Graph Computing-Based Energy Storage Profit Optimization Considering Market Participant

In modern power systems, energy storage has become increasingly vital. Energy storage balances the temporal and seasonal fluctuations in the power grid, ensuring electricity availability during peak demand and enhancing the system’s reliability during emergencies, such as power outages or unexpected increases in load. However, operating energy storage systems comes with relatively high costs, encompassing the procurement and maintenance of storage devices. This paper introduced a graph model of profit-maximizing energy storage optimization that takes market participation into account. It defined nodes in the physical power grid and optimization computation graph models. The proposed approach included various constraints, such as storage capacity, charging and discharging power limits, and energy exchange balance within the energy storage system’s electrical grid. This methodology enabled swift calculations to attain strategies that maximize energy storage profits by leveraging graph computing.