Semi-Markov Reliability Model of Internal Electrical Collection Grid of On-Shore Wind Farm
Robert Adam Sobolewski
AbstractFulfilment of reliability requirements for ‘electrical components’ of wind farm internal collection grid with combination of good wind resources assure the satisfactory performance of a farm. Concerning on-shore farm the feeder section faults lead to the loss of energy served from either all downstream turbines or all turbines in the farm. The failures of protection systems in terms of failures to trip and false tripping increase the incidence and extent the losses of energy served in greater degree as compared to other designs. Achievement of satisfactory performance (in terms of accepted amount of energy not served) in relation to reliability issues, requires the fulfilment of the reliability requirements. They should be obtained relying on quantitative reliability models and take into account: reliability parameters of the components, the topology of collection grid, quality of renewal action and false tripping of protection systems. In the paper the original approach to reliability modeling of on-shore wind farm internal collection grid is presented in details. It relies on semi-Markov model and takes into account the faults and failures of components, the combinations of the components faults and failures that lead to particular number of generators on outage, and the quality of renewal action and false tripping of protective relays. The reliability measure is expected energy not served by farm within specific period of time. The example of reliability model application is presented in details as well.
|Publication size in sheets||0.55|
|Book||Zmojski Wojciech, Mazurkiewicz Jacek, Sugier Jarosław, Walkowiak Tomasz, Kacprzyk Janusz (eds.): Engineering in Dependability of Computer Systems and Networks, Advances in Intelligent Systems and Computing, no. 987, 2020, Springer, ISBN 978-3-030-19500-7, [978-3-030-19501-4], 554 p., DOI:10.1007/978-3-030-19501-4|
|Keywords in English||Wind farm Reliability model Semi-Markov model|
|Internal identifier||ROC 19-20|
|Score||= 40.0, 23-03-2020, ChapterFromConference|
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