CHEMICAL ENGINEERING TRANSACTIONS VOL. 29, 2012 A publication of The Italian Association of Chemical Engineering Online at: www.aidic.it/cet Guest Editors: Petar Sabev Varbanov, Hon Loong Lam, Jiří Jaromír Klemeš Copyright © 2012, AIDIC Servizi S.r.l., ISBN 978-88-95608-20-4; ISSN 1974-9791 DOI: 10.3303/CET1229039 Please cite this article as: Henrion T. and Werner A., (2012), Some benefits of dynamic simulation of energy systems in an integrated steel mill, Chemical Engineering Transactions, 29, 229-234 229 Some Benefits of Dynamic Simulation of Energy Systems in an Integrated Steel Mill Thibault Henrion* a , Andreas Werner b a Austrian Institute of Technology, Department Energy, Giefinggasse 2, 1210 Vienna, Austria b Vienna University of Technology, Institute for Energy Systems and Thermodynamics, Getreidemarkt 9/302, 1060 Vienna, Austria thibault.henrion@ait.ac.at In the frame of a research project, the physical behavior of the steam and hot water networks of an integrated steel mill were reproduced using the APROS simulation tool. The analysis of the steam distribution network behavior shows that strong fluctuation of some state variables (pressure, temperature) occur due to batch process productions and variable heat demand. Classical methods for efficiency improvement, like energy/exergy analysis or pinch/total site analysis, are based on steady-state assumptions. Hence, they do not consider inefficiencies due to the above described transient behavior. This work relies on a method based on dynamic behavior modeling of energy systems in order to assess energy efficiency, fluid quality and flexibility improvements. This paper describes, through a practical example dealing with a pressure swing problem caused by the interaction between the basic oxygen furnace and the hot rolling mill steam systems, the modelling and improvement procedure of the steam network. Subsequently, the application range of the developed simulation models is discussed. 1. Introduction The actual need in the industry to further reduce energy use encourages investigating new methods for the analysis and optimization of existing production processes. To answer to this need, a method using physical modeling of the dynamic behavior of energy systems has been developed. It is based on the general procedure of the process synthesis as explained by Tuomaala (2007).Existing optimization methods are usually based on empirical correlations or on thermodynamic correlations. They assume a steady-state operation of the considered units. An improved accuracy of the process parameters estimation can be reached, when the dynamic behavior of the process is taken into account, especially when time dependent physical phenomena play an important role in the involved processes (Henrion, 2012c). Therefore process modeling and especially dynamic simulation of transient operation helps to gain detailed knowledge on the investigated processes and deliver better optimized technical solutions. It helps in the case of existing industrial plants to complete the information from partially missing documentation and/or not available process data. This paper exposes some findings of a study, which used dynamic simulation tools in order to investigate the behavior of an existing Integrated Iron and Steel plant (IISP). It explains how the tool helps improving operations profitability by reducing the energy costs and increasing unit operability. The utilized method is detailed for one specific application example: the discontinuous steam production of the basic oxygen furnace and the hot rolling mill are interacting with each other and produce some pressure peaks in the networks. This leads to steam release through certain safety valves. Solutions to avoid these quality and energy losses were