ChargeTwin

ChargeTwin is a web + desktop app that simulates EV charging behavior for a specific site (apartment complex, workplace, depot) before spending on chargers, panels, or service upgrades. Users import a simple site layout, electrical constraints, and expected vehicle schedules, then run scenarios: number/type of chargers, load management rules, TOU rates, and demand-charge caps. The simulator outputs queueing risk, peak load, energy costs, and “days to failure” under worst-case arrival patterns. It also generates a plain-English recommendation report for stakeholders and a CSV of hourly load forecasts for utilities/engineers. This is a combination traditional + AI app: traditional for deterministic simulation and constraints, AI for schedule inference from messy spreadsheets, scenario suggestions, and report drafting. It is not a magic optimizer—results are only as good as the inputs, and the app makes uncertainty explicit with ranges and sensitivity analysis.