Modeling and Simulation of Integrated SVC and EAF using MATLAB & ETAP Ahmed M. Hassan
Tarek El-Shennawy
Al-Ezz Dekheila Steel Co.(EZDK) Alexandria 21537Egypt
[email protected]
Alexandria National Refining and Petrochemicals Co. (ANRPC) Alexandria 23111 Egypt
[email protected]
Electric Arc furnace (EAF) represents one of the most Abstra Abstract ct — Electric intensive and disturbing loads in the electric power system. Utilities are concerned about the effects such load can cause and try to take precautions to minimize these effects. Therefore, an accurate model of an arc furnace is needed to test and verify proposed solutions of mitigation. One of the most important solutions for the voltage fluctuations mitigation is the Static Var Compensator (SVC). This study presents the results where arc furnace is modeled using both chaotic and deterministic elements. Voltage fluctuations are captured using the well-studied circuit whereas a dynamic model in the form of differential equation is used for the electric arc. A more accurate simulation of developed model is done in Sim-PowerSystem environment of the MATLAB 7.12 Version and Electromagnetic Transient Analysis Program (ETAP) for Main Receiving Substation (MRSS) of EZDK.
K eywordseywords-com compo ponent nent — Electric Arc Furnace, Static Var Compensator, Harmonic Analysis, Power Quality, Flicker Mitigation, MATLAB, ETAP I.
NTRODUCTION I NTRODUCTION
Electric Arc Furnace (EAF) is a widely used device in metallurgical and processing industries. It is a nonlinear time varying load, which can cause many problems to the power system quality such as unbalance, harmonic inter harmonic and voltage flicker [1]. Thus study of electric arc furnaces has potential benefits for both customers and utilities. An accurate modeling of an EAF will help in dealing with the problems caused by its operation. Minimization of the undesirable impact of EAFs can improve electric efficiency and reduce power fluctuations in the system. The description of an arc furnace load depends on the following parameters: arc voltage, arc current and arc length (which is determined by the position of the electrodes). Based on the study of above essential parameters, many models are set up for the purpose of harmonic and flicker analysis [2]. In general, they may be classified as follows, a) Time domain analysis method (Characteristic Method, Time Domain Equivalent Nonlinear Circuit Method), and b) Frequency Domain analysis method (Harmonic Voltage Source Model, Harmonic domain Solution of nonlinear differential equation). Each method has its own advantages and disadvantages. Comparison and commendation of different arc furnace models were presented in [3]. Most of the existing models make some kinds of approximation on the characteristic of arc. There have been two
Amr Abou-Ghazala Electrical Engineering Department, Faculty of Engineering, Alexandria University Alexandria 21544 Egypt
[email protected]
general approaches to the problem of arc furnace modeling: stochastic and chaotic. In most of the previous studies, stochastic ideas are used to capture the periodic, nonlinear, and timevarying behavior of arc furnaces [4-6]. In [4], the arc furnace load is modeled as a voltage source. The model is based on representation of the V-I characteristics using sinusoidal variations of arc resistance and band limited white noise. Research study shows that, the electrical fluctuations in the arc furnace voltage have proven to be chaotic in nature. Some chaos-based models reported in specialized literature [7-8] have been applied to simulate simulate ac [9-10] and dc arc furnaces [11]. This paper paper intends intends to to present present an integrated integrated simulation simulation modeling of EAF and SVC networks instead of using single valued piece-wise linear V-I characteristics of the arc furnace load, a dynamic and multi-valued V-I characteristics are obtained by using corresponding differential equations [10]. The output of dynamic model developed is modulated with low frequency chaos signal to produce the arc furnace model. The model developed is connected to actual power system model to study the voltage fluctuation. The paper is organized as follows; Section II introduces the modeling of EAF. Section III discusses the SVC theory of operation and background history. Section IV describes the Case Study for Integrated Model of EAF and SVC. Finally, the conclusion is presented in section V. II.
