Optimal Operation Control for Multiple BESSs of a Large-Scale Customer Under Time-Based Pricing

This paper presents an online optimal operation framework for multiple battery energy storage systems (BESSs) of a large-scale customer under time-based pricing. Many publications have been reported on optimal battery operation techniques but most of them were analyzed in a simulation environment or a specifically designed test bed. However, this paper focuses on implementing the proposed scheme into actual multiple battery storage units and investigating the performance during long-term field operation. The operation framework consists of two levels: optimal scheduling and real-time dispatch. The optimal scheduling is calculated every hour, using a model predictive control based nonlinear optimization model, to minimize the daily electricity usage cost while regulating the peak. The real-time dispatch determines final commands to multiple battery systems by monitoring the system state and checking for any violations of the operation constraints. The two-level control scheme was designed to handle uncertainty in forecast load and estimated state-of-charge levels of batteries. The operation method was applied into the energy management system supervising one lithium-polymer BESS and two lead-acid BESSs of an industrial site. Comprehensive field operation results prove the reliability and effectiveness of the optimal operation framework.