Characterization of Industrial Flaring under Uncertainty for the Design of Optimum Flare Recovery and Utilization Systems

One of the main challenges in industrial applications is to optimally manage flare gases that are inevitably generated both in routine and non-routine process operations but can yet constitute valuable energy resources for process systems. A main challenge is to explore the best possible strategies for exploiting these valuable hydrocarbon streams and propose process design alternatives and operational solutions that achieve maximum recovery and use of flare gases at minimum total cost and considering the uncertainty variations associated with flaring incidents. This requires an understanding of the characteristics of flare streams that affect their recovery and reutilization potential as well as an examination of their impact on process system performance while recognizing that the inherently uncertain nature of flaring calls upon a probabilistic approach. In our study, we examine the impact of using a comprehensive probabilistic analysis framework for process flare streams' characterization on the design of an optimal recovery and utilization system. In particular, the work aims to explore the impact of uncertainty for key parameters on the design solutions, such as rate of flare occurrences that were assumed constant in other research works (Kazi et al., 2018). Suitable parametrized Monte Carlo (MC) simulations are employed for more accurate flare profile representations. A comparative study is conducted between the base case optimal design and values at risk solutions for cases where flaring variation increases may significantly affect the design features and economic performance of the process system. The proposed framework could inform decision makers' assessments of the impact of random variations in flaring profiles on process performance profile. 2022 Elsevier B.V.Scopu