Assessing the applicability of an energy storage system (ESS) based on its duty cycle, i.e., its charge/discharge profile, which represents the demands (associated with a specific application) on an ESS, has attracted great attention in the field of renewable energy. The duty cycle of an ESS is determined and analyzed in this paper. The process of obtaining the duty cycle includes extracting common factors from the ESS operation data using factor analysis, clustering the original fragments using a k-means clustering analysis of the common factors, and constructing typical duty-cycle curves using representative sections of each cluster dataset. The duty cycles of the ESS in schedule output, output smoothness, and schedule and smoothness combination applications, for example, were obtained and analyzed. In a schedule output application, the power ratio of the ESS is the primary characteristic parameter, and each band (high, mid, and low) of the power grade accounts for one third of the duty cycle. The changing rate of the power is the key to the assessment and evaluation of output smoothness. The duty cycle of the schedule and smoothness combination application can be treated as a linear superposition of independent duty cycles. The results showed that a combination of factor analysis and k-means clustering methods can effectively identify and quantify the characteristic parameters of the duty cycle to determine the applicability of the ESS. (C) 2017 Elsevier Ltd. All rights reserved.