Optimizing the Initial Conditions To Improve the Dynamic Flexibility of Batch Processes

Abstract

It is shown in this paper that by changing the initial operation condition of batch processes, the dynamic performance of the system can be varied largely. The initial operation conditions are often ignored in design of batch processes for flexibility against disturbances or parameter variations. When the initial conditions are not rigid, as in the case of a batch reactor where the initial reaction temperature is quite arbitrary, optimization can also be applied to determine the “best” initial condition to be used. Problems for dynamic flexibility analysis, including initial conditions and process operation, can be formulated as dynamic optimization problems. If the initial conditions are considered, the conditions can be transferred into control variables in the first step of optimization. The solution of the dynamic optimization is based on the Runge-Kutta integration algorithm and decomposition search algorithm. This method, as illustrated and tested with two highly nonlinear chemical engineering problems, enables the optimal solution to be determined.