Power Quality (PQ) analysis is very important in electrical power systems for their effective operation and stability. The connection of power electronic devices, renewable energy sources, and non-linear loads mainly causes the PQ deviation. In this chapter, PQ disturbances were described with their simulation results, such as transients, voltage sags, voltage swells, interruptions, voltage flickers, harmonics, notching, and combined issues. The PQ issues classification approaches and their studies frequently encounter challenges in managing the diverse conditions of present electrical systems. Artificial Intelligence (AI) techniques have dynamic capabilities in PQ classification because they automate pattern identification and correlate with non-linear trends while performing real-time equipment diagnosis. This chapter investigates different power quality problems with their origins and consequences, and also evaluates various AI-based classification approaches by comparing supervised and unsupervised learning models, deep learning methods, and hybrid analytical techniques.