(92c) Energy Demand Response of Process Systems through Production Scheduling and Control

As the availability and pricing of electricity vary during the day due to intermittency in renewable resources or real-time electricity tariff policies, the chemical industry, especially those with power-intensive processes, needs to rethink operating strategies to maximize economic viability. The implementation of demand response (DR) strategies, which focuses on demand side activities and has been in the center of all pragmatic energy policy decisions, is the key to minimizing production costs and maximizing profits. However, the dynamic behavior, especially transition trajectories, of the underlying process is seldom taken into account during this task. The purpose of this study is to present a novel optimization formulation for energy demand management in dynamic process systems that takes transition behavior and cost explicitly into account, while simultaneously handling time-sensitive electricity prices. This is accomplished by bringing together production scheduling and transition control through a real-time optimization framework. The dynamic formulation is cast as a mixed-integer nonlinear programming problem and demonstrated using a chemical reactor example where the energy required is assumed to be roughly proportional to the material flow.