Submitted Abstract
With the permanent pressure to improve the competitiveness of production sites, efficient resource use is a main topic for manufacturing industries. As such, the valorisation of generated by-products increases a site’s product portfolio and therefore its revenues. One such by-product, so far barely valorised, is waste heat. At global scale, the waste heat potential was estimated at 68 PWh for 2012, of which 9 PWh were stemming from industrial processes, while the total energy consumption reached 120 PWh. One valorisation opportunity consists in producing electricity from waste heat (‘Heat-to-Power’ solution). However, optimising the electricity production in an integrated way is a complex task due to the important number of correlated variables to quantify and optimise. The consequence of this complexity is that potential synergies (e.g. equipment sharing) and optimal system selection and operation are often overlooked, thus limiting electricity production and, ultimately, the related revenues.The purpose of this project is to address this complexity with the development of an optimisation software to support ArcelorMittal Belval & Differdange in its decision-making process. This tool, relying on a mathematical programming model, will select the best combination of several Heat-to-Power technologies (Organic Rankin Cycles, steam turbines, thermoelectric elements, etc.) decentralised at heat source and/or centralised at plant level. The main parameters of these units (e.g. load, temperature, investment and operating costs) will thus be determined while considering economic (e.g. high viability), energy and LCA-based environmental constraints. The collaboration between ArcelorMittal and LIST will lead to an in-depth knowledge transfer as to theoretical mathematical optimisation and modelling of realistic constraints encountered in a production plant.