| Summary: | 碩士 === 國立中央大學 === 土木工程學系碩士在職專班 === 91 === In this paper, we investigate and study an efficient optimal maintenance- scheduling model of power plants’ generators. In order to provide power enough and stably, we also have to keep an eye on the outline research except online research, because of it will influence the mobilization of power generation system.
In this study, the model is to plan the maintenance- scheduling in two years via consideration of the conditions of spare capacity, area balance, fuel cost, mobility of man-power and machine, the minimum maintenance time. We propose the minimum benefits loss of power system operation as an optimal aim to set up the model, the application of mathematical programming soft (LINGO) is used for demanding the optimal solution, and verifying the reliability of model by testing an example.
In this study, the major contents include present situation of the generators maintenance and maintenance scheduling of TPC power system, composition of programming model, and research of example. In this study, the method of research includes literature search, meeting and discussing with experts, methodology. For literature search, we collect and analyze the problem of maintenance scheduling model of power plants’ generators; for meeting and discussing with experts, we through the meeting and discussing with electric expert and the expert of TPC mobility unit to discuss the problem of present situation of maintenance scheduling of TPC, and define what’s the aim and constrains; In methodology, we analyze the problem structure by mathematical programming, and take the optimal composition concept, to set up the single aim of minimum benefits loss of power system operation, and we write the model formula by Excel and join the LINGO mathematical programming soft to seek for the optimal solution. In this study, we take another kind of concept and hope that the better elastic optimum model could be developed and the plan and correcting of maintenance scheduling could be executed with computer directly. This study could be used for the company which own small quantity of generators, and also could be used for the public company which own big quantity of generators, we hope that this study could be an information for policy makers.
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