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Fixing the frequency of the orthogonal signal generator is a classic way to improve the stability and dynamics of single-phase phase/frequency-locked loops (PLL/FLL). However, they exhibit undesired oscillation and bias under the fastly-time-variant frequency of low-inertia grids. It is very difficult to improve due to the absence of an internal model principle when this frequency-fixed property is still maintained. This paper aims to address the above challenge, and a typical orthogonal signal generator based on a second-order generalized integrator (SOGI) is researched. Firstly, it reveals that the frequency-fixed implementation inherently induces inaccuracies of the orthogonal signals generated by SOGI for two factors. One is the additional frequency offset, and the other is that the orthogonal signal is not achieved even when the amplitude is compensated. Then, these factors are considered in the PLL/FLL to interpret the problem of undesired estimation performance. The interpreted problem must be solved by the frequency derivative rather than the frequency itself. A frequency-derivative-adaptive loop is, thus, developed while maintaining the frequency-fixed property of SOGI. The loop analysis is further given to obtain the stabilization conditions and parameters design guidelines. Finally, comparative tests validate the improvement in estimating the voltage parameters under time-variant frequency and its potential merits for weak-grid-following inverters with inertia emulation.

This article proposes a dc microgrid (MG) composed of a cascaded bidirectional Cuk converter (CBC) connected to a cascaded bidirectional boost converter (CBB) sharing two battery energy storage systems (BESSs) as common inputs. Then, the dc-link from CBC also receives a boost converter, which interfaces the dc utility. Thus, this configuration can coordinate the BESSs and the dc utility by employing the state-of-charge (SoC)-sharing function and the droop controller. In this context, the combination of CBC and CBB can improve the reliability of the SoC-sharing function with the battery-to-battery equalization on CBB and can enhance the availability of power production on the CBC dc-link. Therefore, the main advantage of the proposed method is to ensure the SoC equalization even when the MG is under maintenance or electrical fault. Additionally, the dc MG involves a modified energy management system while Lyapunov's indirect method proves the stability analysis. Finally, the experimental setup validates the feasibility of the proposed approach.

Microgrids (MGs) are building blocks of smart power systems formed by integrating local power generation resources, energy storage systems, and power-consuming units. While MGs offer many benefits, including increased resilience and flexibility, there remains a need for improved control and protection techniques that can ensure their performance and automatic restoration in response to dynamic operating conditions and failure events. Recently, researchers have explored model-free emotional-learning adaptive strategies based on the emotional response of human brains to control MGs. These model-free control strategies are well-suited for handling the complexity, nonlinearity, and uncertainty present in MGs and offer several advantages over traditional approaches. This paper provides an overview of different emotional learning techniques applied to MG control and protection, their challenges, and future trends. In addition, we draw parallels between the hierarchical control architecture of MGs and the emotional learning process in the human brain, discussing their operational strategies and key areas of research. Finally, the future implementations of brain emotional learning in the control and protection of MGs are discussed, and concluding remarks on the potential of this approach are provided.

Microgrids (MGs) have gained popularity in various scenarios, such as maritime, space, and terrestrial applications. In all these scenarios, machine-to-machine (M2M) communication is crucial for the management and control of MGs. However, due to the diverse working conditions of different MG types, they may require different communication systems with specific features and characteristics. This article aims to address these issues by providing an overview of appropriate M2M links for different MG types. The article also discusses the unique features of each MG type, their vulnerability to cyberattacks, and their applicability in different scenarios. The information presented in this article can be valuable for researchers, engineers, and decision-makers working on MG projects in different fields.

This article proposes a multienergy trading market model based on price matching, aiming to foster multienergy collaboration and enhance energy utilization through individual participation. With the ongoing advancements in energy distribution and marketization, the energy Internet necessitates improved applicability and efficiency for personalized energy responses. To address these requirements, a multienergy trading market model is proposed, which enables the avoidance of user information disclosure and guarantees user trading autonomy. In addition, a joint trading mechanism is designed that accounts for multiple time scales and energy types, consequently reducing trading failures caused by overlooking energy transmission processes. By performing the proposed trading mechanism, the market operator can match various energy types using conversion devices, thereby augmenting matching efficiency. An income mechanism is also established to deter the operator from purposefully evading potential trading opportunities for personal gain. To address the proposed model, an improved hierarchical reinforcement learning algorithm is employed, which effectively overcomes challenges associated with large state action spaces and sparse rewards. Numerical examples are provided to confirm the efficacy of the proposed approach.

For virtual synchronous generator (VSG) based microgrids, it is challenging to address the adverse effect of nonlinear loads and grid background harmonics with existing harmonic suppression methods. To address this issue, a decomposed grid harmonic current suppression (DHS) method with proper feedforward point of common coupling voltage and feedback VSG output current as well as nonlinear load current is proposed for VSG-based microgrids. The proposed DHS method can separately mitigate the grid harmonic current caused by nonlinear loads and grid background harmonics, obtaining a promising harmonic suppression effect without potential system instability problem. Compared with conventional harmonic control methods, the DHS method reduces the control sensitivity to system parameters including line impedance, grid impedance, and system shunt capacitance, improving the adaptivity of harmonic control in distorted grids. The proposed method's effectiveness and reliability are verified by theoretical analysis and comparative experiments.

A distributed control strategy (DCS) is an efficient way to realize power sharing among distributed generators (DGs) and restore the voltage deviation caused by droop control. However, there are several limitations in the traditional strategy of hybrid ac/dc microgrid (MG), such as the heavy communication burden and sensitivity to the working conditions. In this article, a distributed model-free adaptive control strategy (DMFAC) is proposed with an event-triggered (ET) mechanism. A unified control framework of hybrid MG is established and the ET-DMFAC can operate within it to realize multiple control strategies simultaneously. The dynamic linearization parameters of hybrid MG are estimated online to reflect the working condition, and an ET mechanism is designed to reduce the communication burden. The stability of ET-DMFAC is analyzed with the discrete Lyapunov theory and experiments are carried out to verify the effectiveness of the proposed ET-DMFAC strategy under different operating conditions. The outperformance of ET-DMFAC is demonstrated by comparing it with many existing DCS of hybrid AC/DC MG.

