Critical Clearing Time and Voltage Stability of DG Integration in Lebanon: A Simulation Using MATLAB/SIMULINK

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1 Sep. 2013, Volume, No. (Serial No. ) Journal of Energy and Power Engineering, ISSN , USA Critical Clearing Time and Voltage Stability of DG Integration in Lebanon: A Simulation Using MATLAB/SIMULINK KifahDaher 1, Student and Maged B. Najjar 2, IEEE member 1. Department of Electrical Engineering, University of Balamand, North Tripoli, Lebanon; kifah.daher@gmail.com 2. Ph.D., Professor; power area, Department of Electrical Engineering, University of Balamand, North Tripoli, Lebanon, maged.najjar@balamand.edu.lb Abstract: These days, the renewable energy is widely participating in the electric energy production worldwide. Different studies and work have been done concerning the integration of Distributed Generations (DG) with the power grid; optimal sizing and allocation techniques has shown the appropriate penetration method for superlative beneficial effects. This paper investigates particularly the integration of DG in existing power systems while assuring the system s stability under fault conditions. The relative between the DG especially induction generator type with respect to transient stability is examined. The critical clearing time (CCT) is an essential criterion for a DG to ride through faults; in this paper a theoretical calculation of CCT is obtained all along with simulation results. CCT is improved using a STATCOM at distribution level or by the implementation of inverter-based distributed generations. A simulation was designed to investigate the proposed approaches using MATLAB/SIMULINK. Keywords: Smart Grid, Distributed generators DG, Renewable, Power electronics, Converter, Power flow, Control, CCT. 1. Introduction The constantly increasing penetration of distributed generation (DG); especially the wind farms make it important to understand the impact of these machines on a power system. Distributed power generation integration with the conventional grid can have positive and negative impacts. The impact of DG on the stability of a power system depends on the technology of the DG and on the penetration level. Distributed generations are widely used after the advancement of technology in the electrical engineering field especially smart grid topology. Maintaining the grid stability and voltage regulation is the challenge facing smart grid technology and DG integration [1]. Figure 1 shows the electricity production in Lebanon. Electricity generation from public sector covers approximately 56% of the total demand which is around 2500 MW [2]. Private backup diesel generators provide the rest 44%. DG participates largely in the electricity generation in Lebanon for this reason investigating the CCT and the ride through faults capability along with voltage stability is extremely important. 2. Study Case Network - Microgrid The following section introduces a benchmark distribution system of medium voltage which will be used to test the behavior of DGs under fault conditions. 44% 6% 50% Public thermal Power Plants Public hydro power plants Private backup Diesel Generators Figure 1: Electricity production in Lebanon [2] 1

2 Wind turbines represent the integrated DGs to the system. The used wind turbines from Matlab library, induction generator and doubly fed induction generator type, are introduced in this section. 2.1 Benchmark of Medium Voltage Distribution Network The increase of DG integration at the low voltage (LV) and medium voltage (MV) leads to a new power system concept, the MicroGrid. Distribution networks with DG integration can be connected to the network or operate separately. A benchmark for investigation of DG integration is described in this section. It was considered as an MV benchmark system in the context of CIRGE task force [3].The network is of rural type with a rated voltage 20 kv. The benchmark network is subdivided into two sub networks and supplied by 110/20 kv transformers TR1 and TR2. It is a closed network and the length of cables is around 21 km [3]. In order to investigate stability of integrated DGs to the MV distribution system under different scenarios, the system was simulated under Matlab/Simulink environment. The system is constructed using Three-phase PI section line for distribution line cables, three phase two winding transformer to represent the transformers supplying the network. The grid supplying the network is a 110 kv infinite source. Three-Phase Series RLC Loads are used to represent the load at each bus at its maximal power consumptions. The constructed MV benchmark to be simulated using Matlab\Simulink is shown in Fig. 2. The starting point of investigation was the base power flow. Loads were considered while DGs were omitted from the network. Loads and line parameters are detailed in [3] Wind Turbine Induction Generator The WTIG block was used from the SimPowerSystems library browser to represent the connected DG. The stator windings are directly connected to the three-phase network. The wind drives the turbine and by its turn drives the rotor. Via the induction generator, mechanical power captured is transformed into electrical power and then is transmitted via the stator winding. A pitch angle controller is present in order to limit the generator output power to its nominal value for high wind speeds. The induction generator runs in slip mode. This slip means that an induction generators operation is thus asynchronous. The slip increases when the loads are heavier. As higher loads require stronger magnetic fields, the machine speed deviates from synchronism. Then for an induction generator its operating speed has to be above the rated synchronous speed. 2.2 Distributed Generation Integration For simulation purposes, various scenarios were applied to the MV test network with different DG type integration. Figure 2: MV test network under Matlab\Simulink 2

