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Title: | RELIABILITY AND AVAILABILITY EVALUATION OF PATH RI AND CHILLA HYDROPOWER STATIONS BY USING MARKOV MODEL |
Authors: | Shukla, Akash Kumar |
Keywords: | HYDROPOWER STATIONS;MARKOV MODEL;PATH RI AND CHILLA;WATER RESOURCES DEVELOPMENT AND MANAGEMENT |
Issue Date: | 2011 |
Abstract: | The most important reliability indices namely failure rate (X), repair rate (μ), MTTR, MTBF, MTTF are found through data collection and analysis. An evaluation of Markov model is used to obtain unit reliability and availability the operational data of Pathri and Chilla hydropower stations for period 2005 — 2010. The data of each year for each unit is time scheduled. After tabulating all the data, for each unit the different type of failure taking into account the various sub units and systems were classified according to the classification Markov states were defined Failure rate ,repair rate, MTTR, MTTF, MTBF for each state were determined from the classified data. Subsequently availability and reliability were determined. The Markov model can be used for a wide range of reliability problem including systems that are either non-repairable or repairable and are either series-connected, parallel redundant or standby redundant. A Markov process is a stochastic process in which at any given time the subsequent course of the process is affected only by the state at the given time and does not depend on the character of the process at any preceding time. Therefore, the accuracy of predicting the future of our random process is not dependent on any knowledge or the extent of data on the past behavior of the process. Reliability assessment of individual generating stations can highlight the effect of particular configuration and thus provide detailed and comparative information for decision making for scheduling planned maintenance and inventory management. |
URI: | http://hdl.handle.net/123456789/10418 |
Other Identifiers: | M.Tech |
Research Supervisor/ Guide: | Das, Devadutta |
metadata.dc.type: | M.Tech Dessertation |
Appears in Collections: | MASTERS' THESES (WRDM) |
Files in This Item:
File | Description | Size | Format | |
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WRDMG20851.pdf | 4.07 MB | Adobe PDF | View/Open |
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