Decision-Making Approach Using Fuzzy Logic and Rough Set Theory for Power Quality Monitoring Index of Microgrid

The determination process of the Power Quality Monitoring Index (PQMI) for the microgrid is a complex calculation that considers numerous power quality-related factors like voltage and frequency deviations, power factor, total harmonic distortion (THD), etc. Hence, the ideology of designing an efficient decision-making approach based on a complex set of data and its analysis is a critical issue. Besides, a resourceful decision-making approach has a beneficial effect on the smooth and stable operation of the microgrid system. Thus, in this chapter focusing on the complexity of data handling, data processing, and its dependent decision making, the well-renowned and efficient fuzzy logic and Rough Set Theory (RST) based methodology have been discussed in detail. These methodologies work to display the value of PQMI, and the decision-making approach based on the available data. These methods are verified by analyzing the data set of power quality assessment in a grid-connected/islanded microgrid. From the observations, the fuzzy logic- approach provides the PQMI status in the given range (poor to best). At the same time, the RST method provides a simplified decision based on the indiscernibility of the developed combinations.