3 Components as capacitors and condensers supply the generator by the needed reactive power in parallel to the grid [4]. In our simulation, capacitors will be used to generate the required reactive power. Stability of an induction machine can be studied from the torque Vs speed characteristic curve. If the induction machine is driven to a speed higher than the synchronous speed, it becomes a generator and delivers power. The speed torque characteristic is shown in Fig.3. For an unvarying mechanical input, two equilibrium points are observed in this figure. The point in the stable region is the steady-state stable speed and the second one is the critical speed point. If before the generator s critical speed point is reached the fault is cleared, the mechanical input torque will be less than the electrical torque. This will lead the rotor to decrease speed to a value that match the one before the disturbance. In the other hand when this point is crossed, the electrical torque will be less than the mechanical torque which will invokes acceleration in the rotor speed leading to a runaway slip. Thus, the generator will be unstable [5] Wind Turbine Doubly-Fed Induction Generator The WTDFIG block was used from the SimPowerSystems library browser to represent some of the connected DG. Those kinds of DG are connected to the Grid using control methodology and power electronics. Fig. 4 represents the operating principle of the used induction generator. It is based on an AC/DC/AC converter connected in series with the induction machine then to the grid. The converter is formed from a rotor side converter and a grid side converter. Voltage Sourced Converters (VSC) uses IGBTs to convert the DC voltage source into an AC. The DC voltage can be represented by a capacitor. To smoothen the output, a coupling inductor is connected to the grid side converter. The rotor windings are connected to the rotor side converter by brushes and slip rings, and the stator windings are connected directly to the grid. Wind power is converted into electrical one and then is delivered to the grid by both the stator and the rotor windings. The pitch angle and the voltage signals are controlled by the implemented control system in order to manage the wind turbine output. The power, the DC voltage and the reactive power or the terminals voltage can be controlled. Converters can generate or absorb reactive power. Thus, they are used to control the voltage or the reactive power. In our simulation, since we need a fixed DG output voltage, we used a voltage control model in order to investigate voltage stability issues [7] Static Synchronous Compensator (STATCOM) The STATCOM has been reported to improve the transient stability margin in power systems with DG integration of wind type [8]. STATCOM can be implemented to regulate the voltage as a shunt compensator for the WTIG. Figure 3: Generator Torque v/s Speed Stable Region [6] Figure 4: The WTDFIG model [7] 3

4 The shunt connected STATCOM is based on the vector control principle, the injected reactive current is controlled and regulated in a way to obtain the reference grid voltage. The basic STATCOM model is shown in Fig. 5. The STATCOM s main role is to control its terminal s voltage by managing the quantity of reactive power transferred from or to the power system. In the case if the system s voltage is low and the STATCOM is connected, it responds as a capacitive device by injecting reactive power. In the other hand, if the system s voltage is high it absorbs reactive power and acts as an inductive device. On the secondary of the coupling transformer shown in Fig. 6, a VSC is connected for the reactive power variation control. It uses forced-commutated power electronic devices such as GTO, IGBT or IGCT to convert the DC into an AC voltage. Fig. 6 reflects the STATCOM operation principles. It shows the active and reactive power transfer between the bus voltage and the voltage generated by the VSC [9]. The active and reactive power equations are: P = V1 V2 sinδ X, Q = V1(V1 V2 cosδ) X (1) The angle δ is zero during steady state operation mode since voltages are in phase. Thus P is zero and only reactive power will flow. The amount of reactive power is given by V1 (V1 V2) Q = (2) X In the used model, PWM inverters control the IGBT type VSC. AC voltage is derived from the DC source by the mean of Pulse-Width Modulation technique. Using filters harmonic voltages are cancelled. By controlling the modulation index of the PWM the VSC s output voltage is varied [9]. Fig.7 shows a block diagram of the STATCOM (single line) and a simplified block diagram for the control system. The control system mainly consists of: A phase-locked loop (PLL), Measurement systems measuring the d and q components of AC positive-sequence voltage and currents and Regulation loops consist of voltage and current regulators. To study the impact of the STATCOM on the DG from a stability approach, it is connected with the wind DG to the system and transient stability studies are performed. The impact of the STATCOM on the oscillations and induction generators stability will be observed. Figure 5: Basic STATCOM model [8] Figure 6: Operating Principle of STATCOM [9] Figure 7: STATCOM Block Diagram [9] 4

