Review on the SFCL Control Techniques in Grid System

: In this paper, the authors present a comparative study of inductive and resistive superconducting residual current limiters (SFCLs) from the perspective of current limiting and transient stability of the power supply system. Different types of SFCL can be used to reduce the magnitude of the fault current in a power system. The two most commonly used types are the resistive type (rSFCL) and the inductive type (iSFCL). The study aims here to analyze the performance of SFCL using various switching algorithms when a fault occurs in a simple high voltage (HV) network.


I. INTRODUCTION
A fault current limiter (FCL) is a device that limits the probable fault current in the event of a fault. In general, fault current limiters are superconducting fault current limiters. A residual current limiter (FCL) limits the amount of current flowing through the system and allows continuous, uninterrupted operation of the electrical system, in the same way that surge protective devices limit currents that are harmful to household appliances.

A. Concept of a DC Resistive Type SFCL
One type of SFCL resistor directly uses the transition from the superconducting state to the normal state that a superconducting material (SC) shows when the transport current exceeds the critical value [1].
In practice it consists of a non-inductive winding consisting of a superconducting wire or strip connected in parallel to an external shunt, which can be resistive or inductive. The external shunt provides an alternating path for the current during the fault and thus reduces the Joule heating of the superconductor. An external resistive shunt is advantageous from the point of view of the power supply system, because it does not delay the zero crossing of current and does not reduce the transition stability of the network [2].
Usually, the non-inductive winding consists of a two-wire spiral or other arrangement of pancakes. A superconducting channel, suitably cut on the surface to create a current path similar to that of a two-wire coil, can also be used to make a resistive SFCL [3].
To avoid the risk of hot spots, the superconductor must be in contact with a normally conductive matrix (as in the case of BSCCO and MgB2 composite tapes or wires) or a branch layer (as in the case of conductors coated with YBCO or BSCCO tube). The role of the matrix or shunt layer is to promote uniform propagation of the quench; therefore, they have a high thermal and electrical conductivity.  Figure 1 shows a circuit diagram of an SFCL-type resistor. Nonlinear resistance RSC is given by the parallel equivalent of the superconductor and the normal conductive matrix or shunt layer. The presence of the low resistivity material allows only a low value of the equivalent resistance even after the complete transition [4].
The only way to get an appropriate value for the SFCL resistor is to increase the length of the superconductor. However, this leads to an increase in AC losses to unacceptable values for high voltage applications where a sufficiently high resistance is required to keep the fault current at an acceptable level [10,11].
An ideal rectifier of the SFCL type: it consists of a direct current source integrated in a diode bridge (see Fig. 1). 2 a).
Due to symmetry, the direct current I0 is divided into two equal parts, which flow through the pairs of diodes D1-D3 and D2-D4. Now consider a positive iSFCL current through the device. Due to the fact that all diodes are forward biased, this current splits into two equal parts which flow through the diode pairs D1-D4 and D3-D2 respectively, thus bypassing the current source. The total voltage across the device is just given by the sum of the voltage drops across the diode pairs, which is negligible; therefore the SFCL has zero impedance.
In this situation diodes D1 and D2 carry a current i D1D2 i D1D2 = I0/2 + i SFCL /2 ; while diodes D3 and D4 carry a current i D3D4 When the current of the iSFCL device tries to exceed the direct current I0, diodes D3 and D4 are reverse biased and cut the current. The direct current source is then connected in series to the protected circuit and maintains its current at the value I0. The SFCL behaves as an ideal current source with infinite equivalent impedance.
In principle, the inductance could also be implemented using an ohmic copper coil; However, it is possible to use a superconducting coil to avoid permanent losses. The circuit diagram of a more real SFCL type rectifier is shown in Figure 2 (b). Since the superconducting coil operates in direct current, the only losses are due to the thermal revenues of the power lines and the cryostat, and are considerably reduced compared to the SFCL type resistance. Also, the superconductor does not turn off as long as the current is limited. In fact, during a fault, there will be a small overcurrent with respect to the constant value I0 in the coil. The recovery time of such a limiter is immediate. The practical difficulty of the SFCL type rectifier is the implementation of the DC voltage source [6]. To avoid this problem, the configuration without the DC voltage source shown in Fig. 2 (c) has been widely considered. There are some advantages to using these devices:  SFCL is applied with the distribution generation  SFCL reduce the level of short-circuit current during a fault.  No external control s needed.  Rapid response.  SFCLs are invisible in normal operation and do not introduce unwanted side effects.  SFCLs are economically competitive with expensive conventional solutions.  Negligible loss during normal system operation [12].