DC microgrids (MGs) represent self-contained systems for distributing and managing electricity locally, offering advantages in terms of efficiency and control. This article proposes the optimization of redundancy-based dc MG, emphasizing the integration of an intelligent algorithm to minimize operational costs under real-time pricing conditions and also increase the efficiency operation. The redundancy-based dc MG consists of a cascaded bidirectional Cuk converter (CBC) linked to a cascaded bidirectional boost converter, sharing two battery energy storage system (BESS) units as common inputs. Thereby, two boost converters interface the dc utility and fuel cell (FC) to the dc-link of the CBC. The redundancy-based dc MG operates with a coordinated and decentralized control among the dc utility, FC and two BESS units. The energy management system (EMS) employs a droop control for the dc utility and FC, while BESS units adhere to a state-of-charge (SoC)-sharing function. In addition, the particle swarm optimization dynamically adjusts EMS parameters for optimal real-time performance. Then, a stability analysis determines MG operational boundaries, and the effectiveness of the method is confirmed through experiments using Typhoon HIL and dSPACE setups. Finally, comparative evaluations against traditional SoC-based droop and genetic algorithms demonstrate the cost reduction of the proposed approach.

It is a big challenge for current source converter (CSC) to ensure the desired tracking performance, robustness, and immunity simultaneously in the presence of resonance caused by the grid-side LC filter and slowly time-varying filter parameters or load disturbances. Aiming at this problem, combining the advantages of passivity-based control (PBC) and nonsingular terminal sliding mode control (NTSMC), a hybrid PBC-NTSMC method is proposed. Based on virtual damping injection and energy dissipation theory, the PBC is first designed for the inner loop followed by the construction of the Euler–Lagrange model. In this way, the resonance suppression is realized and the CSC system is proved to be passive. Furthermore, the NTSMC is combined with PBC to improve the dynamic response, reduce the chattering problem of traditional sliding mode control, and enhance the robustness of the system while maintaining passivity. In addition, the power references are modified to enable system to flexibly configure the control target depending on actual application requirements under nonideal grid. To further enhance the immunity, an ultralocal model predictive controller based on extended state observer disturbance estimation is designed for the outer loop. Finally, the simulation and experimental results verify the effectiveness of the proposed method.

Two-way communication systems in smart grids help to engage consumers in demand–response programs, which can bring many benefits but also make smart grids vulnerable to cyber attacks. In this paper, a cyber attack which aims to disturb the demand–response process by injecting false electricity price signals is considered. A real-time pricing model where the operator has incomplete knowledge of the private demand–response behaviors of the customers is proposed. The vulnerability of the power system to false pricing attacks is analyzed by a Markov decision process, and the dynamic interaction between the attacker and the defender is modeled as a zero-sum Markov game where neither player has full information of the game model. For the solution of the Markov game, a model-free multi-agent reinforcement learning method is proposed to find the Nash Equilibrium policies for both players. The proposed method is applied to the IEEE 34 Node Test Feeder, in which the effect of the defense on mitigating the impact of the attack is demonstrated and different policies of the players given various resources are analyzed. The results shows that the studied cyber attack can cause a maximum of 1.96% unsatisfied load and the proposed defense measure can reduce the unsatisfied load by 50%–70% compared with the cases without defense measures.

This paper introduces an innovative approach to promote sustainable electrification in Ethiopia through the strategic development of minigrid clusters. In collaboration with Ethiopian authorities, technical and economic barriers obstructing the large-scale deployment of minigrid clusters are systematically identified. A novel Multi-Tier Framework (MTF)-based energy access matrix is presented, facilitating the creation of hybrid load profiles prioritizing affordability and reliability. The most suitable multi-criteria optimization strategy tailored to the Ethiopian context is explored, emphasizing the need for scalable and adaptable solutions. The proposed approach is rigorously validated through case studies in three villages within the Southern Nations, Nationalities, and Peoples' Region (SNNP). The research findings reveal the remarkable techno-economic advantages of minigrid clusters when compared to single minigrids, establishing the practicality and significance of the methodology. Sensitivity analysis is conducted to assess the impact of varying techno-economic scenarios on optimal sizing, providing essential insights for decision-makers. As a result, this paper significantly contributes to the upcoming deployment of four planned large-scale minigrids in the SNNP region, funded by the African Development Bank. Valuable guidance for stakeholders and decision-makers involved in minigrid cluster development in Ethiopia is offered, underscoring the critical role of such systems in achieving sustainable energy access and fostering socioeconomic progress.

