Open AccessLoad Dispatching Control of Multiple-Parallel-Converters Rectifier to Maximize Conversion Efficiency
Author(s) -
Dai Orihara,
Hiroumi Saitoh,
Yuji Higuchi,
Tadatoshi Babasaki
Publication year - 2014
Publication title -
journal of electrical engineering and technology/journal of electrical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.226
H-Index - 27
eISSN - 2093-7423
pISSN - 1975-0102
DOI - 10.5370/jeet.2014.9.3.1132
Subject(s) - converters , rectifier (neural networks) , precision rectifier , control theory (sociology) , computer science , maximization , power (physics) , electronic engineering , engineering , power factor , mathematical optimization , electrical engineering , control (management) , mathematics , voltage , physics , stochastic neural network , quantum mechanics , machine learning , artificial intelligence , recurrent neural network , artificial neural network
In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.