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The modern power system has undergone a paradigm shift in terms of geographical sprawl through extensive interconnection as well as technological innovations. As a consequence, the wide-area measurement system has evolved to cope with the requirements of efficient operation, monitoring, and control of such a complex system. The phasor measurement unit is the edifice of such a system; therefore, its reliable operation has assumed utmost importance. This has led to recent research focusing on the reliability assessment of phasor measurement units. In order to overcome the difficulties associated with decision making using a single reliability index, as is done in most traditional reliability assessment techniques, the well-being analysis framework has been employed in this article for phasor measurement units. This article presents a methodology using a Markov model in conjunction with event tree analysis to embark upon a set of health indices for phasor measurement units. The most significant contribution of this article is to arrive at three well-being indices for healthy, marginal, and risky states. In addition, the effect of failure rate and repair rate of sensitive components of phasor measurement unit on the well-being indices has been investigated for reliability planning. [ABSTRACT FROM AUTHOR]

Assessment of software reliability has emerged as an area of utmost importance in recent times with the proliferation of software-based systems. Conventional software reliability assessment is done by applying software models that incorporate the unfortunate drawback of requiring previous failure data to formulate the model based on statistical methodologies. But highly dependable software systems used for safety-critical applications, such as computer relays for power system transmission line protection, produce little failure data. This article presents a methodology using statistics of extremes to embark upon software success estimation. The estimate so obtained is an indicator analogous to the conventional reliability index. This estimated reliability is further employed for assessing software's health more effectively by means of well-being analysis. The most significant contribution of this article is to compute the software well-being indices for healthy, marginal, and risky states. A case study for software used in computer relaying of power system transmission line protection validates the efficacy of the proposed methodology, especially for safety-critical applications. [ABSTRACT FROM AUTHOR]

A digital relay can be conceived as a digital signal processor in which the values of line currents and voltages are continuously monitored and processed. Hence, the heart of the digital relay is the software used for implementing the relaying algorithms in an efficient way. Assessment of software reliability is an area of utmost importance for such software-based systems for safety-critical applications such as digital relaying of power transmission lines. But software testing of safety-critical systems is particularly challenging because of the availability of meager failure data. Therefore, this article presents a methodology for estimating software reliability of digital relaying using statistics of extremes. The unique advantages of using such a methodology are the independence of the evaluation of the test sampling order, the amount of available data, and a priori knowledge about the underlying distribution of any parameter. The case studies demonstrate the efficacy of proposed methodology for evaluating the software reliability for digital relaying of transmission lines. [ABSTRACT FROM AUTHOR]