Distribution transformers (DTs) are the most costly and crucial power grid equipment, and accurate investigation of their thermal status can prevent their failure, since insulation condition directly correlates with hotspot temperature (HST). In this article, an accurate and nonuniform magnetic–thermal analysis of DT is proposed for precise HST prediction. In the magnetic analysis, the DT is modeled as a 2-D axial symmetry, and the losses calculation of the windings has been fulfilled as a nonuniform. In the thermal analysis, the DT is modeled as 3-D and nonuniform, and the conservator and core stacking, which has a considerable effect on the HST, are precisely modeled. By taking advantage of optical fiber sensors (OFSs) in the understudied 500-kVA DT, the accuracy of the proposed nonuniform 3-D computational fluid dynamic (CFD)-based modeling during the temperature rise test (TRT) is validated. The empirical evaluation results depict that the presented nonuniform CFD-based thermal analysis for HST prediction is very precise, and there is an appropriate vicinity to the experimental values. The error percentage of the proposed 3-D CFD-based thermal analysis is 0.11% (0.1 °C) compared with the OFSs measurements, which demonstrates the precision and effectiveness of the presented modeling. Also, the verification of the results of nonuniform 3-D CFD-based thermal analysis in top-oil temperature (TOT) and bottom-oil temperature (BOT) during the experimental TRT is fulfilled via thermography. According to the attained evaluated results, temperatures of 3-D CFD-based thermal analysis and thermography in the noted two points are in good accordance with each other. In short, the error percentage is less than 0.65%, which indicates the correctness and proper performance of the proposed 3-D CFD-based modeling. Finally, the proposed nonuniform 3-D model was subjected to the unbalanced load currents of 0.95, 1.05, 1.1, 1.15, and 1.2 of rated current, which increased the HST by −1.6 °C, 1.3 °C, 2.8 °C, 4.3 °C, and 6.0 °C, respectively, over the original model without unbalanced load currents.

Common-mode voltage (CMV) has several negative effects on photovoltaic (PV) grid-connected systems and motor drives. To reduce CMV, converter topology improvement draws great interest, such as the novel three-level H8 converter topology. This converter has the potential to achieve low CMVs, but it suffers from CMV jumps during dead-time (DT), which is detrimental to the reduction of CMV. To solve this problem, this article proposes a three-level H10 converter and its modulation techniques considering the DT effect. First, by choosing a suitable combination of space vectors, two reduced CMV modulations (RCMVMs) are introduced. Second, to eliminate CMV jumps during DT when entering and leaving the zero voltage vector (ZVV) in RCMVMs, an H10 topology with control strategy, which applies active voltage vector (AVV) to ZVV period, is proposed. Finally, the applicable conditions of control strategy are analyzed. Simulation and experimental results are provided to demonstrate the effectiveness of the proposed scheme.

DC power flow controller (DCPFC) is regarded as an effective technology to improve the power distribution capability in a complex dc power grid. Among different types of DCPFCs, the interline dc power flow controller (IDCPFC) can realize multiline power flow control functions in a complex dc grid. In this paper, a modular interline dc power flow controller based on switch isolation (ISO-IDCPFC) and a decoupling and phase shift control method of ISO-IDCPFC are proposed. ISO-IDCPFC has the advantages of modularity, scalability and multi-level outputs. By utilizing the dual-target decoupling and multi-carrier phase shift control method, ISO-IDCPFC can realize flexible and economical line current adjustment. Based on these, simulation models built in PLECS and downscaled experiment setup are used to validate the effectiveness of the proposed topology and the control method.

In this article, a new cascaded-H-bridge (CHB) inverter is proposed to enhance the input voltage of a renewable energy source to a desired level without any necessity of a dc–dc converter. The proposed topology consists of a pair of inductor and capacitor that serves as an input impedance network for the two full bridge inverters to boost the source voltage. An interleaved control scheme is proposed for the grid-tied inverter that independently supervises the duty cycle and the modulation index. The maximum power point tracking (MPPT) system commands the duty cycle, whereas the dc-link voltage regulator maintains a constant voltage across the capacitors irrespective of the disturbances in the system. The proposed control scheme is primarily investigated in the MATLAB/Simulink platform. Different test cases are analyzed to explore the performance of the proposed inverter in the applications of photovoltaic systems. An experimental prototype is designed in the laboratory to validate the simulation results.

The stability of inverters can be greatly improved by designing them with a robust control system. However, even if the system remains stable under symmetrical conditions, the presence of asymmetrical load/grid impedance can still pose a threat to its stability. Under this circumstance, the coupling between the αβ- and dq-frames in the average model leads to the creation of a multi-input multi-output system. Consequently, simplifying the system into a single-input single-output form is no longer feasible. This situation becomes even more complex when multiple inverters are connected in parallel, where the interaction among inverters complicates the modeling of the system. This letter presents a simple yet accurate approach to address these challenges. To this end, the models of the inverters in the frequency domain are lumped to investigate the stability of the entire system in light of the asymmetrical condition using the generalized Nyquist criterion.

To achieve the fault ride through (FRT) operation of DFIG-based wind turbines, various improved control methods have been proposed. However, it is difficult to reveal their essential relations and quantitatively evaluate their performance differences, due to the wide assortment of solving ideas and control structures. To cope with this issue, this paper revisits the FRT control from a new perspective of rotor-port impedance characteristics (RPIC). First, a unified RPIC model of nine typical FRT controls is established and it is found that their RPIC are manifested as the pure inductance, but the inductance values are different in the phase sequence. Subsequently, the influence of RPIC on FRT performance is analyzed and some practical design guidelines for FRT control are given. On this basis, nine typical FRT control methods are quantitatively evaluated and compared in terms of six key performance dimensions. Moreover, the study contributes to the understanding, analysis and redesign of FRT control, and the RPIC perspective features the definite physical meaning and simple. Finally, the analysis is validated by the experiments.

The fluctuated power output of renewable energy sources brings new challenges to frequency control, especially for islanded microgrids with small spinning reserves. However, energy storage systems and widespread flexible loads can be employed to the frequency regulation thanks to their flexibility of power outputs. This paper investigates the frequency regulation problem for islanded microgrids with distributed heterogeneous energy storage systems (HESS) composed of battery energy storage systems (BESS) and building thermal energy storage systems (BTESS). A distributed event-triggered balanced power sharing strategy considering denial of service (DoS) attacks is designed for frequency regulation by allocating HESS power according to BESS state of charge (SoC), BTESS state of temperature (SoT) and their capacities. The range of control parameters for a stable controller are all provided by Lyapunov analysis. Moreover, the frequency feedback control gain for HESS is derived by using linear quadratic regulator. Simulation results show that the proposed frequency regulation strategy can guarantee the recovery of microgrids frequency and the proportional sharing of HESS power. Besides, SoC and SoT balancing with fewer communications are achieved, even with considering various parameters of HESS, such as capacity, efficiency and with communication link failures as well as DoS attacks.

