On a Method to Estimate Worst Case Effectiveness of the System for Process Optimization under Uncertainty

Abstract

At the phase of feasibility study on the system for process optimization, effectiveness of the system is often estimated in terms of a mathematical program formulated from the regional analysis of the operating results. A two-level mathematical programming is presented, which predicts the optimal cost in the worst case caused by the error involved in the process model. In particular, nonlinear inequality constraints of the upper level problem are proposed to give a limit on the acceptable error range. In order to examine the efficiency of the proposed method, a case study on the operation optimizing system of the electric power plant is reported.