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Hardware and software integration as a realist SCADA environment to test protective relaying control Daniel Martinez, David Celeita, Diego Clavijo and Gustavo Ramos Department of Electrical and Electronic Engineering Universidad de los Andes Bogota D.C., Colombia Email:
[email protected] [email protected] [email protected] [email protected]
Abstract—As the need for analyzing complex power systems increases, simulation tools make possible adding coupling strategies to interface simulations with Real-Time (RT) and Hardware in the Loop (HiL) techniques. This paper introduces a novel hardware and software integration to reproduce a real-time performance environment of power system simulations, especially focused on protective relaying control adjustments and training tools. The IEEE-9 bus system and a real validated model of a Colombian transmission systems section are presented; both cases are implemented in the platform and reproduced with the aim of evaluating its performance. Finally, the different possibilities with the developed tool and future developments are presented. Index Terms—Power system control, SCADA systems, Power system simulation, Power system protection, Real-time systems.
I. I NTRODUCTION A SCADA system solution is mainly used to provide realtime (RT) information about the operation of electric power systems [1]. Most of the power systems need to collect data at a central location, from a range of multifunctional intelligent electronic devices (IEDs) located in the field for performing a comprehensive analysis of equipment to make a decision [2], [3]. The HMI of a SCADA system is based on some measured remote points to be monitored and eventually controlled, in which communications are expected to be operated by a human operator. The primary purpose of a SCADA interaction are [4]: • Data acquisition of AC voltages and currents, powers, frequency, power factor (PF) value for metering, limit checking, scaling, and indication supervision. • Reports the status of relay contact points and controls circuit breaker ON/OFF. • Alarm handling in case of limit violation, acknowledgment facilities, and control supervision. • Report facilities of the current and historical data storage availability. • Fault and event data report gathering for fault analysis. • Changing/checking the settings of intelligent RTUs remotely with ease.
•
MIMIC diagrams for an overview of the status of the power system.
Thus, the research to interface with SCADA systems due to the fast changing scenario in RT power systems, the multilevel dynamic modeling of power system elements appears as a modern solution. This new context brings important challenges involving rapid prototyping and validation of power system controllers, the coupling with external or user defined models and the use of advanced algorithms capable of analyzing the complete range of transient phenomena in electrical power systems. Such developments are designed to improve simulation testing and laboratory platforms for more demanding Hardware in the Loop (HiL) testing [5], [6]. It is necessary to set up a power system laboratory which integrates the use of SCADA systems [7]–[9]. The design emphasizes an operator training simulator and powerful graphical interfaces capable of handling big amounts of data which support decision making more accurately with flexibility, scalability, realism and fast simulation tools [10]–[12]. This paper focuses on a hardware/software coupling platform between a developed SCADA system with PowerFactory for large-scale stability simulation (RMS) running in a RT testing architecture. Since this application interacts with precision amplifiers in a power HiL set-up, hard time constraints in the order of milliseconds must be fulfilled; therefore, a robust dedicated hardware with an embedded system and available FPGA is included to reproduce analog signals of voltage and current. This architecture allows improving the performance of a long-term transients simulation analysis and monitoring, as an alternative to achieve a realistic simulation. The paper is organized into four sections: first, the description of the integrated simulation algorithm. Section II presents the parallel programming methodology. Then, the results using different test systems are presented, and finally, further work and conclusions are presented.
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x x x x x Power system model – 9 nodes Anderson – Infeed effect analysis
x x
Voltage Current Frequency Active power Reactive power Breaker status Time stamp
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OPC CLIENT Shared variables
OPC SERVER
Distributed programming methodology Update rate 50ms
Precision Load
TCP IP Protocol Subnet
FPGA Digital / Analog I/O
Power amplifier
Current signal
Matrikon OPC server for simulation and testing Control Signals
Relay
NI cRIO 9082
Voltage signal
Voltage amplifier
Figure 1. General framework of the RT HiL integration with PowerFactory and National Instruments tools
II. D ESIGN OF INTEGRATED SIMULATION Fig. 1 illustrates the general design of this framework and presents six different modules to integrate the hardware and software. The required equipment and software tools are presented: • A computer with DigSilent PowerFactory, MatrikonOPC Server for Simulation and NI LabVIEW. • A RT embedded system and FPGA - NI cRIO 9082. • A power amplifier NF 4510 the current signal. • A precision load NF AS-513 to control the amplified current. • A basic voltage amplifier 10V / 120V. • A protection relay to manage trip/close, event recording, voltage and current monitoring. A. Power system co-simulation The different mechanism which exists to interface the power system model and simulation engine of PowerFactory with other models, simulators or applications are showed in Fig. 2 [6]. These interfaces open different ways for co-simulation, RT simulation for controller HiL testing set ups or automation and control of simulation.
