Abstract: In power systems, when synchronous generators experience loss of excitation, overload, or minor or major disturbances, system stability may be compromised, leading to out-of-synchronization and generator tripping, resulting in significant power deficits and economic losses. Therefore, seeking a better resynchronization control measure is of great practical value. This paper proposes a fuzzy controller to implement this control strategy based on the principle of resynchronization with discontinuous control in multi-machine power systems. Its superiority and effectiveness are verified through digital simulation. Keywords: out-of-synchronization; resynchronization with discontinuous control; fuzzy controller [b]1 Introduction[/b] Maintaining synchronous operation of generators in a power system is a necessary condition for the normal operation of the power system. Therefore, the concepts of static and transient stability of a power system are based on whether any generator in the power system loses synchronous operation. In a power system, once a generator enters asynchronous operation, it should be immediately disconnected to maintain the normal operation of other parts of the power system. However, due to the increasing capacity of power systems, the system has a large reactive power reserve, especially after the widespread adoption of fast excitation regulation systems and other automatic devices, providing an objective possibility for short-term asynchronous operation of generators and rapid resynchronization. Practice has shown that short-term asynchronous operation is permissible in many cases and will not lead to serious consequences for the operation of the power system. However, asynchronous operation can only be regarded as a temporary abnormal operation or a transitional process before entering normal operation. It is hoped that after a certain period of time, the generator can be pulled into synchronization through manual intervention or the action of automatic devices to restore or enter normal operation. This requires determining the possibility and conditions of entering synchronization from asynchronous operation and studying specific measures to ensure synchronization. During asynchronous operation after generator loss of synchronism, appropriate control should be taken for the generator to quickly pull it into synchronization with small oscillations and small slip. The control methods used in the past include: ① setting the speed governor droop coefficient to reduce the output of the prime mover; ② short-circuiting the excitation circuit after loss of synchronism and then re-energizing the excitation at an appropriate time after entering steady-state asynchronous operation to pull it into synchronization; ③ time-optimal control; ④ nonlinear parameter optimization; ⑤ piecewise linear optimal control, etc. Reference [3] proposed a resynchronization additional discontinuous control strategy, which is a different control measure adopted according to different stages of the process, and has good robustness and adaptability. Furthermore, the control law is simple, easy to implement, and convenient for engineering applications. Digital simulation studies and dynamic simulation experiments using an online controller composed of micromechanical components demonstrate the feasibility and practicality of its principle. Based on the principle of resynchronous discontinuous control, this paper further proposes a fuzzy controller control method based on resynchronous discontinuous control, which can achieve real-time online control. Digital simulation results in single-machine-infinite loop systems and multi-machine systems demonstrate that this control measure has good control performance, a simple control method, and adaptive characteristics. [b]2 Brief Description of the Principle of Resynchronization Added Intermittent Control[/b] The specific principle analysis of the resynchronization added intermittent control strategy can be found in references [3-5]. Its control law is briefly described as follows: (1) Resynchronization excitation control ① When a step loss is detected, the excitation voltage is made to reach the positive peak value in order to increase the electric power and pull it into resynchronization as soon as possible; ② When the slip crosses zero, the excitation voltage is made to reach the negative peak value in order to reduce the electric power and prevent slipping through the synchronization; ③ When the generator accelerates again, when an excitation control signal proportional to the acceleration is applied, the damping torque is increased to prevent resynchronization failure; ④ When the generator decelerates again, the additional intermittent excitation control is cut off, and only the conventional AVR works. 