5 3. Simulation and Results In this section, the critical clearing time (CCT) factor is reviewed and its impact on the stability of an induction generator is highlighted. Increasing the stability of an induction machine is achieved by increasing the CCT factor. For this purpose, STATCOM and power electronics voltage source converter impact on the CCT margin is simulated. 3.1 Transient Stability Criteria: the CCT With the continuous increase in the diffusion of the wind farms in the electric systems as in Lebanon, the DGs impact on a power system is important to be analyzed. The DGs should ride through the fault according to the new grid codes [10]. During severe faults as a three phase fault, the electromagnetic torque decrease when the mechanical torque related to wind speed is considered to be constant. In this case the rotor shaft accelerates; hence it is important to analyze the speed impact. Critical clearing time CCT and critical speed CS are obviously the main factors on which the stability of DGs depends. Analytical calculation of critical clearing time is derived in [11]. T Critical = 2H w cs dw T r = m Wss 2H T m (w cs w ss ) (3) The slip factor determines the wind generator stability. During faults, the increases slip point at which the electromagnetic torque corresponds to the same amount as before disturbance is known the critical slip. If the disturbance is cleared beyond the stable point, a continuous increase in the rotor speed will be encountered whereas, the electromagnetic torque decreases. In this case runaway slip is denoted. The time duration starting from the fault time until the critical slip point is the CCT. Hence the CCT can be determined from the torque and rotor speed characteristic of the induction machine. For this purpose, the CCT of a single induction generator wind turbine was simulated using Matlab\Simulink. As shown in Fig. 8, an induction generator wind turbine from the SimPowerSystems library was connected to Bus 7 of the MV test network. The wind speed is considered constant at a value of 8m/s. The DG delivers 2 MW output power at steady-state. A three-phase fault was induced at the terminal of the DG. The STATCOM is disconnected. The simulation time is 20 seconds which is enough to investigate the transient behavior of the rotor speed. Fault is induced at t=2sec and the rotor speed is plotted in pu for various fault clearance time t= 3.4 s, 3.49 s and 3.5 s. Fig. 9 shows the response on the rotor speed for three-phase fault induced at the terminal of the DG and cleared for different time. It is obvious from the figure that at the fault clearing t=3.5 s the machine is unable to remain stable. Thus, the CCT is 1.5 seconds. Above this critical point the rotor will continue to accelerate indicating a runaway slip. By this mean the CCT of and induction generator can be calculated, which will be useful since we will be focusing on increasing this transient stability criteria. Figure 8: DG connected to Bus 7 Figure 9: rotor speed vs. time for various faults clearing time 5

6 3.2 STATCOM impact on transient stability margin Various scenarios are performed on the MV test Network to investigate the transient stability of the DGs connected to the network. Four classical WTIG providing each 4MW are connected to buses 4, 7, 9 and 10. The stator of these DGs is in straight connection with the grid. The total loads connected to the system are 45 MW and 10.5 MVars. Part of the power absorbed by the loads will be fed from the DG when they are connected. To investigate the stability of the wind turbine for a large disturbance, a three-phase fault is induced at bus 3. The fault was cleared at different time and the CCT was calculated. Not all the DGs have the same sensitivity to the fault; hence they don t have the same CCT. However, the CCT will be the smallest one which ensures that all DG remain connected and re-establish a normal operating point after a disturbance. The first scenario consists of finding the CCT for the DG of squirrel cage induction generator type connected to the grid without the STATCOM support. The simulation is repeated when the STATCOM is connected in order to investigate its impact on the transient stability margin [8]. The simulation time for this scenario is 10 sec. Fig. 10 and 11 represent the rotor speed versus time during a three-phase fault. The three-phase fault at bus 3 is induced at t=2 sec, and is cleared at t=2.9 sec in Fig.10 and t=2.95 sec in Fig. 11. It reflects the instability issue and a runaway slip is denoted. Thus, the critical time point is CCT= 0.95 sec (without STATCOM). The critical clearing time CCT is directly related to the critical speed of the rotor. The disturbance should be cleared before this critical time in order for the DG to remain stable and succeed in restoring a steady-state operating point. The four DGs are capable of re-operating in a stable mode after the disturbance was cleared at t=2.95 sec. When the fault clearing time is at t=2.95 sec none of the generator could re-establish a stable operation as shown in figure 11. In our simulation platform, the STATCOM has been connected to bus 3. To observe the effect of the STATCOM on the critical clearing time (CCT), the switch was closed, hence the STATCOM is connected and the three-phase fault was induced at bus 3. By investigating the fault clearing time it is found that when the STATCOM is connected, the CCT becomes CCT=1.15 sec. It is obvious that the STATCOM had increased the critical clearing time CCT by 200ms. Hence giving the machine more time to right through fault and remain connected and re-establish a stable operating point after the fault is cleared. During fault, the STATCOM have the capacity to control the reactive power transfer at its terminal. Hence achieves a voltage regulation mode. When the three-phase fault is induced, the system voltage drop, hence the STATCOM generates reactive power and act as capacitive device. Fig. 12 shows the voltage at STATCOM s terminal (top) and the reactive power generated by the STATCOM all along the simulation (bottom). Figure 10: CCT calculation for clearing fault time t = 2.9 s Figure 11: CCT calculation for clearing fault time t = 2.95 s 6

