Batteries will undoubtedly play critical roles in modernizing energy grids, allowing greater penetration of renewable generation and providing services that help grids function. Applying storage technology to grid applications is a business decision that requires potential revenues to be accurately measured to determine economic viability. Using models of storage connected to the California energy grid, we simulate grid-scale applications to estimate such revenues under current market conditions. All calculations are undertaken over two full years of operation of the storage device where a simulation of the grid-connected battery is undertaken so that control and decision are made in real time. Control and decision are made with data available at the time and mimics actual use as it might have happened. The use of a long period of data provides precise estimates as to the values of different applications of the battery. Each simulation results in duty cycles (power profiles) on which the cell-level batteries are tested. We examine the effects of these differing duty cycles on the efficiencies of batteries with various chemsitries. For the first time, we reveal critical tradeoffs between the battery chemistries and the applicability of their energy content, and show that accurate revenue measurement can only be achieved if realistic battery operation in each application is taken into account. The findings in this work could call for a paradigm shift on how the true economic values of energy storage devices could be assessed.