Due to the advantages of smaller size and lower cost, transformerless grid-connected converter (GCC) has been widely used in photovoltaic (PV) power generation system. But this may incur obviously leakage current, which is related to the common-mode voltage (CMV) of the GCC. Topology improvement by adding additional switches is an effective way to reduce CMV, i.e., H7, H8, and H10 topologies. However, some topologies suffer from high leakage current and low-power quality of the grid current. To solve those problems, based on the existing H8 topology, this article proposed a nonclamped H10 (NCH10) topology. First, the large variation in CMV of H8 topology is analyzed using complex frequency-domain model. Second, a NCH10 topology which could achieve a 66.7% reduction in CMV is proposed. Finally, the PWM control signals based on novel logic functions are established. Compared to H10 topology, the proposed NCH10 topology which has special arrangement of additional switches owns better loss performance. Moreover, its isolated operation between grid and PV array during zero-voltage vectors (ZVVs) greatly reduces the leakage current. The effectiveness in terms of CMV limitation and leakage current reduction is demonstrated by numerous simulation and experiment results.

The need for affordable, reliable, sustainable, and modern energy is now more important than ever because of the climate crisis. Climate change will push up to 130 million people into poverty over the next 10 years and continue to cause more unpredictable natural disasters, such as cyclones, flooding, earthquakes, landslides, tsunamis, and volcanic eruptions. Power outages do not occur only in remote rural areas but also in developed countries, lasting for several hours and even a couple of days, due to the extreme weather in recent years. Microgrids, as a flexible architecture capable of integrating local distributed energy resources (DERs), can satisfy wide-ranging demands via their variable solutions, from off-grid to on-grid applications.

Voltage regulation, frequency restoration, and reactive/active power sharing are the crucial tasks of the microgrid's secondary control, especially in the islanding operating mode. Because sensors and communication links in a microgrid are subject to noise, it is of paramount value to design a noise-resilient secondary voltage and frequency control. This paper proposes a minimum variance control approach for the secondary control of AC microgrids that can effectively perform noise attenuation, voltage/frequency restoration, and reactive/active power sharing. To this end, the nonlinear generalized minimum variance (NGMV) control approach is introduced to the islanded microgrid's secondary control system. The effectiveness of the proposed control approach is verified by simulating two microgrid test systems in MATLAB.

Transformerless inverters are used in small and medium power photovoltaic grid-connected systems due to small-size, low-cost and high-efficiency. Transformerless inverters have problems of leakage current and low-voltage gain in applications due to the lack of electrical isolation and boost characteristics of transformers. According to these problems, this article introduces a gain unit circuit in the front-stage based on the two-stage topology of Boost converter combined with the H-bridge inverter to improve the boost capability. In addition, the rear-stage converter adopts double Buck inverter, which has the ability to prevent the short circuit of the bridge arms and improves the reliability of the system. At the same time, it is ensured that there is no high-frequency component in the parasitic capacitor voltage, and the leakage current is suppressed. In this article, the operational modes, circuit gain, devices stress and loss calculation of the proposed inverter are analyzed. Finally, an experimental platform is built to verify the effectiveness of the proposed circuit.

In this article, a converter-based multibus dc microgrid (MG) in series is studied, in which the tradeoff between voltage recovery and current equalization has been a hot topic of interest. To solve this problem, a distributed learning-based high-order fully actuated (DL-HOFA) secondary control is proposed in this article, and the simple structure of this control technique facilitates its application in various modern dc MGs with different configurations. Before designing the secondary control protocol, this article provides a comprehensive description of dc MGs in advance. In the suggested control strategy, the controller design is tightly related to the underlying physical characteristics of the MG, and this prominent feature represents a significant improvement in its adaptability. In addition, the DL-HOFA control obtains fast dynamic and accurate current sharing performance by virtue of the high-order fully actuated dc MG model. The effectiveness of the proposed control method is verified on a real photovoltaic- and battery-based hardware system with maximum power point tracking controller.

Unbalanced low-voltage survivability of islanded microgrids under three-phase nonlinear load conditions in terms of primary control of distributed generations (DGs) is a research gap. This paper bridges the gap by proposing dynamic-sliding mode controller (SMC) for the voltage control loop and a novel current limiting strategy (CLS) based on the sliding-discrete Fourier transform (DFT) algorithm. The proposed sliding-DFT-based CLS separates fundamental and harmonic components of the reference value of inverter current and only restricts its fundamental component to a value less than the threshold value. The proposed dynamic-SMC, which presents robust performance with low chattering phenomenon, in combination with the sliding-DFT-based CLS prevents DG's output voltage distortion. This feature is favorable for supplying local and sensitive loads. Moreover, single-phase washout filter-based power sharing method has been implemented to ensure precise active power sharing and frequency regulation of the microgrid with mixture of single-phase and three-phase DGs during asymmetrical short-circuit faults as well as better fault clearance dynamics than the conventional three-phase droop control method. The offline and hardware-in-the-loop (HIL) simulation results also confirm the effectiveness of the proposed CLS and voltage controller applied to the control structure of DGs operating in the grid-forming mode in comparison with existing methods.

