A Decision Support Tool for Optimal Design of Integrated Biorefineries under Strategic and Operational Level Uncertainties

In this work, a decision support tool is presented to carefully design and optimize the business value of a renewable energy endeavor considering all types of uncertainties, including uncertainties at strategic and operational levels. A stochastic linear model is first developed to optimize production capacity of the plant, and then process simulation coupled with a stochastic optimization algorithm is employed to optimize the operating conditions of the plant. Market uncertainties are taken into account at the strategic planning level, and uncertainties related to parameters characterizing the processing technologies are addressed in operational level optimization. Monte Carlo-based simulation and global sensitivity analysis are utilized to identify the most critical parameters and optimize the operating conditions of the plant accordingly. Additionally, risk measurement strategies are introduced to the framework for explicit treatment of strategic and operational risks. For a demonstration of the effectiveness of the proposed methodology, a hypothetical case study of a multiproduct lignocellulosic biorefinery is utilized.