The smart grid was initially developed to facilitate communication between operators of the electric power system (such as power generation companies and transmission system operators) and consumers within the distribution network. To implement the smart grid paradigm, time-synchronized measurement devices were developed and introduced into the electric power system. Phasor measurement units (PMUs) and waveform measurement units (WMUs) were created for wide-area transmission networks (at the high-voltage layer), while micro-PMUs were introduced for real-time state estimation in distribution networks (at the low-voltage layer). These time-synchronized measurement devices allow power system operators to monitor the operational status of power generation, transmission, and distribution infrastructure in real time. In particular, data-driven applications utilizing the measurement data can intelligentize and advance the monitoring, operation, and control of the smart grid. The capabilities of digitized high-resolution measurement and time-synchronization are the key factors that enable these contributions to the smart grid. This paper provides an introduction to time-synchronized measurement devices, outlines their specific capabilities, and explores the data-driven applications that can be implemented for advanced smart grid monitoring systems.

Various chemicals are used for semiconductor process. In particular, the most important element in the etching and cleaning process is chemical liquid. An ultrasonic flow meter is used to monitor the supplying amount of chemical solution. If the ultrasonic flow meter contains bubble inside the liquid, measurement cannot be performed or measurement error will be occurred. In this research, the waveform was improved by zero-crossing processing so that the influence on measurement performance is negligible even if the bubble in the chemical solution is included. Consequently, the amplitude of the sound wave is attenuated. Existing flow meters monitor the amplitude value to determine the authenticity of the signal and to filter the noise. The improved method in this study distinguishes noise waves and monitors signal frequency. Flow measurement was carrying out even when the amplitude was resulting only less than 3% of input level volt. The system developed of this study has shown an exact measuring performance compared with the other make’s flow meters.