Smart Grid is expected to provide a reliable power supply with fewer and briefer outages, cleaner power, and self-healing power systems, through advanced Power Quality (PQ) monitoring, analysis and diagnosis of the PQ measurements and identification of the root causes, and timely automated controls. It is important to understand that signal processing has been an integral part of advancing and expanding the horizons of this PQ research significantly. The capabilities and applications of signal processing for PQ are continually evolving due to the advanced PQ monitoring devices. Thus, this paper is to present a survey on the proven and emerging signal applications for enhancing PQ, focusing on algorithms for estimating system modal parameters because resonant frequencies and their damping information are critical signatures in evaluating the PQ. In particular, we discuss the need for investigating time-varying and nonlinear characteristics of the modal parameters due to dynamic changes in system operating conditions, and introduce promising signal processing techniques for this purpose.