MODELING OF EAF
A. Arc Furnace Operation Electric arc furnaces are available in both alternating current (AC) and Direct current (DC) models. A transformer directly energizes furnace electrodes in a high current circuit in arc furnaces, whereas dc furnaces employ a controlled rectifier to supply dc to the furnace electrodes. Arc furnace operation may be classified into stages, depending on the status of the melt and the time lapse from the initial energization of the unit. Consider the case of the processing of scrap steel in an ac EAF. During the melting period, pieces of steel create momentary short circuits on the secondary side of the furnace transformer. These load changes affect the arc characteristics, causing fluctuations of current. The current fluctuations cause variations in reactive power, which cause a momentary voltage drop or flicker, both at the supply bus and at nearby buses in the interconnected system. The arc currents are more uniform during
(i) At least one locally active reactor
the refining period and result in less impact on the power quality of the system. Arc furnaces also create harmonic load currents and asynchronous spectral components. Harmonics represent an important power quality issue, because they may cause undesirable operating conditions such as excess losses in transformers, mal-operation of drive controllers etc. [1]. Fig.1 shows typical installation of EAF.
C. Matlab Simulink Model Of EAF
Fig. 1. Typical installation of EAF
The development of general dynamic arc model in the form of a differential equation is based on the principle of conservation of energy. The approach is fundamentally different from those methods where some empirical relation is used to represent the electrical arc. In the dynamic model such relations which are implicit for steady state conditions are not pre defined and give result for different conditions depending on both frequency and current magnitude. Here the arc furnace is modeled in two stages. First dynamic electric arc modeling is done and the obtained arc voltage is then modulated with chaotic signal to produce final arc furnace model.
Fig.2 shows actual and piece-wise linear approximation of VI characteristic of an Arc Furnace Load where Vig is the ignition voltage and Vex is the extinguish voltage.
(ii) At least one nonlinear element. (iii) At least three energy storage elements Chua’s circuit satisfies the above requirements.
The power balance equation for the arc is
(1)
Where P1 represents the power transmitted in the form of heat to the external environment. P2 represents the power, which increases the internal energy in the arc, and which therefore affects its radius. P3 represents the total power developed in the arc and converted into heat. The above equation can be represented in the form of differential equation [13] of the arc:
Fig. 2. Actual and piece-wise linear approximation of V-I characteristic of an Arc Furnace Load
B.
Chaotic Dynamics In Electric Arc Furnaces
Chaos, also known as the strange attractor, does not generally have an accepted precise mathematical definition. Usually from a practical view point, it can be defined as the bounded steady-state behavior that does not fall into the categories of the other three steady-state behaviors i.e. the equilibrium points, periodic solutions, and quasi periodic solutions [8]. The equilibrium points are zero dimensional and periodic solutions are one dimensional, where as strange attractors are more complex and their dimension is a fraction. A chaotic system is a deterministic system that exhibits random movement and it is a nonlinear system that exhibits extreme sensitivity in the state trajectory with respect to the initial conditions. It has been observed that t he electric fluctuations in an arc furnace are chaotic in nature [12]. The chaotic component of the arc furnace voltage is obtained from the chaotic circuit of Chua [10]. To exhibit chaos, the circuit consisting of resistors capacitors and inductors has to contain the following:
(2)
Where r is the arc radius and is chosen as the state variable instead of taking arc resistance or conductance. k 1, k 2 and k 3 are constants relative to EAF melting conditions. m is the variations of the resistivity with temperature. n is the conditions of cooling. The arc voltage is given by:
(3)
Where g is defined as arc conductance and is given by the following equation:
(4)
It is possible to represent the different stages of the arcing process by simply modifying the parameters of m and n. The complete set of combination of these parameters for different stages of electric arc can be found in [11]. The state space equations of the above mentioned system would be in this case: R o =
-
V=i*
(5) (6)
Implementing the above equations using Simulink blockset as shown in Fig.3, taking the parameters K 1= 2500; K 2 = 1; K 3 = 0.0001; n=2; m= 0 the dynamic voltage/current characteristic of the electric arc are modeled as shown in Fig.4.
III.
SVC BACKGROUND AND THEORY OF OPERATION
By definition, capacitors generate and reactors (inductors) absorb reactive power when connected to an ac power source. They have been used with mechanical switches for (coarsely) controlled var generation and absorption since the early days of ac power transmission. Continuously variable var generation or absorption for dynamic system compensation was originally provided by .over- or under-excited rotating synchronous machines and, later, by saturating reactors in conjunction with fixed capacitors. Since the early 1970’s high power, line-commutated thyristors in conjunction with capacitors and reactors have been employed in various circuit configurations to produce variable reactive output, [19]. These in effect provide a variable shunt impedance by synchronously switching shunt capacitors and/or reactors "in" and "out" of the network as shown in Fig.6
Fig. 3 MATLAB/ Simulink model of electric Arc Furnace
Fig. 6 SVC Components
The SVC is used to regulate voltage on a system. When system voltage is low the SVC generates reactive power (SVC capacitive). When system voltage is high it absorbs reactive power (SVC inductive) as shown in Fig.7. Fig. 4 Dynamic Characteristics of EAF
This model is then combined with the band limit white noise to create the chaotic nature of the arc furnace voltage and current parameters as shown in the control structure of EAF as shown in Fig.5 [14-18]
Fig. 5.Control Structure of Arc Furnace
Fig. 7 SVC Interaction with Power Network Dynamics
IV.
