کاهش مصرف انرژی و تولید گازهای گلخانه ای CO2 از صنایع انرژی بر از طریق سیستم های پشتیبانی تصمیم گیری - نمونه ای کاربردی برای صنعت فولاد

The management of process industries is becoming in the recent years more and more challenging, given the stringent environmental policies as well as raising energy costs and the always-present drive for profit. A way to help plant decision makers in their daily choices is to refer to decision-support tools, which can give advice on the best practices on how to operate a plant in order to reduce the energy consumption and the CO2 emissions keeping at the same time the costs under control. Such an approach can be useful in a variety of industries, particularly the most energy-intensive ones such as iron and steel industries. In this paper, an approach to the realisation of a software system, which allows to generate internal reports on the plant performances, as well as to simulate the plant behaviour in different scenarios, is described. The main production processes (coke plant, blast furnace, steel shop, hot rolling mill) are described and simulated focusing on the prediction of products flow rates and composition, energy consumption and GHGs (Greenhouse Gases) emissions in different operating conditions. The importance of a correct management of the CO2 within the plant is underlined, particularly with regard to the new EU Emission Trading System, which will be based on European benchmarks. The software tool is illustrated and a case study is included, which focuses on the simultaneous minimisation of the CO2 emissions and maximisation of the profit through an optimised management of the by-product gases. The results from the case study show a good potential for process improvement, by a reduction in the cost and environmental impact.

Steel industry is among the main energy-intensive manufacturing systems worldwide: according to the International Energy Agency (IEA), the iron and steel sector is the second-largest industrial user of energy, consuming 616 Mtoe in 2007. In particular, the BF/BOF route (which uses 13–14 GJ per ton of iron produced) is much more energy-intensive than the scrap/EAF route (using 4–6 GJ per ton of iron produced when using 100% scrap [1]. Given its heavy dependence on fossil fuels, it also accounts for 15% of total anthropogenic GHG emissions [2]. The greenhouse gas of highest relevance to the world steel industry is carbon dioxide (CO2): 1.9 tons of CO2 are emitted per ton of steel produced and approximately 4–5% of total world CO2 emissions are attributed to this sector [3]. European and non-EU governments require concrete actions to tackle global warming worldwide [4] and [5]. Thirty-eight countries committed in December 2011 that a universal legal agreement on climate change should be adopted no later than 2015. Starting from January 2013, a second Kyoto Protocol commitment period will take place [6]. In such a scenario the steel industry is strongly interested in reducing its energy consumptions as well as its CO2 emissions. The final objective of this research work is therefore to develop and implement a decision support tool aimed at the reduction of the CO2 emissions and the energy consumptions within an integrated steelwork located in Piombino, Italy.

This paper describes the development of a decision support system for the management of energy-intensive industries. In particular, an example of application to the iron and steel industry has been shown as an example of application. The tool is intended to provide reports on the energy consumption, current and cumulated emissions of the plant, and these capabilities as well as the possibility to elaborate scenarios and forecasts about the energy consumption and the CO2 emissions of the plant have been discussed in the article. The reporting system which is underlying the system is in line with current EU normative framework and allows the plant to compare its performance with the relative benchmark CO2 curves. Different flowsheeting models have been realised and interlinked to give a comprehensive simulation system for the plant considered as a whole. The simulation framework has been adapted for convenient implementation within optimisation tasks. The presented software system also allows to run a process optimisation which returns best trade-off solutions based on multiple criteria, and focusing on the economical and environmental aspects for a correct management of the plant operating conditions. A case study where CO2 emissions and profit were used as objective functions has been presented, where interesting results were achieved; however, the capabilities of the software which were utilised as well as the flexibility of the tool could allow to focus on different process KPIs, e.g. raw material or energy efficiency, as objectives of the minimisation problem. Moreover, future work will be focused on the finalisation of the software tool user interface and of its online integration within the hardware structure of the company. The final system will be subject to further evaluation of reliability in terms of stability and accuracy of results in comparison with actual process data.