Model-based energy flexibility analysis of a dry room HVAC system in battery cell production

Abstract

Heating, ventilation and air conditioning (HVAC) systems in a production environment ensure a variety of functions, such as providing a pleasant room climate, ensuring defined process conditions and maintaining clean air in the workplace. In fulfilling these functions, they contribute significantly to the overall energy demand in industry. With the rise of fluctuating renewable energies, HVAC systems are interesting in the context of energy flexibility measures to ensure grid stability. In this context, model-based, quantitative analyses are of interest in order to evaluate the effects of energy flexibility measures on the indoor climate or process conditions. In the Battery LabFactory Braunschweig (BLB), research is being conducted on the production of batteries on a laboratory to pilot plant scale. In the BLB the semi-automated cell production takes place in a large drying room, which is supplied by a specially designated HVAC system, which requires more than 70 % of the total energy demand of the BLB. In addition, by using a continuous data acquisition system, the HVAC system records over 90 data points in high temporal resolution. Using a validated physical simulation model of the HVAC system different alternative, energy flexible operating modes can be examined. As alternative modes of operation, a simple rule-based method is compared with a mathematical optimization, which optimizes the overall system in terms of cost and air quality. Mathematical optimization is preferable in terms of the amount of energy potential that can be flexibilized. However, since the optimization involves a higher computational as well as implementation effort and the results of the rule-based method are very similar in terms of cost savings, the rule-based method can also be interesting when the cost-benefit trade-off is taken into account.