A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit

Demand response (DR) has become a key element in balancing the power grid as contribution of time-varying renewable generation increases. Chemical plants are appealing candidates for DR programs they offer large, concentrated and flexible loads. participation calls frequent production rate changes over time scales that overlap with dominant dynamics plant. Production scheduling should therefore consider process explicitly. We present data-driven approach modelling scheduling-relevant based on historical closed-loop operating data using autoregressive extra inputs (ARX) models. introduce new, linear problem formulation ARX representation, demonstrate its implementation an industrial air separation unit.