Multiobjective Optimal Design of Photovoltaic Synchronous Boost Converters Assessing Efficiency, Reliability, and Cost Savings

被引：75

作者：

Adinolfi, Giovanna ^{[2
]}

Graditi, Giorgio ^{[2
]}

Siano, Pierluigi ^{[1
]}

Piccolo, Antonio ^{[1
]}

机构：

[1] Univ Salerno, Dept Ind Engn, I-84084 Fisciano, Italy

[2] Italian Natl Agcy New Technol Energy & Sustainabl, Res Ctr Portici, I-80055 Naples, Italy

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2015年 / 11卷 / 05期

关键词：

Distributed maximum power point tracking (DMPPT) converters; mean time between failure (MTBF); multiobjective optimization; nondominated sorting genetic algorithm (NSGA-II); photovoltaic (PV); switching converters; SMART DISTRIBUTION-SYSTEMS; ENERGY; OPTIMIZATION; INVERTER; NETWORK; MODEL;

D O I：

10.1109/TII.2015.2462805

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1038 / 1048

页数：11

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