B. Faults in grid system
An electrical grid (EPG) is a dynamic system based on four main operations: generation, transmission, distribution and control [5]. Technological developments over the past decade, notably through the increased use of information and communication technologies (ICT), have exposed EPGs to a whole new set of threats [7]. Like any system, an EPG is not completely error free. An error can occur anywhere on the network, including natural causes, operational errors, cyberattacks, or physical attacks [8].
The errors that can occur at different levels of the system can be classified as follows: 1. Physical Device / Component Errors: These errors occur when a physical item is malfunctioning. The new network system model should include the modeling and identification of actual network conditions, as well as the collection and processing of heterogeneous information from different information systems. Taking into account the classification models, network systems should be able to identify fault conditions using the decision function, which is interpreted as the reliability of the classification. The power grid failure model is of the utmost importance for distinguishing faults from standard operating states. Network and microgrid protection systems (μGs) take into account the Internet of Energy (IoE) concept, used for the operation and coordination of protection to maintain an efficient and dynamic infrastructure. III.

PROBLEM FORMULATION
The demand for electricity is increasing with the arrival and creation of smart cities and Industry 4.0. Fault analysis is important for improving performance and minimizing interruptions in the intelligent power system. Detecting, locating and correcting faults at all levels of the fuel system is essential for the fuel system to continue to operate normally. This activity requires intelligent control in order to be able to work quickly and efficiently. This investigation covers various aspects of fault detection in network systems using SFCL. The aim is to indicate topics relevant to future development in order to bridge the gap between SFCL and future defect detection techniques, which may include AIbased detection and restriction.

IV. PROPOSED TECHNICAL METHOD
The methodology suggested the use of some AI-based algorithms to switch the SFCL device, which should result in a more efficient improvement of the transition stability of the power system for symmetrical and asymmetrical failures when using DC resistive SFCLs. Reduction of large voltage drops and high level of current in the power system model, thus reducing the power loss in the system, thus improving efficiency and reliability. Work should focus on comparing voltage and current situations without using SFCL, then on a system with an SFCL resistor type driven by an AI-based control algorithm to minimize fault current within a minimum time frame.

V. ARTIFICIAL INTELLIGENT CONTROLLER
Genetic algorithms, fuzzy logic, and neural networks are artificial intelligence-based digital computing techniques that are popular in the field of computing. However, more and more applications based on these new approaches to digital computing are developing for practical applications in science and technology.
Observers or estimators based on artificial intelligence techniques lead to better dynamics and accuracy and are more robust. Your deliveries are very good even with large deviations in the machine parameters. However, the need for perfect knowledge of the adjustment or estimation system and the lack of specialist knowledge of the system limits current applications to a very specific area.

VI. FUZZY LOGIC CONTROLLER
Fuzzy logic allows us to formulate mathematically inaccurate concepts and derive precise actions from fuzzy rules resulting from observations. The most common tool used in fuzzy logic applications is the fuzzy rule base. A fuzzy rule consists of three phases: fuzzification, inference and Defuzzification.
The fuzzy controller consists of two input variables, the error (e) and the error variation (de / dt), and an output variable. The error of the input variable results from the difference between the reference models with the actual rotor speed. The membership function for determining the input and output variables is determined based on the experience of the system failure [13].

VII. ARTIFICIAL NEURAL NETWORK
Neural modeling is chosen to circumvent the parametric variations of the mathematical model of the engine. First, the neural network is taken offline; In other words, the network elements are used after the application of all training pair data for a fixed network is complete.
The training is then carried out online so that the neural model can be adapted at any time. This type of training allows you to design adaptive control. The neural network can describe the behavior of a nonlinear dynamic system without having to know its parameters.
The neural network used for education has a multilayer structure with a hidden layer activated by the sigmoid function, while the output layer is activated by a linear function. Its programming is performed by a backward gradient propagation algorithm with an adaptive learning rate. The general principle of learning algorithms is based on the minimization of a quadratic cost function of the differences between the network outputs and the desired values. Several other optimization and learning algorithms are associated with artificial intelligence techniques, which can be used in conjunction with the SFCL model for error detection and elimination.

VIII. CONCLUSION
For grid systems to function efficiently, it is important to understand the main types of power grid outages and the benefits of the production resources available in the system in the event of an outage. This article looks at different types of errors that can occur in the power system. The underlying fault management approaches offer various fault detection and localization techniques for intelligent grid systems using SFCL, which is controlled by artificial intelligence algorithms for rapid detection and elimination.