Modular multilevel converters (MMC) are widely used in power systems. However, relevant studies and reports show that MMC connected with the grid may cause oscillation problems. When the bridge arm resistance is large enough, the operating conditions will be stable because of overdamping in the system. According to this idea, a virtual damping strategy is proposed, which is equivalent to increasing the resistance of the bridge arm without any actual power loss. Meanwhile, from the perspective of the impedance‐based analysis method, it is explained that this virtual damping control strategy can improve the stability margin of the system to realize the suppression of oscillation. In order to verify the effectiveness of the control method, the MMC simulation model is established under Matlab/Simulink. The simulation results show that the proposed virtual damping control can effectively suppress the MMC oscillation problem.

An oscillation suppression strategy based on virtual impedance is proposed to solve the oscillation problem when the MMC connects to weak AC grid, and the effectiveness is verified by a MATLAB/Simulink platform. MMC equivalent impedance model is established based on the multi‐harmonic linearisation method. Impedance‐based analysis method was used to study the difference of MMC impedance before and after virtual damping access, and the oscillation suppression mechanism based on virtual impedance strategy is revealed from the perspective of MMC output impedance.image

A novel distributed feedback optimisation (FO) based control method is proposed to control grid‐forming inverters (GFMIs) in fully inverter‐based islanded AC microgrids (MGs). The proposed controller has two control layers. The upper layer uses FO to calculate the frequency and voltage setpoints of GFMIs, whereas the lower layer makes GFMIs track these setpoints. The proposed control method takes advantage of the flexibility of voltage control to regulate the system frequency, maintain both active power and reactive power sharing accuracies, keep bus voltage within allowable range and meanwhile preserves the optimality of the closed‐loop system in term of optimal power flow. The gradient descent method is used to solve the proposed FO problem based on the real‐time measurements in the MGs, which is implemented in a distributed way, and thus eliminates the need for a central controller. Case studies show the effectiveness of the proposed method.

The cover image is based on the Research Article Distributed feedback optimisation based optimal power flow control in fully inverter based islanded AC microgrids by Y. Cheng et al., https://doi.org/10.1049/stg2.12132.

The authors use distributed feedback optimisation to continuously drive microgrids to their optimal states in optimal power flow problem in real‐time. The time‐scale of optimisation is shorter than the existing hierarchical control used in microgrids. Therefore, microgrids can track the optimal operating point of optimal power flow more quickly.image

With the development of power electronics and motor driving system, AC motor speed control or the servo system has been widely explored. Among them, the Induction Motor (IM) driving based on a three‐phase six‐switch inverter has become a mature technology for a wide range of applications. However, in some scenarios, a certain fault‐tolerant ability and further cost savings are required. Under this circumstance, the motor driving system based on the three‐phase four‐switch inverter is proposed. However, it has fewer voltage vectors, with unequal amplitudes, spatial asymmetry, and no zero vector, which will inevitably lead to the deterioration of the control performance. In this study, the operation of the four‐switch inverter IM driving is analysed in detail. The model predictive direct torque control (MPDTC) is proposed to obtain better static and dynamic characteristics. Through the simulation and experimental studies, the control algorithm is verified to drive a 2.2 kW IM. Compared with the conventional DTC, the proposed MPDTC has a rapid dynamic response and greatly reduces the torque and flux ripple in a steady state.

The three‐phase four‐switch inverter is used to drive an induction motor, which has a lower cost and can be a fault‐tolerant solution to ensure a continuous operation. Model predictive direct torque control is proposed for this motor driving system to improve the static and dynamic control performance.image

The authors propose a continuous‐time two‐stage stochastic optimisation model for the integration of centralised and distributed energy storage (ES) systems into power systems with high levels of volatile renewable generation. In the proposed model, centralised and distributed ES systems, respectively, controlled by the independent system operator and distribution system operator, can offer energy and flexibility to the operation of the power system in order to help accommodate the uncertainties of renewable generation and load. The proposed model considers the power network constraints and minimises the day‐ahead and real‐time operation costs of the system in the first and second stages. The proposed model utilises energy and ramping flexibility trajectories of ES systems to enhance the cost‐effective operation of the power system, countering the financial risks imposed by the integration of uncertain load and renewable generation. Simulations are conducted on the IEEE 24‐bus reliability test system with multiple risk‐aversion levels for the power system operator, and the results demonstrate the efficiency of the proposed model in utilising the ES systems to provide energy and ramping flexibility and reducing the financial risks measured by the conditional value at risk.

This paper is devoted to the distributed demand response (DR) charging control of plug‐in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Specifically, PEVs are divided into different clusters according to their parking place under different energy management systems. Each EV cluster is modelled by a transport‐based load aggregate model with the input being the charging rate, and the output is the aggregate power. Based on the aggregate charging control model, a novel dynamic real‐time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory. The theoretical analysis shows that if the reference power profile is in the trackable area of all PEVs' charging power and the ramping rate is restrained by a predefined bounded constraint, then the demand response charging tracking control is solvable. Finally, simulation results on an EV system with twelve PEV clusters are presented to show the effectiveness of the proposed demand response control algorithm.

This paper is devoted to the distributed demand response (DR) charging control of plug‐in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Based on the aggregate charging control model, a novel dynamic real‐time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory.image