This paper describes the problems associated with the implementation of a real-time
optimization (RTO) decision support tool, for the operation of a large scale hydrogen
network of an oil refinery. In addition, a formulation which takes into account
the stochastic uncertainty of hydrogen demand, due to hydrocarbons quality change,
is described and further studied, focusing on its utility in the decision-making process
of operators. An integrated robust data reconciliation, and economic optimization,
considering plant-wide uncertain parameters is presented and discussed. Moreover,
stochastic uncertainty in hydrogen demand is assessed for its inclusion within
the RTO framework. A novel approach of the decisions stages at hydrogen producers
and consumers is proposed, which supports the formulation of the problem as
a two-stage stochastic non-linear program. Representative results are presented and
discussed, aimed at assessing the potential impact in the hydrogen management
policies. For this purpose, the value of the stochastic solution, perfect information,
and expectation of the expected value are analyzed. Complementarily, a risk-averse
formulation is presented (value-at-risk and conditional-value-at-risk) and its results
compared against the formulation without risk considerations. Finally, some attention
is given to future directions of this decision support tool, based on these work
contributions, including the importance of the decision makers’ participation in the
analysis of the potential impact of risk-averse results.
