Towards Net Zero Energy Factory: A multi-objective approach to optimally size and operate industrial flexibility solutions

This study proposes a methodology for sizing and operating new flexibility options within a German carpentry, targeting to be operated as Net Zero Energy Factory (NZEF). A key element of this system is the maximization of the integration of the electric power locally generated by a photovoltaic plant and the electric demand for driving the manufacturing processes. This aim is achieved with a proper integration between design choices in terms flexibility options and optimal control of energy fluxes. In this work, benefits and criticalities arising from the integration of different flexibility options, such as stationary and mobile Energy Storage Systems, are identified and analyzed. A double step optimization process is implemented. First, a Model Predictive Control strategy is used to schedule the manufacturing machines and the energy storage systems (stationary and mobile). Then, a multi-objective optimization aiming at the minimization of annual energy grid exchange and the optimal exploitation of battery capacity is carried out with the Genetic Algorithm. Such a methodology allows the factory operators to optimally size the flexibility capacity (the battery energy storage in this application) needed to operate their industrial facility as a net-zero energy factory. Results show that an optimally controlled stationary energy storage system allows a reduction of energy exchange with the grid up to 53%. The further introduction of electric vehicles increases of about 5% and 67% the renewable energy self-consumption and carbon emissions savings, respectively, ensuring also a significant increase in the yearly annual savings (up to 406%).