data transfer is automatically synchronized with the RMS simulation. The OPC data exchange has to be carried out through an explicit DPL command charged to build data points, which clients can communicate (inputs, outputs, and external measurements data). Some interesting functionalities of different applications in which could be applied the coupling of PowerFactory by OPC Server are illustrated in Fig. 3. These applications allow a bidirectional data exchange through the use of OPC Tags. The data type that can be imported or exported are listed as follows [13]: • Import – Update of operational data in PowerFactory model. – Operation actions (e.g. breaker status, tap position). – Import of measured network snapshot for State Estimation • Export – Update of SCADA with calculation results. – External DAT Measurements (e.g. voltage, current, powers, frequency, power factor).
OPC Server
OPC Client
Topology Status Data State Variables Execution Commands
Online State Estimation Simulation Mode Dispatcher Load Flow Switching Validation Training Simulator Controller Development Network Security Analysis Stability Analysis Spinning Reserve Allocation
Figure 3. PowerFactory OPC Interface
B. Server/client model Figure 2. Overview of the coupling interfaces provided by PowerFactory
OPC (OLE for Process Communication) client interface is suitable for the implementation of a SCADA system because
OPC is a standard with a set of specifications to guarantee security and reliability data exchange for automation and industry applications. These specifications define the interface between client/server that allows access to data in RT. Data transfer includes different values related to time and a certain
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amount of information, which is defined by the OPC DA layer (Data Access). This Layer is based on the Microsoft Windows technology using COM/DCOM (Distributed Component Object Model) for data exchange between software components [14].
III. S YSTEM ARCHITECTURE AND PROGRAMMING STRATEGY
The fact of establishing a HiL simulation technique between the hardware and software components, it is necessary to recognize the primary agents in this design: the analyzed power system simulation, an algorithm that makes control decisions depending on the events that occurred and the embedded system that generates the measurement signals in RT. Since processing each one of these actors and since all those events happen at different speed rates, a distributed and parallel programming methodology is aimed to ensure the RT performance of the monitoring system.
Figure 4. OPC client/server link
The specification describes the OPC-COM Objects and their interfaces implemented by the OPC Server which determines a relationship with multiple clients; therefore, this communication feature between DigSilent PowerFactory software and NI OPC clients in LabVIEW is established through the freeware MatrikonOPC Simulation Server as shown in Fig.4. The OPC Server must be configured to transfer data bidirectionally based on a HiL testing. Subsequently, the configuration for MatrikonOPC Simulation Server which is used from data points organized in groups called OPC tags for the associated clients could exchange data to read and write.
Figure 5. Shared variable engine - SVE as OPC client
The PowerFactory implementation is performed through an OPC Client configuration, which is set to an online model for information exchange at the stipulated simulation frequency. Indeed, from PowerFactory OPC a communication link is established to the External Data Objects, and by programming DPL (DIgSILENT Programming Language), an OPC tag identification format is assigned to each input/outputs variables [6]. The OPC output tags are referred to measurements of voltage, current, active power, reactive power, power factor, breaker status, frequency, and timestamp for each element of interest of the power system; in parallel, the input tags are assigned to signaling switches in response to failure events. NI LabVIEW allows a robust integration with OPC DA systems through a plug-in called OPC Client I/O Server which is associated with the service Shared Variable Engine (SVE). This feature allows linking the OPC tags from an OPC Server to Shared Variables; therefore, the SVE acts as an intermediary between the OPC server application providing an easy way to read and write ”Bound Shared variables data” on the OPC tags as shown in Fig.5.
