Arc-furnace model for the study of flicker compensation in electrical networks

Montanari, G.C.; Loggini, M.; Cavallini, A.; Pitti, L.; Zaninelli, Dario

doi:10.1109/61.329535

Cited by 175 publications

(73 citation statements)

References 10 publications

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“…There are already a number of papers that present various modeling approaches to several sub-systems of electric arc furnaces, from basic arc models 1,2) to complex flicker simulations, [3][4][5][6][7] which tend to prevail due to the enormous impact of EAFs on electrical networks. Since the EAF represents a complex system these articles usually focus on a certain EAF-related problem and in some instances use simulated, laboratory-generated data for the analysis, which is easier to process and gives more convenient results.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Experimental Validation of an Electric Arc Furnace

2011

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The following paper presents an approach to the mathematical modeling of 3-phase AC, electric arc furnace (EAF) processes for control-design and process-optimization purposes. The EAF can be, from the modeling point of view, considered as a combination of electrical, hydraulic, chemical, thermal and several energy-balance sub-processes or sub-models. In this paper the modeling of the electrical and hydraulic submodels is presented in detail, since the two represent a very complex and important sub-system of the complete EAF model. The presented sub-models are obtained in accordance with different mathematical, electrical and mechanical laws. Several parameters, which are necessary to successfully identify the scrapmelting process, were fitted experimentally, using the measured operational data of an 80 MVA AC furnace during different periods of the melting process. Similar data has also been used for the validation of the developed model in typical EAF operating situations. The aim of the presented EAF modeling is to obtain an accurate, robust and realistic mathematical model of the scrap-melting process, which will later be used for control-design purposes, the optimization of the energy consumption and the development of an operatortraining simulator. The main advantage of our modeling approach over the existent EAF-related models is a more macroscopic level of modeling, which accurately simulates the electrical and hydraulic processes under different conditions in the EAF.KEY WORDS: EAF; electric model; hydraulic model; experimental validation; harmonic analysis. reactances; etc.) and non-electrical (transformer and reactor taps; number of short circuits and arc breakages; electrode controller outputs; electrode position; temperatures of the cooling panels; composition and weight of the additives; consumption of oxygen, carbon, gas; etc.) values sampled over a 1-s time window. At this stage of the model's development, nearly all of the electrical and some of the mechanical values were used to obtain the correct parameters of the sub-models describing the electrical properties of the EAF. Additionally, since the properties of the electric arcs are dependent on the position of the hydraulically actuated electrodes, the presented hydraulic sub-model for the electrode control completes the particular modeling assembly. Measurements and Modeling EAF Operation DataFor the purposes of this study, the measurements were made during different operational situations in the EAF melting process. The obtained data included measurements of the effective values, i.e., the root mean squares (RMS), sampled over a 1-s window of the following: phase voltages; phase-to-phase voltages; arc voltages; phase currents; power factors; arc resistances and reactances; total circuit resistances and reactances; apparent, active, reactive and arc power; total energy consumption; etc. The measurements were made with the electrode-control and data-acquisition system (E.M.P.E.R.E.). 8) ModelingThe following section presents the approach to mod...

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Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Experimental Validation of an Electric Arc Furnace

2011

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“…The electric arc furnace was modelled as described in [2]. The furnace (the electric arc) is modelled as a voltage source.…”

Section: Test System Configurationmentioning

confidence: 99%

“…The time-varying nature of consumption and the non-linear voltage-current characteristic have a large negative influence on power quality. They are major sources of voltage oscillations in power systems, which can produce the effect known as flicker [1], [2]. In addition, EAFs consume a significant quantity of reactive power which may give rise to voltage instability in power systems without proper compensation.…”

Section: Introductionmentioning

confidence: 99%

Development of a Control Algorithm for a Static VAR Compensator Used in Industrial Networks

Spasojević¹,

Papič²,

Blažič³

2014

Journal of Power Electronics

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In this paper a method for the development of a static VAR compensator (SVC) control algorithm is presented. The proposed algorithm has been designed with the objective of eliminating the negative impact of electric arc furnaces on the power system. First, a mathematical model of the proposed SVC controller in the d-q synchronous rotating coordinate system is developed. An analysis under dynamic and steady state conditions is also carried out. The efficiency of the presented controller is demonstrated by means of computer simulations of an actual steel-factory network model. The major advantages of the proposed controller are better flicker compensation, increased ability to regulate voltage and the need for only one-point network measurements.

