Managing Uncertain Industrial Flares during Abnormal Process Operations using an Integrated Optimization and Monte Carlo Simulation Approach

Abstract

In this work, an integrated optimization framework with Monte Carlo (MC) simulation techniques is suggested for the systematic synthesis of energy alternative tools, such as cogeneration (COGEN) systems, which can effectively manage industrial flares with uncertain occurrence patterns. The optimization model that was previously developed is now extended to incorporate the risk associated with the uncertain nature of the flaring events that are probabilistically characterized based on empirically meaningful historical samples. The model aims at minimizing the total annualized cost including fixed and operating costs of the system, the value of by- and co-products (i.e., power, excess heat), and regulatory taxes/credits associated with Green House Gases (GHGs). A base case ethylene production plant is presented to illustrate the applicability of the proposed approach and highlight trade-offs between different performance objectives (economic, environmental and energy-related). The results show that some of the examined factors (i.e., CO2 tax savings) can be severely affected by small variations in flaring profiles, whereas others are only slightly affected by such variability (i.e., power vs. heat generation curves, fixed and operating costs). Therefore, the uncertain nature of flaring events may be of high importance in process performance and should be inevitably considered during abnormal situation management. 1 2017 Elsevier B.V.