Figure 6. Real-time communication structure
The algorithm is optimized by separating it in independent subsystems, and each subsystem has its dedicated hardware resources. As a result, the high performance of the whole system is enhanced due that the task is developed in a parallel software computing and distributed hardware architecture [15]. The main agents of this platform are shown in Fig.6. A full calculation of the load flow is done during each time step, dynamic simulation such as fault events can also be programmed. The power system simulator sends and receives data at the next time step; then the first subsystem consists in the power system SCADA, which was developed taking into account a parallel computing programming in NI LabVIEW. Through de OPC client-server communication, the SCADA system has to upgrade the MIMIC diagram and stores the current measurements value according to the simulated system. The data exchange interface is the second agent of the platform. It organizes and synchronizes information packages between PowerFactory and the NI LabVIEW embedded system. The parallel subsystem structure has to communicate using high-speed interprocess TCP link with the distributed
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embedded system in charge to reproduce in RT the external DAT measurements of interest. This hardware/software integration is a versatile way to work with protective equipment; devices could be relays, IEDs, merging units, PMUs, and so forth.
(a)
Loop Rate = 20Hz User Interface Data Logging TDMS Database OPC Interface
Loop Rate = 250Hz Multi-core Deterministic Simulation Remote Interfaces
(b)
Loop Rate = 1MHz Measurements Analog/Digital I/O Safety Checks
Figure 7. Distribuited hardware architecture (c)
The main characteristic of RT hardware is the concurrence of process (see Fig.7). The FPGA allows defining hardware to attend processes in deterministic time cycles, so the parallelism between different tasks like data acquisition or signal generation can be handled by hardware. The coupling between agents is made using strategies like user events, state machines, OPC and TCP link. The final prototype of the implemented RT simulation platform to integrate PowerFactory models and HiL techniques are shown in Fig.8. IV. RT SIMULATION OF THE TEST SYSTEMS Once the SCADA system has been developed, two testing scenarios are implemented. The aim of both is to compare the performance regarding the computing time required to accomplish different simulation events.
(d)
Figure 9. Results for steady state RT simulation of a three phase fault (Line 5-7) in IEEE 9 bus system (a) Powers from generator 1 in PowerFactory (b) Powers from generator 1 in LabVIEW RT (c) Signal generated in RT in prefault and fault (d) COMTRADE file recorded of protective relay
giving all external measurements. The typical application was related to using the FPGA target to reproduce voltage and current variables; nevertheless, the input parameters of this sinusoidal analog signals come from the data exchange (voltage RMS, current RMS, and frequency). Also, digital inputs were connected from the relay to the cRIO 9082 to define trip, and close signals and digital outputs communicate whether the breaker from the power system simulation is open or closed.
A. The validation process: IEEE 9-bus system Due to its nature and topology, the 9-node system is suitable to assess the performance of a power system using HiL testing. It allows many dynamic and transient studies among its elements. A time domain simulation is set for a model at steady state (RMS) under balanced conditions of the power system [16]. A load flow is performed to ensure convergence of the system, and this process determines the initial conditions of the variables; then, events related to different faults in the power system could be programmed to integrate power system analysis to study selected variables of interest. Finally, the simulation runs, and the user can access the results. The OPC communication is established with the SCADA system, which has the task to update the front panel interface with the current values of simulation Active power, reactive power, and frequency variation are plotted in every simulation step; breaker status, voltage, and current are shown in each bus, time stamp simulation is presented too. At the same time, the HiL methodology is included from the RT signaling generation and acquisition. The SCADA system is linked via TCP with the CRIO 9082 embedded system
Figure 10. Flow chart for test case
The case is assessed with a three-phase fault event at line 5-7, the purpose is to analyze the power generation behavior in generator number one of the system, and based on HiL testing reproduce the open/close status of protection relay. Fig. 9 summarizes PowerFactory and LabVIEW RT results and the consistency of COMTRADE files acquired with a relay in HIL testing.
