System and method for model predictive energy storage system control

A system for controlling one or more Battery Energy Storage Systems (BESSs), comprising:

• a processor device operatively coupled to a non-transitory computer-readable storage medium, the processor being configured for:
• determining a historical minimum state of charge (SOC) for peak shaving of a previous day based on historical photovoltaic (PV)/load profiles, historical demand charge thresholds (DCT), and battery capacity of the one or more BESSs;
• estimating a minimum SOC for successful peak shaving of a next day by generating a weighted average based on the historical minimum SOC;
• generating optimal charging/discharging profiles for predetermined intervals based on estimated PV/load profiles for a next selected time period and grid feed-in limitations;
• and
• providing continuous optimal charging/discharging functions for the one or more BESSs using a real-time controller configured for overriding the optimal charging/discharging profiles when at least one of a high excess PV generation, a peak shaving event, or a feed-in limit violation is detected.

A non-transitory computer readable storage medium comprising a computer readable program for controlling one or more Battery Energy Storage Systems (BESSs), wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

• determining a historical minimum state of charge (SOC) for peak shaving of a previous day based on historical photovoltaic (PV)/load profiles, historical demand charge thresholds (DCT), and battery capacity of the one or more BESSs;
• estimating a minimum SOC for successful peak shaving of a next day by generating a weighted average based on the historical minimum SOC;
• generating optimal charging/discharging profiles for predetermined intervals based on estimated PV/load profiles for a next selected time period and grid feed-in limitations;
• and
• providing continuous optimal charging/discharging functions for the one or more BESSs using a real-time controller configured for overriding the optimal charging/discharging profiles when at least one of a high excess PV generation, a peak shaving event, or a feed-in limit violation is detected.