Demand Side Management of a Battery-Supported Manufacturing Process with On-Site Generation

Abstract

Due to the global competition in manufacturing, flexibility to provide for individually customized products is considered an important selling point. Constantly changing manufacturing processes face higher production costs than well known reoccurring schedules. To lower these costs in general, we propose a model predictive control concept to reduce manufacturing energy costs in particular, using an existing digital twin to estimate the load of the different manufacturing steps. Based on a mixed integer linear programming formulation of the battery-supported manufacturing process, the system makes optimum use of the on-site photovoltaic generation by production scheduling and adaptive battery control. A simulation study considering a time of use and a real-time pricing scenario provides a proof of concept.