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Figure 8. Implemented real-time simulation platform
Table I PARAMETERS OF EACH SUBSTATION Substation
Table II PARAMETERS OF EACH LINE
SC 3ph [kA]
SC 1ph [kA]
R0/X0
R1/X1
Line
Distance [km]
Impedance [Ohm]
Imax [kA]
A
11.768
14.03
0.004
0.007
A-B
81.13
2.7341+j30.1804
1.44
B
0.837
1.099
0.013
0.171
B-C
74.95
2.5708+j28.0238
1.44
C
4.244
5.202
0.445
0.029
C-D
14.96
0.6642+j7.1853
0.96
D
4.189
3.54
0.231
0.083
B. Case study: Colombian transmission line A platform test was conducted using a reduced model from a central region of the Colombian national grid. The big database model of the complete transmission system is simplified to focus on a small portion of the grid, therefore to optimize computational simulation performance. The full test case assessment is shown in Fig. 10. The case study has four substations which are connected with three transposed transmission lines. The system has an equivalent distributed generation at each substation; therefore, it has an interesting feature for protection coordination studies. Due to these power sources, infeed currents must be taken into account in the protection schemes. The implemented model is shown in Fig. 11. The voltage level of the case study is 230 kV, with a maximum power flow of 243 MVA. The equivalent and simplified system parameters are shown in Table. I and Table. II. It is worth noting that the positive and negative sequence parameters of impedance are assumed equal to each substation equivalents. C. Case study: Model validation First, the equivalent system is implemented in PowerFactory 15.1. The model validation is performed on ETAP 12.6. Subsequently, a load flow study and short circuit study with three-
Table III P ERCENTAGE ERRORS BETWEEN P OWER FACTORY DATABASE MODEL AND EQUIVALENT ETAP MODEL Percentage errors Load flow
1%
Three phase short circuit
1%
Single phase short circuit
2%
Total average
1%
phase and single-phase for various points in the system are performed (IEC 60909 method). Both systems are compared with real database information. In Table. III the percentage errors are presented regarding the information of the database and the equivalent model. Regarding the load flow study, the values of voltages and angles at each of the four buses are compared. Additionally, this comparison is also made with currents, power, and losses in each transmission line. For short circuit studies, the current is taken at the point of failure. Moreover, on the short circuit study, the magnitudes of three and single phase faults at 1%, 20%, 50%, 80%, and 99% percent of each line are compared. The difference between the values found in the database and the case study model is equal or less than 2%, so the simplified model is completely validated.
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Figure 11. Case study model with a three phase fault at 50% of line A B
D. Real-time testing of distance protection coordination and infeed effect The next step after model validation is to test suitable applications such as distance protection coordination, which is a constant concern for protective relaying control engineers. Furthermore, considering the system topology and the equivalent short circuit arising at each substation, additional calculations were needed to find the parameters given the infeed effect present in this example. According to the IEEE standard C37.113 2015 [17], the infeed effect for transmission systems is the presence of power supplies for short circuit currents between the distance relay protecting a transmission line and the failures. Exemplifying a drawback infeed shown in Fig. 6, it illustrates the shortcircuit currents from the relay protecting the line A B at the substation A; as result of a fault on the line B C, there are input currents from a substation A and substation B. The contribution of the second substation will make the relay measures a lower fault current from the first substation, as shown in (1): VA = ZAB × IAB + ZB × IBC
(1)
The relay also will identify a farthest short circuit distance, by following equation (2): IBC (2) × ZB ZAparent = ZAB + IAB
Table IV G ENERAL PARAMETERS OF PROTECTION REACH AND ACTIVATION TIMES TO COORDINATE THE CASE STUDY RELAYS
Protection zone
Reactive reach [% Regarding the protected line]
Activation time [Seg]
Zone 1
0.8 × ZL
Instantaneous
Zone 2
ZL + 0.5 × (1 + K) × ZAL
0.4
Zone 3
ZL +0.5× (1 + K1 )×ZSAL +0.5× (1 + K2 ) × Z2SAL
1
Reverse
−0.2 × ZRL
1.5
between the short-circuit current measured by the relay and the total short circuit current at different distances for each line. After finding these relations proceed to the configuration of the relays to cover the ranges proposed above line correctly. Bookstore 7SL32AC Siemens Power Relay Factory, for which the parameters in Table. IV were considered in the configuration of each protection zone is used. Where ZL is the line impedance, K is the infeed factor as shown in equation (3), ZAL is the adjacent line impedance, ZSAL is the shortest adjacent line impedance, Z2SAL is the second shortest adjacent line impedance and ZRL is the reverse line impedance.
