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A multi-state Markov model for a short-term reliability analysis of a power generating unit

机译：用于发电机组短期可靠性分析的多状态马尔可夫模型

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This paper presents a multi-state Markov model for a coal power generating unit. The paper proposes a technique for the estimation of transition intensities (rates) between the various generating capacity levels of the unit based on field observation. The technique can be applied to such units where output generating capacity is uniformly distributed. In order to estimate the transition intensities a special Markov chain embedded in the observed capacity process was defined. By using this technique, all transition intensities can be estimated from the observed realization of the unit generating capacity stochastic process. The proposed multi-state Markov model was used to calculate important reliability indices such as the Forced Outage Rate (FOR), the Expected Energy Not Supplied (EENS) to consumers, etc. These indices were found for short-time periods (about 100 h). It was shown that these indices are sensibly different from those calculated for a long-term range. Such Markov models could be very useful for power system security analysis and short-term operating decisions.
机译：本文提出了一种用于燃煤发电机组的多状态马尔可夫模型。本文提出了一种基于现场观测来估算机组各种发电量水平之间的转换强度（速率）的技术。该技术可以应用于输出产生能力均匀分布的单元。为了估计过渡强度，定义了一个嵌入到观察到的容量过程中的特殊马尔可夫链。通过使用该技术，可以从观察到的单元发电容量随机过程的实现中估计所有跃迁强度。所提出的多状态马尔可夫模型用于计算重要的可靠性指标，例如强制断电率（FOR），向消费者提供的预期能源未供应量（EENS）等。这些指标是在短期内（大约100小时）发现的）。结果表明，这些指数与长期计算得出的指数明显不同。这样的马尔可夫模型对于电力系统安全分析和短期操作决策可能非常有用。

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