Abstract

Diverse grid energy storage applications establish varied cost and performance targets for emerging battery technologies. Optimal dispatch models that target specific energy storage applications and incorporate key battery performance characteristics are crucial for evaluating the economic benefits of these promising technologies. For applications such as energy time shifting (ETS), energy arbitrage, and renewable integration, existing economic dispatch models either overlook essential battery dynamics or fail to simplify complex nonlinear constraints, resulting in less realistic and more computationally challenging optimizations. To address this issue, this study proposes an optimal energy dispatch model that aims to maximize operational revenue of a battery energy storage system (BESS) while modeling battery behavior by introducing the simplest equivalent circuit model into the constraints. The model's nonlinear constraints are relaxed into linear representations to formulate a mixed-integer linear programming problem. A case study on ETS in the real-time market demonstrates that the vanadium redox flow and sodium-ion BESSs achieve higher daily revenue than the lithium-ion BESS. Additionally, higher C-rates (the rate at which a battery charges or discharges relative to its capacity) and stronger power capabilities enable these BESSs to cycle more frequently and better capitalize on price differences, thereby generating greater profit. These findings indicate that the proposed model effectively evaluates the economic performance of various battery technologies in an ETS application.