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A method is developed to generate optimal bid schedules for a hybrid energy storage system participating in both energy and regulation service markets. The hybrid energy storage system includes a fast-response component, such as a flywheel or battery, and a slow response component, such as a pumped-hydro or a conventional generator. This paper describes the objective function and constraints of the cross-market optimization problem. A genetic algorithm is used to solve the problem with a nonlinear penalty curve applied to the energy constraints. A single market optimization method based on priority search is used as a baseline. The results show that the cross-market optimization can improve revenue of the energy storage system by 6.9% over the baseline. Although the method was applied to a hybrid energy storage system, it can be generalized to any energy storage systems.