By applying virtual synchronous generator (VSG) method in high penetration level microgrids, current limiting issue under fault condition has become an important challenge. The main objective of this paper is to propose a novel current limiting strategy which has the capability of voltage tracking error reduction to avoid voltage controller saturation. This purpose is obtained by adaptive virtual impedance-based reference voltage correction during fault condition. Furthermore, positive and negative peak detection-based current limiting method implemented in double loop control system prepares soft transition ability. Moreover, this current limiting method generates the adaptive term of virtual impedance part. In contrast to conventional VSG methods, the proposed approach provides high quality voltage and current for microgrid in both grid-connected and islanded modes during fault conditions. The offline and hardware in the loop (HIL) simulation results confirm that the peak current of the inverter is restricted to the threshold value under symmetrical and asymmetrical faults for two operating modes of microgrid.

The problem of voltage recovery and current balancing has been a hot research topic in the field of DC microgrids. How to build a model that reflects the circuit and component-level control (e.g., inner control loops) characteristics and design a secondary controller based on it to accomplish the above output regulations is the concern of this paper. Accordingly, in this paper, based on the large-signal model of microgrids, the corresponding high-order fully actuated model is developed for DC microgrids, which is not only simple in form but also able to capture the details of the actual power system, such as the relationship between voltage and current. Further, a distributed predictive fully actuated secondary control strategy is proposed based on the developed model to achieve voltage recovery and accurate current sharing. Allowing one to design the secondary controller free from the constraints of physical coupling in the microgrid is one feature of this control strategy, while the other is the arbitrarily assignable closed-loop poles. An analytical model of the closed-loop DC microgrid system with predictive fully actuated secondary control is developed, and the analysis of stability and output current consensus is presented therewith. Extensive tests on a hardware system of a DC microgrid with solar panels and an MPPT controller are performed to validate the performance of the designed controller.

In the realm of power systems, load redistribution attacks (LRAs) involve the manipulation of measurements by attackers, leading operators to make decisions based on falsified estimated loads. Detecting LRAs is a well-explored area, but the critical post-detection phase, which requires operators to understand the attack's nature, remains under-addressed. Our paper introduces a novel probabilistic mechanism based on the Bayesian network model. It excels at not only detecting affected areas but also pinpointing the buses with manipulated loads under LRAs. Our work prioritizes simplicity by offering a straightforward calculation method that doesn't rely on complex tools or extensive system parameters. It also exhibits robustness against measurement noise. Acknowledging the paramount importance of data recovery, we highlight that post-detection measures are essential for minimizing errors in optimal power flow calculations. However, this data recovery is challenging due to the complexity of understanding the attacker's behavior. Our methodology employs kernel density estimation for precise probability density calculations and integrates the Bayesian Markov model to reduce computational complexity. Rigorous testing on the IEEE 118 bus system demonstrates its strong performance in producing consistently satisfactory results.

With the high penetration of renewable energy sources in power systems, DC microgrid clusters are widely installed and employed that can interface several types of renewable energy sources to different types of loads. However, being highly dependent on communication networks, DC microgrids are exposed to cyber-attacks. Therefore, in this paper, a resilient cooperative control method is proposed for DC microgrid cluster systems, that is able to achieve both the voltage regulation and power sharing in the presence of cyber-attacks. Firstly, a comprehensive microgrid cluster model is developed taking the grid forming converters, grid feeding converters, loads and line impedances into account. Based on the Lyapunov-based stability analysis, a design guideline for controller that depends only on parameters of the local microgrid is then presented. Next, steady state analysis is carried out showing that the controller is capable of eliminating the impact of cyber-attacks on the microgrid. Finally, the resilience performances of the provided control scheme are validated by experimental results.

Autonomous power control (APC) and energy management system (EMS) for space microgrids (MGs) on the Moon require well-designed operating references to ensure their safe operation considering the long-term goals of the mission. Oxygen and water, as two vital elements for human survival on the Moon, can be produced from the lunar regolith using the in-situ resource utilization (ISRU) and water treatment subsystems. Since ISRU is one of the highest power-demanding units in a lunar base, this article proposes a methodology for modeling the power demand profile for ISRU, considering oxygen and water management systems, which was not addressed in the literature. The article presents the power consumption model of the ISRU, considering the Sun's illumination profile at a candidate site near the Shackleton crater at the lunar south pole. Furthermore, a methodology is proposed to create oxygen and water consumption and wastewater generation profiles in the crew habitat. This article proposes models and algorithms to maintain the oxygen level and pressure in the crew habitat, transfer oxygen from ISRU to the associated oxygen tank, filter wastewater in the wastewater subsystem, transfer water produced from ISRU and freshwater from the wastewater subsystem to the associated water tank, considering oxygen and water consumption, and wastewater generation profiles of the crew habitat. Finally, an optimization framework is proposed to determine the power demand profile of ISRU by maintaining the oxygen in ISRU, the crew habitat, and water tanks at desired levels. It is observed that the ISRU power demand profile depends on the desired levels of oxygen and water in their associated tanks and their consumption/production rates. In addition, the interaction of different oxygen and water generation and consumption subsystems and storage tanks is thoroughly analyzed.

Energy management systems (EMSs) and autonomous power control (APC) for space microgrids (MGs) on the Moon need properly designed operating points and references to ensure the mission's safety. The oxygen and water requirements of the lunar base are supplied by the in situ resource utilization (ISRU) from the lunar regolith. ISRU is one of the most power-demanding subsystems in the lunar base. This article proposes an optimization methodology for sizing and optimal operation management of a photovoltaic (PV)-battery-based space MG. By solving the optimization problem, the optimal size of the PV array and battery, and the PV power generation and battery charging/discharging profiles are determined. First, the ISRU power demand profile is presented considering the oxygen and water management systems of the lunar base. Then, the optimization algorithm is employed to minimize the PV and battery mass and the total unused PV power generation while maintaining the desired level of energy in the battery considering system constraints. It is observed that curtailing the excess PV power generation plays a crucial role in minimizing the battery size and mass, thereby reducing the cost of the space mission.

Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted.

To eliminate low-frequency oscillations, this article proposes an active-damping method for multiple grid-tied virtual synchronous generators (VSGs) in a power plant. First, using Lyapunov’s indirect method, the damping ratio of multiple VSGs in parallel is analyzed. The average damping ratio reveals that this multi-VSG power plant can be poorly damped in a wide range of inertia and damping settings. Then, self- and mutual-damping controllers are developed to suppress self- and mutually induced low-frequency power oscillations, respectively. For practical implementation, an adaptive tuning algorithm that enables automatic realization is proposed. Through a reassessment, a remarkable damping-ratio improvement is validated. Moreover, the inertial response improvement is validated by the frequency response analysis. Finally, simulations in Digsilent/PowerFactory and experiments are performed to demonstrate the accuracy of the analyses and the effectiveness of the proposed method.

This paper aims to investigate the adversarial effects of man/machine-in-the-middle (MITM) attacks on interconnected direct current microgrid (MG) clusters, their detection and countermeasures for the first time. Therefore, a novel multi-layered attack recovery (ARF) scheme coordinated with state reconstruction has been formulated in the higher layers to identify such mishaps and provide cyber-resiliency to the MG power system operation at various levels of the hierarchical structure. The proposed countermeasures are based on synchronisation errors of the consensus variables and aid in preventive isolation of the healthy MG clusters or converters, thereby avoiding events which could potentially cause cascading effects. Its efficacy is demonstrated through theoretical analysis and extensive time domain simulations in MATLAB/Simulink under various scenarios of unidirectional and bidirectional MITM alongwith communication latencies. Lastly, controller hardware-in-loop (cHIL) implementation is employed to validate the security of real-time operations of MGs against stealthy MITM attacks.

This paper presents an innovative passivity-based $L_{2}$ -gain performance $(L_{2}$ -GP) adaptive robust control method for the design of primary and secondary frequency control in the low-inertia microgrid with lines and the inverter-interfaced generation. First, by exploiting and analyzing the internal structural properties, the Port-controlled Kuramoto-Hamiltonian model with dissipation for the microgrid system is derived. Combining the dynamics of Kuramoto oscillators with energy viewpoints and following the physical features of dynamic energy coordination in the microgrid, an adaptive robust $L_{2}$ -GP decentralized secondary control is developed to guarantee frequency restoration and active power sharing. An adaptive mechanism is adopted to estimate the electrical parameters so that the parameter randomness can be overcome and fast transient response, high performance, and robust stability can be achieved. Via local measurements, the decentralized framework accordingly obviates the need of any communication links for information broadcast or exchange. Finally, the comprehensive case studies are presented to validate satisfactory performance under rapid randomness and flexibility during plug-and-play operations.

Aggregated electrical vehicles (EVs) can flexibly serve grid frequency regulation (FR) with adjustable FR capacity (FRC) via vehicle-to-grid (V2G) technology. Therefore, current research applies integral reinforcement learning (IRL) to FR as it can easily solve difficult modeling and optimization problems. However, communication between EVs is vulnerable to denial of service (DoS) attacks, which can significantly degrade FR performance and even destabilize V2G FR systems. This paper proposes an adaptive V2G FRC-based FR scheme with IRL to improve FR resilience and mitigate FR performance degradation against DoS attacks. The proposed scheme optimizes V2G control by IRL without analytical models, integrating an event-triggered mechanism to reduce communication burden. It adapts V2G FRC to attack intensity to minimize frequency deviation and mitigate the impact of DoS attacks. The analytical estimation of convergence rate establishes the quantitative relationships among control performance, V2G FRC, and attack intensity, thereby deriving an adaptive mechanism. The theoretical analysis of the proposed scheme yields stability conditions that guarantee the FR performance. The simulations were performed on the IEEE 39-bus test system to verify the effectiveness and advantages of the proposed scheme. The results indicate that V2G FRC should be scaled down to mitigate performance degradation when intensive attacks occur.

The frequency-domain passivity theory suggests that incorporating passive output admittance in grid-connected inverters (GCIs) can effectively mitigate system instability issues. This theory has been widely recognized and applied in design guidelines for active damping (AD) and passive damping (PD) methods tailored explicitly for LCL-type GCIs. However, AD methods have a limitation in that they can only reshape the output admittance of GCIs to be passive (with a nonnegative real part) up to the Nyquist frequency. This limitation arises from the inherent characteristics of the digital control system. Similarly, existing passivity-based PD design cases primarily focus on addressing instability issues that occur below the Nyquist frequency. To overcome this limitation and achieve full-frequency passive output admittance, this article introduces a resistor–capacitor (RC) branch-based PD scheme. It provides a comprehensive design guideline that can be applied to different scenarios involving inverter-side or grid-side current control, regardless of whether AD methods are utilized. By incorporating this RC-PD scheme, the designed GCIs achieve full-frequency passive output admittance, effectively preventing potential harmonic oscillations both below and above the Nyquist frequency. Finally, comparative experimental results for different cases are demonstrated to verify the effectiveness and superiority of the proposed approach.

A three-level T-type converter interfaced with an LCL filter (LCL-3LT2C) has been widely used in low-voltage and high-quality photovoltaic (PV) systems. The control of LCL-3LT2C is a multiobjective optimization problem (MOOP), which is suitable to apply model predictive control (MPC). Although the MPC has fast dynamic response, accurate transient control, and easy handling of MOOP problems, its control performance is still highly dependent on the system model used for the control system. If the system parameter mismatch between the plant and the MPC controller occurs, the performance of the control object will degrade. To solve this problem, a novel adaptive ultralocal model-free predictive control for LCL-3LT2C is proposed. First, the relationship between the NP voltage and the converter current is analyzed, and a dynamic antidisturbance factor is introduced into the reference of the converter current for NP voltage suppression. Second, to improve the model estimation accuracy, a new ultralocal model is introduced, which decouples the known and unknown terms of the system into the linear known and the nonlinear unknown terms. Finally, an extended sliding-mode disturbance observer is considered to estimate the nonlinear unknown term. The proposed method simplifies the control of NP voltage, converter current, and grid current. Experimental results on the 10-kW laboratory prototype demonstrate its superior performance over existing techniques.