7 Fig. 13 focuses on the voltage behavior during the transient time of the simulation. Fig.13 (top) represents the voltage profile of bus 7 without STATCOM intervention whereas Fig.13 (bottom) for the STATCOM connected. We can realize that the STATCOM s advantage is re-stabilizing the voltage on the reference voltage 1 pu following a disturbance. Therefore assuring the voltage ride through capability for the DGs. 3.3 Impact of control methodology VSC In this section a robust control stability enhancement method is investigated. The DGs are replaced by the DFIG with AC/DC/AC converter. Rotor and grid side converter are VSC power electronic devices (IGBTs). Voltage control parameter has been picked up for this block and the reference voltage is selected. The simulation is run, and since the DGs are responsible of voltage regulation, the STTACOM is omitted from the platform. It is realized that DG with power electronics that uses control methodology are capable of stabilizing the induction machine, since the active and reactive power are controlled in a way to maintain the output voltage at a reference of 1 pu. Fig. 14 shows the response of doubly fed induction generator wind turbine with power electronics controllers. A steady-state operating point is succeeded after clearing the fault. In what concern the voltage, it re-stabilizes at 1 pu, the reference voltage. Thus when the fault is cleared, if none of the standard is violated, the DG with robust control methodology remain solidly connected to the grid. Figure 15 focuses on the voltage behavior during the transient time of the simulation showing the robustness of this strategy. 4. Conclusion Figure 12: Voltage and generated reactive power by STATCOM Figure 13: Voltage transient behavior without and with STATCOM In this paper, voltage stability and critical clearing time for DG were investigated. The main focus was on wind turbines used in distributed energy applications. Solutions for enhancing transient stability margin or increasing the CCT were proposed. Simulation results proved that the SATCOM can increase the CCT thus the fault ride through capability of the DG. Moreover, the STATCOM contributed in restoring the voltage to its initial reference point following a disturbance. However, power electronics converters that use forced-commutated electronic devices implemented with DG interconnection succeed in controlling the voltage and the reactive power remarkably. Hence, two proposed method were investigated to enhance the fault ride through capability and the voltage stability of a DG. The output power and voltage control dynamically achieved by the power electronics converters integrated in the DG makes it more flexible, and the stability margin was extended. In a distribution system where classical wind farms are connected to the grid, installation of a STATCOM is mandatory. 7

8 Nevertheless, when new DG power electronic based converters are being used, there is no need for the STATCOM. References [1] C. Lopes, A. C. Nascimento, J. P. A. Vieira, M. V. A. Nunes, U. H. Bezerra, Reactive Power Control of Direct Drive Synchronous Wind Generators to Enhance the Low Voltage Ride-Through Capability, in 2010 IREP Symposium. [2] M. Ziade, Technical Challenges to 24/7 electricity in Lebanon, available online at: electricity-in-lebanon/ [3] K. Rudion, A. Orths, Z. A. Styczynski, K. Strunz, Design of a benchmark of Medium Voltage DIstribution Network for investigation of DG Integration, in Power Engineering Society General Meeting, 2006 IEEE Conference, Montreal, Que. [4] S. Heier, Grid Integration of Wind Energy Conversion Systems, John Wiley & Sons Ltd, 1998, ISBN X [5] Alternative Energy tutorial, Wind Turbines using Induction Generators, available online at: /induction-generator.html [6] J. Vaidya, Advanced Electric Generator & Control for High Speed Micro/Mini Turbine Based Power Systems, in PowerGen Conference held in Orlando, Florida in December [7] N. Miller, J. Sanchez Gasca, W. Price, R. Delmerico, Dynamic modeling of GE 1.5 and 3.6 MW wind turbine generators for stability simulations, GE Power Systems Energy Consulting, IEEE WTG Modeling Panel, Session July 2003 [8] M. Molinas, S. Vazquez, T. Takaku, J.M. Carrasco, R. Shimada and T. Undeland, Improvement of Transient Stability Margin in Power Systems with Integrated Wind Generation Using a STATCOM: An Experimental verification, in IEEE 2005 International Conference on Future Power Systems. [9] N. G. Hingorani, L. Gyugyi, Understanding FACTS; Concepts and Technology of Flexible AC Transmission Systems, IEEE Press book, [10] M. Tsili, S. Papathanassiou, A review of grid code technical requirements for wind farms, IET Renew. Power Gener., 2009, Vol. 3, Iss. 3, pp [11] A. Abbaszadeh, V. Mortezapour, A. Zohoori, Analytical Calculation of Critical Clearance Time of Doubly Fed Induction Generator, in Environment and Electrical Engineering (EEEIC), th International Conference, Rome. Figure 14: Wind turbine behavior with control methodology Figure 15: Voltage Transient Behavior of DG with Control Strategy 8

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