| Summary: | 博士 === 中原大學 === 電子工程研究所 === 94 === Abstract
Escalating energy costs and the overloaded power plants during peak demand periods are major concerns many industrialized nations have to deal with today. This dissertation discusses the deployment of an Intelligent Dynamic Local Area Power Dispatch System (IDLAPDS) utilizing Radio Frequency (RF) and local Area Network (LAN) technologies consis of Local Power Dispatch Card (LPDC), Local Host System (LHS) and Central Power Dispatch System (CPDS). In this paper, the authors will further discuss on ways to incorporate Artificial Intelligence (AI) ideologies in building a LAPDS that is both more efficient in energy deployment and saving.
In this dissertation, the author consists of the idea of Artificial Intelligence and LAPDS to present the IDLAPDS, which links 'how to disperse power load' and 'how to economize the power effectively'. The main targets of the system is to reduce peak, to shorten sharp from peak load indirectly, to release power developing and power deman, and to dispatch and save the power more effectively.
There are two application cases in this dissertation. An electronic factory that the factory reduced peak load by IDLAPDS for several months. It is not only to drop peak load 21.6%, to reduce sharp, but also to save more than NT$40,000 in September. That is very considerable result, which reduces electric rate by nearly 14% in a month.
Another case, an university is made up by 8500 students and more than 600 lecturers and staffs. There are more than 100 air-conditioning classroom, which are controlled by IDLAPDS to pander to the experiment goal of this research. Author converts the lecturing timetables to the system control parameters. The devices are controlled by LPDCs, and LPDCs transfer the parameters to LHS by using RF to procure for the Intelligence power load dispatch. The system economizes nearly 10% electricity for one week.
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