In this article, the detailed steps for the derivation of linearized minimum current stress modulation scheme for single-phase bidirectional and isolated dual active bridge ac–dc converters is presented. In order to reduce the current stress of the converter, a Lagrange multiplier method scheme is designed to obtain the control coordinates constraint on the minimum value of the current stress. Compared with the conventional minimum current stress control scheme, the proposed scheme realizes the linearization of power control, which significantly reduces the complexity of the controller algorithm. Moreover, the synchronous inverter control applied to the back-stage full-bridge is designed. Thus, the single stage power conversion is realized and the converter topology is electrolytic capacitorless, which promote the improvement of system reliability and power density. The impact of the zero-voltage switching (ZVS) scheme is analyzed in detail, and the adaptive-ZVS scheme for less system loss is selected. Finally, experimental results confirm the validity and feasibility of the proposed control scheme.

In light of the growing integration of renewable energy sources in power systems, the adoption of DC microgrids has become increasingly popular, due to its simple structure, having no frequency, power factor concerns. However, the dependence of DC microgrids on cyber-networks also makes them susceptible to cyber-attacks. Potential cyber- attacks can disrupt power system facilities and result in significant economic and loss of life. To address this concern, this paper presents an attack-resilient control strategy for microgrids to ensure voltage regulation and power sharing with stable operation under cyber-attack on the actuators. This paper first formulates the cyber-security problem considering a distributed generation based microgrid using the converter model, after which an attack-resilient control is proposed to eliminate the actuator attack impact on the system. Steady state analysis and root locus validation illustrate the feasibility of the proposed method. The effectiveness of the proposed control scheme is demonstrated through simulation results.

This article proposes a decoupling control method to eliminate frequency coupling in three-phase grid-tied system. Firstly, the admittance model of three-phase LCL-type three-phase grid-tied converter (GTC) considering DC-bus voltage control (DVC) loop and phase-locked loop (PLL) is established in dq-domain frame, and the influence of asymmetrical DVC and PLL control structure on frequency coupling oscillation is analyzed. Then decoupling factors are added to the DVC loop and current control (CC) loop to achieve that the off-diagonal elements of the sequence admittance matrix of the GTC are 0, which means the frequency coupling in the GTC is eliminated. Therefore, the GTC system can be regarded as a single input single output (SISO) system, and the stability can be analyzed by the classic Nyquist criterion in the sequence-domain frame. Compared with the double input double output (DIDO) system, the resulted SISO system convenient for calculating the stability margin of the system and guiding parameter design. In addition, the SISO system is easier to be analyzed on the oscillation and resonance mechanism, and the analysis results can be used to optimize the design of the converter controller, grid planning and operation. Finally, simulation and experiment verify the feasibility and effectiveness of the proposed decoupling control method.

Control design of advanced grid synchronization systems is complex as they are often adaptive nonlinear feedback systems with one or more filtering networks and feedback loops in their structure. This article intends to contribute to addressing this issue. It is shown that the phase or frequency estimation loop of many advanced grid synchronization systems, including $3\phi$ and $1\phi$ phase-locked loops and frequency-locked loops equipped with in-loop filters and prefilters, can be well-approximated by a standard type-2 control system in the low-frequency range and an extension of the symmetrical optimum (SO) approach could be used to efficiently tune their control parameters. To better understand all this, an overview of the SO method and its extended version is provided and several case studies are presented. The limitations of this design approach and possible solutions are also discussed.

Due to its outstanding merits, such as quick response, multiobjective optimization, and simple principle, model predictive control (MPC) has been widely used in power converters and motor-drive systems. However, MPC highly relies on the precise circuit parameters and control models, and cannot be used in unknown circuit relationships. To solve this issue, this article presents a model-free predictive control (MFPC) with multiobjective optimization (MOO) for two parallel three-level T-type rectifiers (3LT2Rs). First, the main control objectives of 3LT2Rs are analyzed, and the overall control scheme of the double closed-loop control is established. Second, based on the mathematical model of the parallel system, an MOO-MFPC for neutral-point voltage balance, current tracking, and zero-sequence circulating current elimination is proposed, which does not require any prior knowledge of the circuit parameters and circuit models, and it can achieve MOO control without weighting factors and its priority is not fixed. To solve the current difference updating stagnation problem in MOO-MFPC, a synchronous updating method is designed, which is faster than that of a single rectifier. Finally, the proposed method is tested on a hardware prototype of a 10-kW and a 5-kW parallel rectifier. Numerous experimental results demonstrate the merits of this method over the existing methods under several typical scenarios.

For the cascaded H-bridge system, the existing decentralized methods are mainly focused on single-phase systems. Designing a decentralized method for the three-phase cascaded H-bridge system is more challenging, particularly, for achieving phase-to-phase frequency synchronization and three-phase voltage balance without real-time communication among each distributed generation (DG). To achieve this, this article proposes a decentralized master-slave method for three-phase cascaded H-bridge systems, where no communication is required for each local control unit of DGs. The overall control is divided into two parts. One part is for the master DG to realize phase synchronization among phases A, B, and C, which is designed by modifying the power factor angle through droop control. The other part is for slave DGs to achieve frequency synchronization of the modules in each phase, which adopts the power factor angle droop control. Small signal stability analysis based on fast and slow time scale separation is carried out for the proposed method. Last, the control-hardware-in-loop tests and experimental results prove the effectiveness of the proposed method.

