Hot water storage tanks play a pivotal role in the transition to low carbon energy systems by increasing energy efficiency and allowing a range of non-conventional intermittent energy sources in the energy mix such as renewable energy and recovered waste heat. Apart from lowering GHG emissions, sizing these systems appropriately can lead to significant reductions in annual energy cost. In the current study, a simple analytical method is developed to optimally size hot water storage tanks using only the system residual heating profile and the following system characteristics:​ the heat source temperature, the load service temperature, the auxiliary energy price, and the tank’s surrounding environmental temperature. A transient numerical model (TRNSYS) of a hot water storage tank system is developed to simulate randomly generated residual heating profiles under 36 distinct scenarios. For each residual heating profile, the optimal storage tank volume is determined by coupling the TRNSYS model to an optimization framework developed in Matlab®. Fast Fourier transform techniques are used to decompose each residual heating profile, and ordinary least-squares regression models are used to relate the residual heating profile’s component amplitudes and periods to the optimal storage volume. Results show that all scenarios with a source temperature of 95 °C, a source to load temperature difference of at least 35 °C, and an auxiliary energy price of at least 0.105 USD/kWh have associated R² values of 0.8 or greater, indicating the proposed sizing method is able to predict the optimal storage tank volume with a high degree of confidence. A case study is presented to demonstrate the proposed sizing method for a hypothetical solar-thermal DHW system in Montréal, Canada.