The advent of the smart grid requires both reliable, cost-effective energy storage solutions and the ability to accurately and efficiently simulate these systems. Thermocline thermal energy storage, where heat is stored over a temperature gradient, is a promising energy storage technology. However, because of the complexities of thermal stratification, accurate, yet simple models are difficult to identify and generally require complex computational fluid dynamics (CFD) models. In this work, a novel, adaptive-grid one-dimensional model for representing thermocline thermal energy storage systems is presented and validated using experimental data. Compared to standard, fixed-grid one-dimensional models, the adaptive-grid model improves accuracy and decreases the required number of state variables and equations by using a high-resolution grid in the region of thermal stratification and larger, variable-volume, isothermal nodes to represent the ends of the tank. Experimental data shows that the adaptive-grid model is more accurate than other one-dimensional models because it minimizes the effect of numerical diffusion and better predicts system behavior when temperature inversion is introduced into the system. The model presented has applicability in both cold and hot thermal energy storage systems and is advantageous over CFD models when many repeated simulations are required, such as in optimization, control, or prediction of long-term performance. (C) 2013 Elsevier Ltd. All rights reserved.