Battery Storage Design AI

Battery energy storage systems (BESS) are increasingly specified for commercial buildings, microgrids, and renewable energy installations. AI optimizes the battery system design by analyzing the building's load profile, utility rate structure, solar generation (if applicable), and resilience requirements to determine the optimal battery capacity and control strategy.

The sizing analysis considers multiple objectives simultaneously: reducing demand charges by peak shaving, storing excess solar generation for evening use, providing backup power for critical loads during outages, and participating in utility demand response programs. AI balances these objectives against the battery cost, available space, and the building's electrical infrastructure capacity.

For buildings with on-site solar, AI optimizes the interaction between the PV system and the battery — determining when to store solar energy, when to export it to the grid, and when to draw from the battery versus the grid. This optimization depends on the utility rate structure (time-of-use rates, demand charges, net metering policies), which varies by jurisdiction and changes over time. AI maintains current rate data and adjusts the control strategy accordingly.