This paper presents an evaluation tool for demand-side management of domestic hot water systems in distribution systems. The tool accurately models and predicts potential peak demand reductions through direct load control of domestic hot water systems. It employs a unique multi-layer thermally stratified hot water cylinder model and Monte Carlo simulations to generate hot water load profiles of domestic customers. To meet peak reduction targets set by the tool user, switching programs found via iterative optimizations are applied to hot water systems. The structure and individual components of the tool are described, and case studies are presented. Impacts of different switching programs on customer’s comfort are evaluated and discussed.