Abstract
The power system at present is a complex network that accommodates several applications with diverse requirements. For the stable operation of this network the wide area synchrophasor measurement system (WASMS) has been instituted. The WASMS consists of several measuring devices called the phasor measurement units (PMUs), for collecting the information pertaining to the subtleties of the power grid, which is in the form of time-synchronized phasors measured at various spatial locations in the power system. The synchronization in the time domain is achieved by using the global positioning system timing signals. These synchronized phasors are communicated to the phasor data concentrator where the data is analyzed for detection and control of the power system abnormalities. Reliable performance of the WASMS is quintessential for effective monitoring and subsequent decision-making. Risk assessment of this system prior to its actual deployment would help the power system engineers in the design of fault-tolerant monitoring system. Risk quantifies the severity of failure, and uncertainties in the system parameters pose a major impediment for the accurate determination of the system’s risk. Therefore uncertainty analysis has to be included in the risk assessment framework for obtaining a better estimate. The aim of this book chapter is to present a Monte Carlo simulation (MCS)–based uncertainty analysis and risk assessment of the WASMS. MCS can model simultaneous component failures and is widely used for estimating the failure rates of complex systems. It can also model complex interconnections that are neither series nor parallel. MCS models are presented for the PMU and its communication system. With the uncertainty analysis included in the risk assessment, the WASMS is optimally designed such that the risk is minimized without compromising the system’s observability. Case study results of an Indian power system are presented to elucidate the proposed approach.
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