445047 Extendible Multi-Objective and Multi-Period Optimization Framework with Monte Carlo Simulation to Manage Industrial Flares during Normal and Abnormal Process Operations

Tuesday, April 12, 2016: 4:30 PM
337A (Hilton Americas - Houston)
Kazi Khoda, Chemical Engineering, Qatar University, Doha, Qatar, Fadwa T. Eljack, Department of Chemical Engineering, Qatar University, Doha, Qatar and Vasiliki Kazantzi, Department of Project Management, Technological Educational Institute of Larissa, Larissa, Greece

In this work, an extendible multi-objective and multi-period optimization framework is presented for the systematic synthesis of energy alternative tools to manage industrial flares during normal and abnormal operations. Flaring is a very common practice across all industrial plants during abnormal situation management. Industrial flaring and its negative impacts on environment, ecosystem and society have gained the attention of researchers, environmentalists and decision makers. It does not only waste potentially valuable source of energy, it also adds significant carbon emissions and other toxic materials to the atmosphere that have been linked to cause diseases in human health and contribute to global warming or several natural disasters. Although, governments and companies have had success in reducing flare gas with significant investments; global gas flaring has remained largely stable the past fifteen years in the range of 140-170 billion cubic meters (BCM) which is 5% of global gas production (Kazi et al.,

2015). Therefore, much attention is still needed to mitigate and manage industrial flares by innovating green process engineering for sustainable energy and environment.

Target of this work is to utilize the surplus energy from industrial flaring to manage waste water treatment facility. In addition, the uncertainty of flaring incidents should be taken into consideration. Thus, it is essential to develop a robust methodology to integrate flare and water management tools with process industries considering the risk factor form uncertain flaring incidents.

The objective of the proposed framework is to reduce the environmental footprint of abnormal flares by enumerating and assessing possible process configurations in order to manage flares from uncertain sources and to utilize unused energy resources for waste water treatment. Following the concept of multi- period optimization approach, the core of this optimization framework is developed using genetic algorithm and Monte Carlo simulation results. Its objective function is aimed at minimizing the total annualized cost which accounts the fixed and operating costs of the system, the value of produced by co- products (i.e., power, waste water treatment savings, income from permeate), and taxes/credits associated with GHGs. An ethylene process plant is used to demonstrate the applicability of the developed framework. The results of different alternative configurations demonstrate the economic, energetic and/or environmental trade-offs of integrating thermal membrane distillation (TMD) and cogeneration (COGEN) unit with the process plant both for flare mitigation and during normal operation.

Kazi, M.-K., Mohammed, F., AlNouss, A. M. N., & Eljack, F. (2015). Multi-objective optimization methodology to size cogeneration systems for managing flares from uncertain sources during abnormal process operations. Computers & Chemical Engineering, 76, 76-86.

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