StoreSmart: Carbon-Aware Energy Storage Control Optimizer

The tool begins by ingesting time-series data including carbon emission factors (in CO₂ intensity per kWh), PV generation forecasts, building demand, and grid electricity rates. These datasets are parsed using custom CSV readers that handle irregular file structures commonly found in exported simulation results or monitoring dashboards.

At its core, the optimizer implements a rule-based strategy to evaluate the environmental impact of each energy transaction. It considers factors such as battery capacity, roundtrip efficiency, depth of discharge, and initial state of charge. The algorithm prioritizes storing energy during periods of low carbon intensity and discharging during periods of high intensity to effectively offset dirtier grid power usage.

StoreSmart simulates system performance over annual profiles, calculating avoided emissions and efficiency gains under different control strategies. Results are visualized through structured output tables and logs that summarize battery usage, emissions reduction, and performance trade-offs.

The modular design allows easy adaptation for future enhancements, such as incorporating time-of-use tariffs, demand charges, or more enhanced predictive machine learning models. By providing an emissions-aware decision framework, StoreSmart supports facility managers, energy consultants, and researchers in designing and testing intelligent storage control strategies aligned with decarbonization goals.