Consideration of Stochastic Variables in Block Layout Optimization.

Abstract

Layout planning has a high impact on both costs and technological risk in the context of chemical plant installation. In the last decades, several models designed to optimize process and block/site layout have emerged. These models still have many deficiencies. Among them, the complexity to consider the surroundings in the block layout, since it evaluates catastrophic accidental events; and, the analysis of major events requires, in general, the performance of a quantitative risk analysis (QRA) demanding the approach of the involved stochastic variables. In this work we intend to develop tools that will be incorporated into a Risk Based Design methodology, reformulating a MILP model to optimize the block layout of a refinery using the Montecarlo method in the realization of the QRA. The objective function considers interconnectivity costs and risk as a constraint.