Developing a PC-based automated monitoring and control platform for electric power systems

被引:17
作者
Yao, AWL [1 ]
Ku, CH [1 ]
机构
[1] Natl Kaohsiung First Univ Sci & Technol, Dept Mech & Automat Engn, Kaohsiung 824, Taiwan
关键词
supervisory control and data acquisition; open modular controller; human-machine interface;
D O I
10.1016/S0378-7796(02)00150-5
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Power companies generally have many different rate schedules and penalty policies for poor-power-factor loads. In order to cut down on electric bills and avoid penalties, companies concern themselves with the efficient use of electricity. In this paper, we present a cost-effective automated monitoring and control electric system (AMCES), based on open modular controllers (OMCs) and a PC-based visual human-machine interface and data acquisition system (HMI/DAS). The AMCES is an intelligent supervisory control and data acquisition (SCADA) platform, which provides economical and user-friendly solutions to electric power facility management. The key aspect of this AMCES platform is its easily accessible flow of information and wiring through network. The OMC provides feasible solutions to the demand control of electricity, using PC-based HMI/DAS, whereby OMCs are optimized for executing data collection and rapid sequential control strategies. Information from this platform can be distributed through an enterprise's Intranet or Internet. Nowadays with the convergence of underlying microprocessor technology and software programming techniques, the hybrid AMCES provides a cost-effective solution to real time control in small- to medium-sized process plants on electric power management. The major purpose of this paper is to demonstrate that OMCs are responsive to rapid and repetitious control tasks. By using PCs that present the flow of information automation and accept operator instructions, it therefore provides the user a tool to monitor and control the use of electric power economically and efficiently. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:129 / 136
页数:8
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