Evaluation of Power Management Control on the Supercomputer Fugaku

2020 ◽  
Author(s):  
Yuetsu Kodama ◽  
Tetsuya Odajima ◽  
Eishi Arima ◽  
Mitsuhisa Sato
Keyword(s):  
Power Management ◽  
Management Control

scholarly journals Bidirectional Power Sharing for DC Microgrid Enabled by Dual Active Bridge DC-DC Converter

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 404
Author(s):  
Sara J. Ríos ◽  
Daniel J. Pagano ◽  
Kevin E. Lucas
Keyword(s):  
Power Management ◽  
Distribution Systems ◽  
Control Method ◽  
Dynamic Performance ◽  
Management Control ◽  
Photovoltaic System ◽  
Dc Microgrid ◽  
Dual Active Bridge ◽  
Control Scheme ◽  
Bidirectional Power Flow

Currently, high-performance power conversion requirements are of increasing interest in microgrid applications. In fact, isolated bidirectional dc-dc converters are widely used in modern dc distribution systems. The dual active bridge (DAB) dc-dc converter is identified as one of the most promising converter topology for the mentioned applications, due to its benefits of high power density, electrical isolation, bidirectional power flow, zero-voltage switching, and symmetrical structure. This study presents a power management control scheme in order to ensure the power balance of a dc microgrid in stand-alone operation, where the renewable energy source (RES) and the battery energy storage (BES) unit are interfaced by DAB converters. The power management algorithm, as introduced in this work, selects the proper operation of the RES system and BES system, based on load/generation power and state-of-charge of the battery conditions. Moreover, a nonlinear robust control strategy is proposed when the DAB converters are in voltage-mode-control in order to enhance the dynamic performance and robustness of the common dc-bus voltage, in addition to overcoming the instability problems that are caused by constant power loads and the dynamic interactions of power electronic converters. The simulation platform is developed in MATLAB/Simulink, where a photovoltaic system and battery system are selected as the typical RES and BES, respectively. Assessments on the performance of the proposed control scheme are conducted. Comparisons with the other control method are also provided.

scholarly journals Shipboard Power Management for Failure Mode Using the Hybrid MPC Approach

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2915
Author(s):  
Xiuyan Peng ◽  
Bo Wang ◽  
Lanyong Zhang ◽  
Peng Su
Keyword(s):  
Model Predictive Control ◽  
Power Systems ◽  
Power Management ◽  
Failure Mode ◽  
Hybrid Model ◽  
Predictive Control ◽  
Minimum Principle ◽  
Management Control ◽  
Shipboard Power ◽  
Two Stages

Shipboard integrated power systems, the key technology of ship electrification, call for effective failure mode power management control strategy to achieve the safe and reliable operation in dynamic reconfiguration. Considering switch reconfiguration with system dynamics and power balance restoration after reconfiguration, in this paper, the optimization objective function of optimal management for ship failure mode is established as a hybrid model predictive control problem from the perspective of hybrid system. To meet the needs for fast computation, a hierarchical hybrid model predictive control algorithm is proposed, which divides the original optimization problem into two stages, and reduces the computation complexity by relaxing constraints and the minimum principle. By applying to a real-time simulator in two scenarios, the results verify the effectivity of the proposed method.

scholarly journals Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qunzhang Tu ◽  
Xiaochen Zhang ◽  
Ming Pan ◽  
Chengming Jiang ◽  
Jinhong Xue
Keyword(s):  
Power Management ◽  
Electric Drive ◽  
Fuel Economy ◽  
Control Strategy ◽  
Fuzzy Controller ◽  
Management Control ◽  
Drive System ◽  
Tracked Vehicles ◽  
Hybrid Particle Swarm Optimization ◽  
Electric Drive System

This article studies the power management control strategy of electric drive system and, in particular, improves the fuel economy for electric drive tracked vehicles. Combined with theoretical analysis and experimental data, real-time control oriented models of electric drive system are established. Taking into account the workloads of engine and the SOC (state of charge) of battery, a fuzzy logic based power management control strategy is proposed. In order to achieve a further improvement in fuel economic, a DEHPSO algorithm (differential evolution based hybrid particle swarm optimization) is adopted to optimize the membership functions of fuzzy controller. Finally, to verify the validity of control strategy, a HILS (hardware-in-the-loop simulation) platform is built based on dSPACE and related experiments are carried out. The results indicate that the proposed strategy obtained good effects on power management, which achieves high working efficiency and power output capacity. Optimized by DEHPSO algorithm, fuel consumption of the system is decreased by 4.88% and the fuel economy is obviously improved, which will offer an effective way to improve integrated performance of electric drive tracked vehicles.

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