posted on 2016-02-10, 16:01authored byA. Geraili, S. Salas, J. A. Romagnoli
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.