The emergence of power system digitalization initiatives is revolutionizing the way electricity grids are monitored and protected. However, the integration of cyber and physical electrical infrastructures leads to an increase in the risk of cyber intrusions. Attackers can gain access to the smart grid and inject falsified data, leading the protection schemes to activate unnecessary power outage actions. Such outages can be devastating to end users. In this paper, an intrusion detection and mitigation system (IDMS) is proposed using deep learning neural networks (DLNNs) to detect, classify, and locate intrusions in smart grids. Once the disturbance is detected, the IDMS is designed to diagnose the intrusion and classify the attack into a single point or coordinated intrusion. Afterward, the algorithm locates and isolates the contaminated intelligent electronic device (IED) and predicts its current waveform utilizing long short-term memory (LSTM) to maintain power system observability. The proposed IDMS performs the required diagnosis on the modified IEEE 13-bus system. Simulation results demonstrate high accuracy in the proposed detection, classification, location, and prediction approach.

Extensive research has been conducted on protecting alternating current (AC) power systems, resulting in many sophisticated protection methods and schemes. On the other hand, the natural characteristics of direct current (DC) systems pose many challenges in designing a proper protection scheme for DC microgrids (DC-MG). This paper highlights the significant challenges facing the design of effective protection methods for DC microgrids. Furthermore, several technologies and techniques presented in the literature to overcome the challenges associated with DC microgrid protection are presented in this paper. These methods are comprehensively and comparatively analyzed. In addition, some potential issues of DC microgrid protection that need further investigation in future research are highlighted.

The critical challenges with integrating renewable energy into the grid are smooth power flow control, isolation between the high-voltage and low-voltage networks, voltage regulation, harmonic isolation, and power quality regulation. This paper considers the design and construction of a two-stage DC-AC solid-state transformer based on wide bandgap (WBG) semiconductor technologies, an optimized medium-frequency transformer, and PI and dq controllers for supplying urban area electric drive systems and microgrid applications. The designed SST consists of a dual active bridge (DAB) DC-DC converter followed by a DC-AC three-phase inverter. Each stage of the SST was simulated with independent controllers. The proposed system was initially developed in MATLAB/Simulink and a laboratory prototype was constructed to verify the results experimentally. Resistive and inductive load were used to test the load disturbance to evaluate the voltage regulation performance. This work has comprehensively provided the performance of a double stage (DC-DC and DC-AC converter) by taking into consideration input voltage, load disturbance, and voltage tracking both in simulation and experiment. The dual active bridge with its controller is able to maintain the desired output reference voltage with minimal voltage ripples under input voltage fluctuations and load variations. Similarly, the three-phase DC-AC converter’s controller exhibits better performance in tracking the desired reference voltage and producing well-regulated AC voltage with low harmonic distortion.

DC distribution systems are drawing huge attention from researchers and industries because of their many advantages over AC systems. Due to its various benefits, including isolation and good fault current performance which is a big challenge for DC grids. the three-phase dual active bridge (DAB) converter is one of the most widely used converters for high power applications. However, the existing modulation techniques of the three-phase DAB have some drawbacks including high peak current, very low voltage ratio limitation as well as low output current. This paper proposes a new modified asymmetrical duty cycle control (MADCC) method to enable fault ride through operation of the three-phase DAB. By having three independent control parameters, the modulation strategy presented here efficiently controls the peak current and allows for high output current, all the while ensuring the converter switches operate with soft switching. Both simulation and experimental verification have been performed to test the proposed schemes. A comparison has been made between the performance of the proposed scheme and other existing control methods, and their key features are outlined and emphasized. During reference DC voltage tracking, low ripple voltage, small overshoot, and nearly no steady-state error was attained. Experimental and simulation results also confirmed the high DC current injection capability of the proposed technique during short circuit faults. This improvement in fault ride-through capability (FRT) enhances the performance of the three-phase DAB converter.