CASE STUDY FOR I NTEGRATED MODEL OF EAF AND SVC
The integrated model built in the simulink environment is based on Pierre Giroux and Gibert Sybille (Hydro-Quebec) SVC detailed model in SimPowerSystems™ first and Second Generation software after eliminating the switching on the filter circuits and integrate the model with the EAF. The combined model represents actual complete case study network of EZZ-DEKEILA Main Receiving Substation with Point of Common Coupling (PCC) and the configuration is as described in the following table:
The fault is cleared and the network restores normal operation. 4) Case 4 from time 0.5 till 0.7 sec The SVC is in service and the TCR and number of capacitors reacts with the B.B MVAR. 5) Case 5 from time 0.7 till 0.9 sec A three phase short circuit is applied on the furnace B.B while the SVC is online. 6) Case 6 from time 0.9 till 1 sec The fault is cleared.
TABLE I. Network and SVC data Network Data PCC (kV) Substation incoming feeders installed capacity (MVA)
Power Transformers kV, MVA EAF’s MVA Short Circuit Capacity, MVA System X/R Ratio SVC Data Thyristor Controlled Reactors (TCR), MVA 2nd Harmonic Filter, MVAR 3rd Harmonic Filter, MVAR 4th Harmonic Filter, MVAR 5th Harmonic Filter, MVAR
220/66 3x380 220/33, 2x125/150 (ONAN/ONAF) 58 MVA 8000 10 265 35 52.5 40 52
In order to study the behavior of the network a fault breaker is added as shown in Fig.8 to simulate the following various cases:
Fig. 8 Integrated SVC and EAF Matlab Model
1) Case 1 from time 0 till 0.2 sec During this time the EAF start while the SVC is offline, refer to Fig.9 2) Case 2 from time 0.2 till 0.4 sec A three phase short circuit is applied on the furnace B.B while the SVC is still offline. 3)
Case 3 from time 0.4 till 0.5 sec
Fig. 9 Cases shown in the simulation of fault analysis
In Fig.10 an Electromagnetic Transient Analysis Program (ETAP) simulation is implemented to simulate the same network but in this case to check the total harmonic distortion levels on the 220 kV level and on the 33 kV level and ensure satisfying required standards.
Fig. 10 ETAP simulation for THD levels
A. Results & Discussion As shown in case 1, during normal operation the SVC TCR o o reacts from full conduction (90 ) to no conduction (180 ) according to the required reactive power to keep the reference voltage 1 p.u. In case 2, when the SVC is offline the fault makes the B.B current multiples of normal current and a voltage drop occurs.
In case 5, when the SVC is in service the response of the system is better regarding the damping of the fault current and the voltage drop on the B.B. The THD on the 220 kV level is (0.4%) which is within standards limit and penalties due to harmonic pollution can be easily avoided. V.
CONCLUSION
The EAF Matlab model in this paper gives more realistic simulation to the EAF taking into consideration its chaotic nature. The fault analysis during various conditions also gives a better understanding to the system behavior during different fault scenarios and the interaction between the SVC Model and developed EAF model.
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ETAP Modeling showed the harmonic analysis of the complete network and the contribution of the SVC in eliminating system harmonics.
[12] Santo Banerjee, Mala Mitra Applications of Chaos and Nonlinear Dynamics in Engineering – Springer Science+Business Media, 2011.
A techno economical study can be made based on this work to present the feasibility study of the SVC and its role in increasing the EAF efficiency and hence increasing tons of molten steels produced per year.
[13] E. Acha, A. Semlyen, and N. Rajakovic, A harmonic domain computational Package for nonlinear problems and its application to electric arcs, ‖ IEEE Trans. Power Delivery, Vol. 5, Pp. 1390 – 1397, July 1990.
VI.
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