Reliability Prediction of an innovative Power Quality Meter

Abstract

Power Quality is a fast-growing sector of Instrumentation and Measurements for the electric power industry. A degradation of power quality negatively affects the production capability in many different industrial fields. Loss of production, outages, wasted energy, increases in life cycle cost, and decreases in remaining useful life are some of the main reasons that are leading toward new accurate and reliable power quality meters. In this regard, this paper presents an innovative power quality meter developed to rapidly implement on-board Artificial Intelligence (AI) algorithms in order to rapidly identify different kinds of Power Quality Disturbance (PQD). The proposed meter is a complex device which integrates seven different subunits. Each unit must be designed accurately and must work properly to ensure that the whole meter fulfill its requirements. However, the operating conditions that the proposed power quality meter must endure in industrial applications can negatively affect its performances. Thus, the reliability of the proposed instrument has been studied by means of the reliability prediction method under different operating conditions. The results emphasize the drifts in reliability of the system varying the ambient temperature and the electrical stress percentage of each component.