It is not exactly a secret that melting steel with an electric arc requires massive amounts of energy. Typical production volumes start from a hundred thousand tons per year and reach over one million tons annually. It is obvious that the electricity bills are enormous but this means also that the direct and indirect CO2e emissions from the EAF process are unfortunately quite high. This article discusses how to optimize the EAF process to reduce these costs and emissions.
Because of the massive size of the production, even the smallest changes to the Electric Arc Furnace process may have significant economic benefits. In addition, reducing electricity consumption will reduce a lot of indirect CO2e emissions generated.
The challenge with the EAF process
Even though EAF’s have been operated for over a hundred years they have had one major flaw until recent times.
There has not been a simple way to measure how well and thoroughly the scrap inside the furnace is melting during the process. No way of knowing when would be an optimal time for loading additional scrap charges, phasing voltage taps, timing the burners, starting the slag foaming, etc.
This is because the harsh conditions inside the furnace have disabled the use of normal measurement sensors and indicators. Splashing slag and heat pretty much destroys any electrical equipment that is placed inside the furnace.
To work around the problem, the steel factories usually control the EAF processes with static methods. Typically, these models can work pretty well for many types of processes. However, there is just too much uncontrolled deviation in the EAF process.
There is no exact information about the inputted scrap content, material differences between heats, and the build material build-ups and refractory wear in the furnace cause deviation also in the physical dimensions of the furnace.
And in some cases, process control may be based only on the operator’s knowledge and expertise. The furnace is controlled by the sounds it emits or by the subtle visual cues it gives. This is not necessarily a bad thing itself. Though, in this case, the process optimization and the economic benefits it brings are left for the operators’ responsibility whose motivation and skill may also vary.
However, what if we could see and measure what happens inside the EAF in real-time?
With real-time melting information, dynamic control of different phases, and optimizing the EAF process becomes possible. For example, the timing of additional scrap charges can be done optimally exactly when the scrap has melted enough to fit the second charge (or third or even fourth in some cases).
The same goes with controlling the burner online time. Inserting chemical energy into the process only when it is needed (scrap has not completely melted) decreases the burner gas costs but also cuts down the emissions. Timing the high-power voltage taps to match the window of best energy efficiency (can also be deducted from the scrap melting progression) will cut your electricity bill by hundreds of thousands or even millions of euros in a year.
All in all, doing the right things at the right time with real-time melting information will make your EAF process more efficient and productive. And on top of that, the information and data from the process make the life of operators and process engineers much easier.
How to measure the EAF process in real-time?
Like said it is not just possible to put a camera in the furnace and see what happens. There have been also some ways to indicate what is happening inside the EAF, but they have some limitations too
For example, off-gas analysis and side panel cooling water analysis suffer from significant delays. It takes time for the gas to travel to the sensors or for the water to heat up in the side panels. Furthermore, it is very difficult to interpret why has the off-gas temperature or side panel temperature increased. These limitations have prevented reliable real-time control – until now.
Optical emission spectrometry (OES) is an analytical technique to break down and examine light emitted from different sources. This method is usually used in detecting different elements in a sample by analyzing the light that they emit when excited (with laser/spark).
This can be also applied to real-time hot metallurgical processes. For example, EAF emits a great amount of light during the heat and the melting progress can be measured by observing the changes in the emitted light. This makes real-time measurements possible, but also other information such as slag composition and temperature can be deducted from the light’s spectrum.
There are three main features that the measuring device must have so it can be used for real-time, optimized control of the electric arc furnace. These features are:
- Measuring the right phenomenon. The scrap melting progression is the core of the EAF process. There are a lot of different phenomena that can be tracked, for example, the changes in the furnace atmosphere but they don’t describe the actual changes in the EAF process.
- The data must be real-time. The process can’t be timed optimally if there is a long delay between the phenomena and the sensor register the process change.
- The data must be accurate and consistent. To reliably control the process, the data must describe the right phenomena but also the right changes in the phenomena. In addition, the data must be continuous to control the process continuously.
The Optical Emission Spectrometry does exactly these things.
We at Luxmet specialize in using optical emission spectrometry in hot-metallurgical processes. Our ArcSpec system is built to handle the extreme conditions of EAF, and it uses the OES for real-time, dynamic process control.
ArcSpec has been proven to significantly improve EAF energy and process efficiency and productivity in various types of steelmaking EAFs. Typically, we are talking about millions of euros saved per system. In addition, we have helped steel plants to save thousands of tons of CO2e emissions.
We are more than happy to have a brief discussion and analysis of your EAF process if you are interested in real-time scrap melting based optimization. Please, do not hesitate to contact us!
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