Dynamic ramping for demand response of processes and energy systems based on exact linearization

The increasing share of volatile renewable electricity production motivates demand response. Substantial potential for response is offered by flexible processes and their local multi-energy supply systems. Simultaneous optimization schedules can exploit the potential, but leads to numerically challenging problems nonlinear dynamic processes. In this paper, we propose capture process dynamics using ramping constraints. contrast traditional static constraints, constraints are a function state high-order dynamics. We derive rigorously case single-input single-output that exactly input-state linearizable. resulting scheduling problem be efficiently solved as mixed-integer linear program. study, study two reactors system. proper representation allows faster transitions compared thus higher economic benefits proposed approach sufficiently fast application in online optimization. • Dynamic energy Allow dynamics, non-constant ramp limits. Derived from exact linearization. Mixed-integer enough Cost savings close