the given bladed disk are optimized by the non-dominated sorting genetic algorithm (NSGA-II) coupled with the Kriging surrogate model. Material and geometric parameters of the hard coating are taken as the design variables, and the loss factors, frequency variations and weight gain are considered as the objective functions. Results of the bi-objective optimization are obtained as curved line of Pareto front, and results of the triple-objective optimization are obtained as Pareto front surface with an obvious frontier. The results can give guidance to the designer, which can help to achieve more superior performance of hard coating in engineering application.

Assessment and implementation of an optimized Digital Hysteresis Current Control for a low cost Three-level Boost Rectifier in Metal Industries

2020 ◽  
Author(s):  
Gabriel Vilkn Ramos ◽  
Alex-Sander Amavel Luiz ◽  
Marcelo Martins Stopa ◽  
Marcos Paulo Brito Gomes
Keyword(s):  
Low Cost ◽  
Current Control ◽  
Hysteresis Current Control ◽  
Boost Rectifier

A hysteresis current control method for active power filter with lower switching losses

2011 ◽  
Author(s):  
Jiang Zeng ◽  
Zaitian Zheng ◽  
Andong Lang ◽  
Zhipeng Gu ◽  
Zhicheng Wu ◽  
...  
Keyword(s):  
Control Method ◽  
Active Power Filter ◽  
Active Power ◽  
Current Control ◽  
Hysteresis Current Control ◽  
Power Filter ◽  
Switching Losses
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