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“…The first sub-group involves models, such as: EAF electrode control, arc flicker impacts, investigation of the EAF effects on the electrical grids, etc. 8,[10][11][12] In this group, arc behavior is simulated by equations describing the relations between the voltage and the current [10][11][12] and passive devices. 8) Each stage of the melting process can be modeled in a particular way.…”

Section: Introductionmentioning

confidence: 99%

“…A literature review of the existent EAF models [8][9][10][11][12][13][14][15][16][17][18][19][20] indicates a lack of accurate arc models that could be applied for smart sensing, control or optimization of the energy flows. It is assumed that such model should present specific features that support their industrial application, including minimum input requirement, sufficient accuracy, simple mathematics and short calculation times.…”

Section: Introductionmentioning

confidence: 99%

Low Computational-complexity Model of EAF Arc-heat Distribution

et al. 2015

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The paper presents a computational model and the corresponding algorithm for estimating the arc energy distribution to conductive, convective and radiative heat transfer in an electric arc furnace (EAF). The proposed algorithm uses channel arc model (CAM) in order to compute the distribution of the arc energy through empirical equations (to approximate arc radius), ideal gas law (to approximate arc density) and results of magneto-hydro-dynamic (MHD) models (to approximate arc pressure, temperature and velocity). Results obtained using the proposed algorithm are comparable with other similar studies; however, in contrast to other arc-energy distribution models, this model requires only two input variables (arc length and arc current) in order to calculate the energy distribution. Furthermore, simple algebraic equations used in the algorithm ensure minimal computational load and consequently lead to short calculation times which are approximately one hundred thousand (100 000) times smaller than solving the MHD model equations, making the algorithm suitable for real-time applications, such as smart monitoring and model-based control. The algorithm has been validated by two different approaches. First, the simulation results have been compared to a study dealing with arc-heat distribution in plasma arc furnace; and second, the proposed arc module has been integrated into the frame of a comprehensive EAF model in order to estimate the EAF temperature levels and compare them with operational EAF measurements. Both validations show high levels of similarity with the comparing data.KEY WORDS: arc current; arc heat distribution; arc length; channel arc model; EAF.approximately 75-85% of the total energy in low to medium power furnaces and approximately 50-60% of the total energy in ultra-high power furnaces (UHP).3) Implementing an accurate arc module in a comprehensive model-based EAF control, which ensures optimal control of arc length and slag height can lead to substantial energy saving and associated cost reduction. If a total energy reduction in a 200 ton UHP EAF with approximate annual production of 675 000 tones is 50 kWh/ton, with an assumption of 25 kWh/ton being the electrical energy, with the price of 10 $Cent/kWh, total annual energy savings will be equivalent to 1.7 million $ per year.It is known that the heat generated by the arcs is dissipated into the furnace by all three mechanisms of heat transfer (convection, conduction and radiation); however, the amount of the heat, transferred by each mechanism varies according to several factors, such as arc length, arc current, slag height, stage of melting etc. Development of a computational model of the arc, which allows estimation of the arc-heat distribution should therefore include all three types of heat transfer mechanisms, which can also be used to obtain the overall energy balance of the EAF. Application of such models may provide appropriate tools for optimizing the energy flow or use of model-based control systems in the EAFs.

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Arc-furnace model for the study of flicker compensation in electrical networks

Cited by 175 publications

References 10 publications

Mathematical Modeling and Experimental Validation of an Electric Arc Furnace

Mathematical Modeling and Experimental Validation of an Electric Arc Furnace

Development of a Control Algorithm for a Static VAR Compensator Used in Industrial Networks

Low Computational-complexity Model of EAF Arc-heat Distribution

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