Therefore, the failure may be mistakenly associated with a superior protection zone with activation times much higher than necessary. Given the relationship between fault currents, the infeed factor is given in equation (3), which relates the current in remote substations with the current in the configured substation relay: K = Inf eedF actor =
IBC IAB
(3)
However, to mitigate the drawbacks of infeed effect, additional short circuit studies are needed, to know the relationship
Figure 12. Distance protective diagram of the case study
Finally, the protections assistant of the power system sim-
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Table V P ERFORMANCE OF THE OPC UPDATE
Client 1
Items
Changes / second
Items / second
48
20
960
ulation software is used to set the correct configuration of the coordinated relays. In Fig. 12, the diagram of activation for each protection system is shown, where the cover zone of each line is observed, and its activation time respectively. In this chart, there is no overlap between any of the times of the relays for each zone, so the selectivity of protections is ensured taking into account the infeed effect. Also, as an example of the right system protection, there is an R / X diagram shown in Fig. 13. The relay at substation A which protects the line A B, identifies a single-phase fault at 150% of line and allocated to zone 2.
Figure 13. Example of R/X diagram of the protection relay of Line A B at substation A (150% single phase fault)
E. Simulation Results The proposed case is tested on the developed hardware/software architecture, with the fundamental purpose is to assess the RT platform efficiency and the HiL methodology for protective relay time response. Also, all functions of the SCADA system are carried out to analyze the computing performance and demonstrate a distributed architecture framework from embedding processing components. It is assumed that there are four substations in the power system, in each substation, there are 6 points (component units) needed to be supervised. The PowerFactory client application defined and added 48 item (read/write tags) to the server, and requested the server to update the SCADA client application at a rate of 50 milliseconds per tag. It was programmed the data source such that all the data was constantly changing (worst scenario). The data type of all elements, in this case, was four byte-signed integer and boolean. The result (see Table. V) was that the server was able to update almost a thousand items per second continuously. Furthermore, the results reveal that for each group of substation data points, the computing hardware processor of the PC mentioned above required around 20% to execute the data exchange routine, it indicates when the system complexity increases at the full length of data the CPU use rises significantly.
(a)
(b)
Figure 14. (a) COMTRADE file of a three phase fault in zone 1 in RT (Colombian case study) (b) COMTRADE file of a three phase fault in zone 2 in RT (Colombian case study)
Another important issue is related to the RT assessment and HiL architecture to analyze the protective relay response because data exchange is made around 50 milliseconds (the lowest reached), the first and second protection zone are possible to detail because their activation time is under the platform capabilities. COMTRADE files of the RT simulations for faults in zone 1 and zone 2 can be seen in Fig. 14, where is displayed the maximum simulation range that the platform could achieve. The SCADA system works as the core of the hardware/software platform; it was structured taking into account RT and study-mode processes. In Fig. 15 is shown the SCADA features, the main characteristics of the system are: • RT Processes – Interface with PowerFactory through OPC interface. – Ability to obtain the values of various quantities such as real and reactive power, current, voltage, frequency, power factor, and circuit breaker position. – Scan rate is every 50 milliseconds for generation and interchange data. – Builds the RT database and each simulation step saves RT information for archival purposes. – Input data update the MIMIC diagram and HMI interface. – TCP link with embedded system for HiL testing purposes. • Study-mode Processes – Report of historical measurements and event statistics. – Bar and signal plotting for big data analysis. – Time Stamp information for events details. – Academic training V. C ONCLUSIONS AND FURTHER WORK This work presented a full framework to simulate power systems simulations in RT with HiL techniques; this simulation platform is a modern solution with low-cost hardware/software integration that successfully linked PowerFactory with National Instrument Tools. The case study is mainly focused on transmission systems, but it is notable that the proposed framework is feasible to work with any previously validated model. The 9-node system was studied in normal operating condition and failure events