2) Resynchronization Fast-Closing Steam Valve Control ① When a loss of synchronization is detected, the steam valve is quickly closed to reduce mechanical power and pull the generator back into synchronization as soon as possible; ② When a zero slip is detected, the steam valve is opened relatively quickly to increase mechanical power and prevent slipping through synchronization; ③ When the generator accelerates again, a control signal proportional to the acceleration is applied to the governor input to increase the damping torque and prevent resynchronization failure; ④ When the generator decelerates again, the additional control is discontinued, and only the governor operates. [b]3 Principle of Fuzzy Controller[/b] The fuzzy structure of the fuzzy controller consists of three parts: two inputs, a fuzzy controller, and one output. The fuzzy controller structure for implementing the resynchronization additional discontinuous control principle should consist of four fuzzy systems, each completing one stage of this principle. Fuzzy inference uses the Mamdani method, and defuzzification uses the median method. To implement the additional discontinuous control, the fuzzy controller should consist of four fuzzy sub-controllers, each completing one process stage of the additional discontinuous control. Figure 4 is a schematic diagram of the entire fuzzy controller structure. As can be seen from the figure, the four controllers correspond to four control stages, and the output of each controller, in addition to the control operation, also has the effect of the previous controller stimulating the next controller (only the first three sub-controllers have this effect). Therefore, the control rules of these four sub-controllers are not the same, and thus the reasoning process is also different. For the first three controllers, the following three functions need to be realized: control operation (satisfying the control conditions), no action (under normal circumstances), and stimulating the next fuzzy controller (when the above conditions are not met). The fourth fuzzy controller only needs to complete the first two functions. Regarding the conditions for controller operation, the latter three fuzzy controllers can only operate when they meet the fuzzy reasoning conditions, and they can only implement the operation of this controller when the excitation state of the previous fuzzy control is true. Both conditions are indispensable. [b]4 Simulation Results Analysis[/b] 4.1 Single-Machine-Infinite System and its Simulation Results Based on the fuzzy control controller proposed in this paper, the MATLAB simulation tool was used to perform digital simulations of the single-machine-infinite system and the multi-machine system to simulate system instability. The selection of the generator and its excitation system model parameters is shown in the appendix of reference [10]. Since the fast-closing valve control is added to the model of the prime mover and speed control system, the typical values ​​of the governor model and prime mover model in reference [9] are used. When a three-phase ground fault occurs on a transmission line about 1km from the generator end and the fault is delayed for some reason, or when a three-phase permanent short circuit occurs, the generator will lose synchronism and enter the asynchronous operation state. In this case, if the system is allowed to operate asynchronously for a short time, the fuzzy controller proposed in this paper can be used to quickly pull the generator into synchronous operation. The slip change curves of conventional control measures and the slip change curves of additional discontinuous fuzzy controller are given respectively under the condition that the fault is delayed by 0.4s and the line is no longer reconnected. It can be seen from this that under the additional control measures, the generator will recover the synchronous operation state after a period of time. 4.2 Multi-machine system and its results simulation The multi-machine system represented by the two-machine-infinite system used is simple. The parameter selection of the generator and excitation system model and the selection of the governor model and prime mover model parameters in this system are similar to those described above. Here, only the number of generators is increased. In the system, a three-phase ground fault occurred on a transmission line between G1 and the ¥ system approximately 1 km from G1. Due to some reason, the fault clearance was delayed by about 0.8 seconds. Under conventional control measures, the generator would lose synchronism and enter asynchronous operation. The proposed additional discontinuous fuzzy controller was used to control this fault. The slip variation curves of conventional control measures and the addition of the additional discontinuous fuzzy controller are presented under the conditions of a three-phase permanent short circuit on the G1 bus, a 0.8-second delay in fault clearance, and the line no longer reclosing. Using the additional discontinuous fuzzy controller improves the slip variation, and the additional discontinuous control measures enable the generator to quickly return to synchronism, thus quickly restoring the system to synchronous operation. It can be seen that the control effect on G1 is more significant, quickly bringing the out-of-synchronism generator back to synchronous operation within approximately 4-5 seconds, proving the effectiveness of the additional discontinuous control measures. Since the fault occurred very close to G1, its impact on G1 was significant, while its impact on G2 was relatively small. Therefore, the additional discontinuous control device on G2 was essentially inactive, and the stability requirements could be achieved through the regulation of its conventional control system. [b]5 Conclusion[/b] This paper explains the working principle of the fuzzy controller and proves through simulation results in single-machine-infinite-scale systems and multi-machine systems that this fuzzy controller has a good control effect on power system resynchronization, thus demonstrating that the intelligent controller has practical application value.