This paper aims to evaluate and characterize the impact of optimizing the operation of the HVAC system through maintaining dynamic CO2-based Demand-Controlled ventilation (DCV) on the electricity load profile and energy consumption of the sports training center of Leibniz University Hannover. The actual ventilation control scheme, in which the operation of the HVAC system is operated with a two-stage volume flow controller based on indoor CO2 concentration is improved through two steps to avoid overventilation and reduce power consumption. For this purpose, a detailed multi-zone model of the sports center and energy supply system has been developed in TRNSYS. In the first step, a multi-stage control scenario is implemented considering the occupancy schedules and indoor CO2 concentration measurement data. In the second step, based on an indoor CO2 concentration model, a predictive control scenario is developed and applied. Aiming at characterizing the influence of these operation scenarios on the power consumption of the building, the annual electricity load profiles of the simulation cases will be analyzed and compared with the actual load profile of the building based on the technical planning documents and data provided by building management system (BMS). Simulation results show that utilizing predictive CO2-based DCV leads to a reduction of the peak load electricity by almost 2 kW and the base load by 5 kW as well as decreasing the annual energy consumption by 40 %
