Modellering en regeling van flexibiliteit in energie-intensieve industriële systemen

This dissertation proposes methodologies to model, valorize, and control industrial demand-side flexibility. On the one hand, we propose the Industrial Flexibility Scheduling Modeling Framework (IFSMF) approach to estimate the potential value of flexible demand (from the consumer perspective). This framework is inspired by inventory planning, electricity balancing markets' products, the unit commitment and economic dispatch problems, and models presented by other authors in the literature. On the other hand, a similar methodology is proposed for their control, considering a more accurate grey-box modeling approach: the Generic Buffer. This approach allows us to identify potential energy or material storage that can translate as sources of flexibility to the system's electricity consumption. In addition, we showcase multiple flexibility valorization objectives, demonstrating that quantifying flexibility in abstract terms might be irrelevant compared to quantifying its value, which is highly dependent on the target objectives. The case studies within this thesis contain the following: • The flexibility scheduling of a steel powder manufacturing plant under a two-step optimization approach, first on the day-ahead market and then on the intraday market. • A sensitivity analysis of some IFSMF model parameters and how they influence the two-step multi-market optimization. • The multi-objective flexibility scheduling of an industrial steam network with carbon emissions, energy costs, and blow-off steam as objectives. • The predictive control of a steam network with a combined energy cost and carbon emissions objective