A parallel T-type rectifier connection is often required to improve the system capacity and stability in high-power applications. However, the parallel rectifier faces the challenges of zero-sequence circulating current (ZSCC) elimination, neutral-point (NP) voltage balance, dc voltage stability, and power sharing. First, to solve the multiobjective optimization problem of two parallel three-level T-type rectifiers with LCL filters (LCL-3LT2 Rs), a double closed-loop control scheme is adopted. In this scheme, an impartial sequential model predictive control (ISMPC) is proposed as the inner loop controller for ZSCC elimination and NP voltage balance, and an adaptive droop control with voltage feedforward is designed as the outer loop controller to achieve dc voltage stability and power sharing for each rectifier based on its capacity. Second, the main influencing factors of ZSCC in LCL-3LT2Rs are analyzed, and ZSCC elimination is considered as one control objective in ISMPC. Finally, ISMPC is proposed to solve the problem that sequential model predictive control (SMPC) could not select the optimal solution due to the fixed priority and the excessive process of only controlling a single objective. The proposed method is tested on a prototype hardware platform of 10- and 5-kW parallel rectifiers. Experiment results demonstrate the superiority of this method over existing methods under several typical scenarios.

Operation and control dynamics of islanded DC microgrids (DC mGs) have received enormous interest recently in distribution system management. In this regard, research concern on droop-controlled distributed generations (DGs) integrated within the standalone DC mG is becoming more profound. This paper proposes an optimal operation of droop-controlled standalone DC mG with combined small-signal stability and economic-environment-related objectives. The proposed approach optimizes the principal eigenvalue that affects the system stability and two other objectives. An eigen value-based stability analysis for network configurations, with the possibility of its buses solely connected to either dispatchable DG or constant power load (CPL), is proposed. Moreover, uncertainties involved in mG network variables that originate due to the integration of solar PV generation with load consumption were considered and modelled with relevant probability characterization. A recent swarm-based intelligent technique (dragonfly algorithm) for optimization of droop parameters is adopted in the proposed approach. A unique bi/tri – objective combinations are solved, and obtained results are discussed. To show the adaptability of the proposed approach for any given DC mG network, a standalone 6-bus mG was adopted to verify the applicability. Furthermore, the time-domain simulations were carried out on a sample 3-bus DC mG to validate the proposed strategy.

The problem of voltage restoration and current balancing has been a hot topic in the study of DC microgrids (MGs), and how to engineer a secondary controller to solve the conflict between these two is the concern of this paper. With the above consideration, an optimal distributed data-driven secondary control strategy is proposed, relying entirely on the input and output data of DC MGs. The proposed framework completes the design of a secondary control strategy based on a data model for the first time, which incorporates the physical coupling relationship between voltage and current into the controller design and is independent of the global circuit parameters and topology information. By means of a proposed cost function, the designed control strategy enables DC MGs to achieve better output current quality at steady state. Unlike the existing schemes based on average voltage observer, this paper resorts to a combination of limiting the voltage reference value generated by the secondary controller and a current cooperative strategy based on the data model to achieve an easy-to-use trade-off between the two objectives of voltage regulation and current sharing. Then, an analytical model of a closed-loop DC MG system under the proposed control scheme is developed, and the analysis of stability and consensus of weighted output current is given accordingly. Finally, the proposed control strategy is tested on a hardware DC MG system with solar panels and a maximum power point tracking (MPPT) controller.

In many grid synchronization systems (GSSs), amplitude and phase estimation loops are dynamically coupled. It means that a change in the input voltage amplitude may result in spurious phase/frequency transients in the GSS output and vice versa. This article aims to explain the reason behind this coupling and present some guidelines to mitigate it. Several case studies are provided, and numerical and experimental results are presented to make all this more clear.

This paper proposes a novel virtual inertia controller for converters in power systems, which can solve the system's nonlinearity for frequency support. First, the system dynamics are formulated as a nonlinear state-space, in which the reciprocal of inertia is modeled as control input. Correspondingly, a cost function is defined by considering frequency deviation and rate of change of the frequency, which can preserve a tradeoff between critical frequency limits and respective control energy. Following, the optimal frequency regulation problem is solved by using an online adaptive dynamic programming method, where the actor and critic neural networks are constructed to approximate the optimal control input and optimal cost function, respectively. After that, the small-signal analysis is provided to identify the stability of the converter under the proposed controller. Finally, simulation results verify that the frequency response of the system is significantly improved, while retaining more DC side energy.

The increasing demand for decarbonization of marine transportation motivates the utilization of low-carbon resources. Among different options, fuel cells are drawing attention. The selection of fuel cell (FC) and the design of energy management strategy would have a great impact on the vessel’s operational efficiency, and thereby needs to be considered carefully. The objective of this paper is to develop energy management system (EMS) to reduce the fuel consumption of a hybrid fuel cell/battery ship. To this end, a day-ahead EMS scheme is proposed that takes full use of information including ship cruising routines and the degradation status of the fuel cell modules. The developed EMS is optimization-based and conducted off-line to provide guideline for the next-day power generation plan. In addition, three power allocating strategies across the multiple fuel cell modules are considered and compared (equal, independent, and sequential). A sequential rotation procedure is proposed to reduce the degradation rates of the fuel cell modules. Simulation results show that the proposed EMS can effectively improve the fuel economy of the hybrid ship while enhancing sufficient energy backup throughout the full voyage. In addition, comparisons between different FC configurations implies that the independent distribution has the highest fuel efficiency, and with the proposed rotation procedure, the sequential distribution can effectively improve the fuel efficiency by up to 23.2%.