Abstract
1- Introduction
2- Electric arc-furnace energy demand
3- Demand-side management techniques
4- Ampacity
5- Quality of service
6- Optimization
7- Results
8- Conclusions
Acknowledgments
References
Abstract
An electric arc-furnace is a complex industry which demands high levels of electrical energy in order to heat iron materials and other additives needed for the production of cast iron and/or steelmaking. The cost of the electrical energy demanded by the factory during the production can be greater than 20% of the overall cost. This kind of arc-furnace allows the production of steel with levels of scrap metal feedstock up to 100%. From an electrical point of view, the factory size in terms of its maximum apparent power demanded from the grid is designed to make use of the static capacity of the transmission line that supplies the energy. In that case, it is not possible to increase the power of the factory above the static rating by adding new facilites without installing new transmission infrastructures. This paper presents a methodology that allows an increase in net power of an arc-furnace factory without installing new transmission lines. The novelty of the proposed solution is based on a mix strategy that combines Demand-Side Management (DSM) methodologies and the use of ampacity techniques according IEEE 738 and CIGRE TB601.
The application of DSM methodologies provides an improvement in the sustainability of not only the industrial customer but also in the overall grid. As a secondary effect, it reduces operational costs and the greenhouse gas emissions.
Introduction
An electric arc furnace (EAF) is a furnace that heats charged material by using an electric arc. They are usually devoted to the production of cast iron and/or steelmaking. From an energy point of view, it is a load that it is intensive in terms of its power demanded from the grid [1].
As the electrical energy consumption in an EAF based steel factory is typically greater than 20% of the overall production cost, most of the modeling effort has been devoted to the analysis of energy comsuption considering cost minimization [2] as the main target [3]. From the point of view of predicting the electrical energy consumption of Electric Arc Furnaces using statistical Modeling it is possible to find several approaches using both linear and non-linear models. Table 1 summarizes several contributions in the field of EAF modeling.