DocumentCode
1073617
Title
A collaborative operation method between new energy-type dispersed power supply and EDLC
Author
Monai, Toshiharu ; Takano, Ichiro ; Nishikawa, Hisao ; Sawada, Yoshio
Author_Institution
Electr. Eng. & Electron. Dept., Kogakuin Univ., Tokyo, Japan
Volume
19
Issue
3
fYear
2004
Firstpage
590
Lastpage
598
Abstract
In this paper, the modified Euler-type moving average prediction (EMAP) model is proposed to operate a new energy type dispersed power supply system in autonomous mode. This dispersed power supply system consists of a large-scale photovoltaic system (PV) and a fuel cell, as well as an electric double-layer capacitor (EDLC). This system can meet the multi-quality electric power requirements of customers, and ensures voltage stability and uninterruptible power supply function as well. Each subsystem of this distributed power supply contributes to the above-mentioned system performance with its own excellent characteristics. Based on the collaborative operation methods by EMAP model, the required capacity of EDLC to compensate the fluctuation of both PV output and load demand is examined by the simulation using software MATLAB/Simulink, and, response characteristics of this system is confirmed with simulation by software PSIM.
Keywords
capacitors; distributed power generation; fuel cells; large-scale systems; photovoltaic power systems; power engineering computing; power supply quality; voltage regulators; EDLC; Euler-type moving prediction model; Matlab software; Simulink; collaborative operation method; double-layer capacitors; electric double-layer capacitor; energy-type dispersed power supply; fuel cell; large-scale photovoltaic system; multi-quality electric power requirements; voltage stability; Collaboration; Collaborative software; Fuel cells; Large-scale systems; Mathematical model; Photovoltaic systems; Power supplies; Power system modeling; Predictive models; Supercapacitors; Dispersed storage and generation; electric double layer capacitor; fuel cells; photovoltaic cells; prediction methods;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/TEC.2004.827714
Filename
1325299
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