نوع مقاله : پژوهشی
نویسندگان
1 دانشکدهی مدیریت، دانشگاه تهران
2 دانشکدهی علوم اجتماعی و اقتصادی، دانشگاه پیام نور
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The problem faced by electric power utilities in developing countries today is that the power demand is increasing rapidly whereas supply growth is constrained by aging generating, transmitting and distributing assets, scarce resources for constructing new ones and other societal issues. This has resulted in the need to construct additional generating plants and for more economic ways to plan and maintain existing electric power transmission and distribution assets.The goal of this study is to improve the average reliability of a system through optimization of its preventive maintenance policy. The evolution of system reliability depends on its structure as well as on the evolution of its components reliability. The latter is a function of component age during a systems operating life. Component aging is strongly affected by maintenance activities performed on the system. We propose a novel methodology for preventive maintenance policy evaluation, based upon a reliability model, which allows the use of flexible intervals between maintenance interventions. Such innovative features represent an advantage over traditional methodologies, as they allow a continuous fitting of the schedules in order to better deal with the components failure rate. Due to the large amount of parameters to be analyzed and their strong and non-linear interdependencies , the search for an optimum combination of these parameters is a very hard task when dealing with optimization schedules. For this reason, use of an ant colony (ACO) algorithm may be an appropriate optimization technique. In order to demonstrate the effectiveness of the proposed method, it is applied to a typical electric power subtransmission substation. By establishing the failure parameters which will be used, the fault tree is made. Analysis of the sample case fault tree resulted in some minimal cut-sets. Then, we proposed probabilistic modeling. Here, the ant colony modeling allows non constant intervals between maintena
کلیدواژهها [English]
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