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Figure 15. SCADA System functionalities
in the line 5-7. A second validation was completed using the model of a real Colombian transmission line for distance protection with infeed effects. Results in RT were consistent, and the inclusion of real protection equipment demonstrates the versatile feature of this framework to apply a HiL architecture. This model highlights the potential for many utility companies which already have running models that can utilize this framework to assess multiple scenarios, such as modernization equipment including smart grid features in the existing infrastructure. Moreover, this kind of architectures allows the high performance of laboratories able to include a lot of application studies and operator training facilities. Further work is expected to integrate more hardware devices and allow the study of bigger systems with real database models. This development expands the scope to practice endto-end testing, protective functions validation, professional training, academic courses laboratories, integration of interoperability protocols within a laboratory infrastructure, settingless protections, and virtual relay design. R EFERENCES [1] Ce Zheng, Yimai Dong, O. Gonen, and M. Kezunovic, “Data integration used in new applications and control center visualization tools,” in IEEE PES General Meeting. IEEE, jul 2010, pp. 1–7. [2] A. Apostolov, “Protection operation analysis in smart grids,” in 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013). Institution of Engineering and Technology, 2013, pp. 1399–1399. [3] M. Kezunovic and X. Luo, “Automated analysis of protective relay data,” in 18th International Conference and Exhibition on Electricity Distribution (CIRED 2005), vol. 2005. IEE, 2005, pp. v3–74–v3–74. [4] S. C. Savulescu, Ed., Real-Time Stability Assessment in Modern Power System Control, ser. Mohamed E. El-Hawary. Wiley-IEEE Press, 2009. [5] U. C. Chukwu and S. M. Mahajan, “Real-time management of power systems with v2g facility for smart-grid applications,” IEEE Transactions on Sustainable Energy, vol. 5, no. 2, pp. 558–566, April 2014. [6] F. M. Gonzalez-Longatt and J. L. Rueda, Eds., PowerFactory Applications for Power System Analysis, ser. 1612-1287. Springer International Publishing, 2014.
[7] C. Zambrano, C. Trujillo, D. Celeita, M. Hernandez, and G. Ramos, “Gridteractions: Simulation platform to interact with distribution systems,” in 2016 IEEE Power and Energy Society General Meeting (PESGM), July 2016, pp. 1–5. [8] D. Celeita, M. Hernandez, G. Ramos, N. Penafiel, M. Rangel, and J. D. Bernal, “Implementation of an educational real-time platform for relaying automation on smart grids,” Electric Power Systems Research, vol. 130, pp. 156–166, 2016. [9] S. Brahma, J. De La Ree, J. Gers, A. Girgis, S. Horowitz, R. Hunt, M. Kezunovic, V. Madani, P. McLaren, A. Phadke, M. Sachdev, T. Sidhu, J. Thorp, S. Venkata, and T. Wiedman, “The Education and Training of Future Protection Engineers: Challenges, Opportunities, and Solutions,” IEEE Transactions on Power Delivery, vol. 24, no. 2, pp. 538–544, apr 2009. [10] J. D. Pico, D. Celeita, and G. Ramos, “Protection coordination analysis under a real-time architecture for industrial distribution systems based on the std ieee 242-2001,” IEEE Transactions on Industry Applications, vol. 52, no. 4, pp. 2826–2833, July 2016. [11] D. Celeita, J. D. Perez, and G. Ramos, “Virtual relay design for feeder protection testing with online simulation,” in 2016 IEEE Industry Applications Society Annual Meeting, Oct 2016, pp. 1–7. [12] J. Ren and M. Kezunovic, “Modeling and simulation tools for teaching protective relaying design and application for the smart grid,” 2010 Modern Electric Power Systems, pp. 1–6, 2010. [13] DIgSILENT, PowerFactory SCADA Interface and Application, DIgSILENT GmbH, August 2015. [14] Data Access Custom Interface Standard, OPC Foundation Std., March 4 2003. [15] L. Kang and L. Yang, “A Distributed and Parallell Computing Framwork for SCADA Application in Power System,” in 2010 International Conference on Electrical and Control Engineering. IEEE, Jun 2010, pp. 2597–2600. [16] P. Kundur, Power System Stability And Control, 1st ed., ser. Epri Power System Engineering Series. McGraw-Hill Education, January 1994. [17] “IEEE Guide for Protective Relay Applications to Transmission Lines,” IEEE Std C37.113-2015 (Revision of IEEE Std C37.113-1999), pp. 1– 141, June 2016.
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