Reliability analysis of a multi-state wind farm using Markov process

Abstract The usage of wind power is much more popular nowadays although the intermittent nature of wind makes the wind power generation unreliable and stochastic to a large extent. With the uncertainty of wind, the power system planners are faced with a big challenge to design a sound model of power systems. So, reliability estimation of a wind farm has become a great challenge for the researcher. In this article, Markov Reward method has been proposed for developing a realistic model of a wind farm in respect to the wind farm relative availability function. According to the proposed model, the performance of a wind farm has been assessed in terms of different reliability indices. The novelty of this model is that it can be capable of counting any level of power generation made by the wind farm irrespective of failure and success condition reported in the previous literature. A comparison of this study reveals the efficacy of the proposed model over the existing General Markov Reward method. From a case study, the practical validation of this model has been carried out.

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