Gianluca Nastasi

Artificial Intelligence, Artificial Neural Network, Data Mining

The project aims at improving the off-gases management within steelworks by minimizing gas amount that is burned in torch, air emissions, environmental impact and costs related to the waste of a resource and of CO2 allowances. A decision support tool for process operators and the support team is developed simulating gas networks and optimizing gases distribution, considering all operating constraints. System dynamics and correlations between energy demands and gases production are fundamental for this analysis: considerable savings can be achieved through transients proper management. Multi-period and multi-objective optimization (MOO) techniques are applied to face this challenging objective.
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Development of dynamic approaches for electricity demand monitoring and timely reactions to grid situation to avoid non flexible equipment disconnection and financial fines when deviating from energy contingent.
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