This master’s thesis presents a system for dynamic power management of electric
vehicle charging stations based on the current state of the electrical grid and the consideration of a new grid tariff system. This system is based on 15-minute measurement intervals and five time blocks with different contracted power limits. The main goal of the developed solution is to prevent exceeding these contracted power thresholds.
At the core of the system is an algorithm implemented in the Python programming
language, which processes real-time measurements from the Circutor power meter and, based on the acquired data, controls the charging power of the charging stations. Communication takes place via the Modbus TCP/IP protocol and through API calls. When the algorithm detects that the total consumption is approaching or has exceeded the defined threshold, it automatically triggers a reduction in the power output of the charging stations to limit grid load. The entire system operates on an Axiomtek ICO120 industrial computer, which acts as the central processing unit for managing and coordinating measurements and control actions. The solution is scalable and supports the integration of additional devices or chargers, and can be adapted to different tariff models.
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