Integrating permanent magnet synchronous generator (PMSG) wind turbines with DC microgrids have attracted a great attention due to the inherent merits of DC systems. However, under the fault conditions, the excessive energy during fault will be reflected on PMSG rotating parts causing overspeed, mechanical stresses, and fast aging. Also, large fault currents will force generator-side converter to disconnect making it not complied with grid codes. Accordingly, this paper aims to apply superconducting fault current limiter (SFCL) to enhance the performance of PMSG wind turbines with DC microgrids under the fault conditions. PSCAD/EMTDC software is used to build the system under study that includes PMSG, controlled AC/DC converter, SFCL, and DC bus. The behavior of SFCL in enhancing the DC output of the converter is first studied. Then, the impact of using SFCL on the speed, torque, and output current of PMSG is investigated and discussed. Finally, the suitable current limiting resistance is adopted considering DC output as well as PMSG speed.

To guarantee efficient and stable operation of a microgrid, overcharging and unbalanced state of charge (SOC) of batteries have to be mitigated. An adaptive droop control scheme is proposed in this study to provide energy management between distributed batteries having unbalanced SOC and different capacities. The proposed approach suggests using a droop factor proportional to the n th order of SOC in the charging mode and inversely proportional to the n th order of SOC in the discharging mode. Moreover, a modification is proposed to adapt the performance taking into account the battery relative capacity. The relative capacity of an individual battery is defined as the ratio between the maximum capacity of all batteries and the battery capacity. The proposed adaptive droop control scheme is investigated and analysed based on an accurate model of dc microgrid incorporating lithium‐ion battery, photovoltaic, permanent‐magnet synchronous generator‐based wind energy system and constant power loads. Several operating conditions were considered to validate the proposed control approach. The proposed control scheme has been succeeded in keeping the dc bus voltage within limits and equalising SOC of batteries, either having similar or having different capacities.

Recently, various strategies for energy management have been proposed to improve energy efficiency in smart grids. One key aspect of this is the use of microgrids. To effectively manage energy in a residential microgrid, advanced computational tools are required to maintain the balance between supply and demand. The concept of load disaggregation through non-intrusive load monitoring (NILM) is emerging as a cost-effective solution to optimize energy utilization in these systems without the need for extensive sensor infrastructure. This paper presents an energy management system based on NILM and the Internet of Things (IoT) for a residential microgrid, including a photovoltaic (PV) plant and battery storage device. The goal is to develop an efficient load management system to increase the microgrid’s independence from the traditional electrical grid. The microgrid model is developed in the electromagnetic transient program PSCAD/EMTDC to analyze and optimize energy performance. Load disaggregation is obtained by combining artificial neural networks (ANNs) and particle swarm optimization (PSO) to identify appliances for demand-side management. An ANN is applied in NILM as a load identification task, and PSO is used to optimize the ANN algorithm. This combination enhances the NILM technique’s accuracy, which is verified using the mean absolute error method to assess the difference between the predicted and measured power consumption of appliances. The NILM output is then transferred to consumers through the ThingSpeak IoT platform, enabling them to monitor and control their appliances to save energy and costs.

Energy storage systems are a crucial part of microgrids, making up for their autonomous operation. Therefore, much research has focused on increasing their lifetime and operational efficiency. One of the most viable topics is maintaining connected energy storage units (ESUs) at the same state of charge (SoC). Droop control techniques have been developed in centralized, decentralized, and distributed fashions. This paper proposes a novel IoT-based droop control that can achieve SoC balancing not only within the same microgrid but also between multiple microgrids. The proposed architecture increases reliability and flexibility while allowing the system to be expanded, reconfigured, or upgraded, enabling the plug-and-play capability more easily. First, the proposed IoT-based hierarchical control and communication architecture is presented. Then, the proposed SoC balancing technique and its coordination with IoT architecture are introduced. Through 24-hour simulations, the proposed technique’s scalability, adaptiveness, and robustness are validated under different scenarios, including the operation of any microgrids or ESUs with different capacities and the operation in case of a communication failure. Finally, the IoT value chain of the proposed technique is experimentally validated using a physical laboratory microgrid that uses HTTP protocol to send and receive data through the ThingSpeak IoT-cloud service.

Battery energy storage system (BESS) is required in microgrids to balance the energy requirements from the load and the generated available energy. However, under fault conditions, there are many problems facing BESS. Accordingly, superconducting fault current limiter (SFCL) is presented in this paper as an effective solution for system integration of battery banks. A microgrid composed of PV system, battery bank, DC bus and loads is modeled using PSCAD/EMTDC computer package. The impact of SFCL on battery current and its rate of rising is obtained under different battery conditions. Moreover, the change of battery state of charge (SOC) after using SFCL is highlighted. The results proved that using SFCL with batteries will provide technical benefits on battery lifetime, grid code compliance and cost of DC circuit breaker. Finally, the required SFCL material is evaluated by obtaining the suitable resistance value and critical current followed by experimental investigation of developed re-sistance for an actual superconducting tape.

DC distribution systems can provide effective solutions for integrating renewable energy sources in future power systems. The low inertia of the DC distribution system causes several problems regarding stability and fault response. For stability, this low inertia represents a major cause for instability and voltage oscillations, especially with constant power loads. For fault response, the low inertia results in very high fault currents with a significant rate of rising and limited damping. This study aims to use superconducting fault current limiter (SFCL) as a virtual inertia for DC distribution systems under various disturbances and fault conditions. The system description and modeling are first presented, including the detailed dynamics of SFCL. The stability analysis for the DC system is carried out using the Hurwitz criterion, from which the suitable range of SFCL resistance is identified. Considering this range and fault current limitation, an SFCL resistance of $1.5~\Omega $ is adopted. The whole system is implemented using PSCAD/EMTDC software. A series of case studies are investigated to validate the effectiveness of SFCL in strengthening the inertia of the DC system. These case studies include sudden variations in supply voltage, sudden load changes, and faults. SFCL could successfully suppress voltage oscillations, keep voltage stability, and limit fault currents.