Search Results (98)

With the advancement in the “dual carbon” strategy and the integration of high proportions of renewable energy sources, AC/DC ultra-high-power grids are facing new security challenges such as commutation failure and multi-infeed coupling effects. Fault diagnosis, as an important tool for assisting power grid dispatching, is essential for maintaining the grid’s long-term stable operation. Traditional fault diagnosis methods encounter challenges such as limited samples and data quality issues under complex operating conditions. To overcome these problems, this study proposes a fault sample data enhancement method based on the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP). Firstly, a simulation model of the AC/DC hybrid system is constructed to obtain the original fault sample data. Then, through the adoption of the Wasserstein distance measure and the gradient penalty strategy, an improved WGAN-GP architecture suitable for feature learning of the AC/DC hybrid system is designed. Finally, by comparing the fault diagnosis performance of different data models, the proposed method achieves up to 100% accuracy on certain fault types and improves the average accuracy by 6.3% compared to SMOTE and vanilla GAN, particularly under limited-sample conditions. These results confirm that the proposed approach can effectively extract fault characteristics from complex fault data. Full article

Microgrids (MGs) technologies, with their advanced control techniques and real-time monitoring systems, provide users with attractive benefits including enhanced power quality, stability, sustainability, and environmentally friendly energy. As a result of continuous technological development, Internet of Things (IoT) architectures and technologies are becoming more and more important to the future smart grid’s creation, control, monitoring, and protection of microgrids. Since microgrids are made up of several components that can function in network distribution mode using AC, DC, and hybrid systems, an appropriate control strategy and monitoring system is necessary to ensure that the power from microgrids is delivered to sensitive loads and the main grid effectively. As a result, this article thoroughly assesses MGs’ control systems and groups them based on their degree of protection, energy conversion, integration, advantages, and disadvantages. The functions of IoT and monitoring systems for MGs’ data analytics, energy transactions, and security threats are also demonstrated in this article. This study also identifies several factors, challenges, and concerns about the long-term advancement of MGs’ control technology. This work can serve as a guide for all upcoming energy management and microgrid monitoring systems. Full article

Power systems need to meet the ever-increasing demand for higher quality and reliability of electricity in distribution systems while remaining sustainable, secure, and economical. The globe is moving toward using renewable energy sources to provide electricity. An evaluation of the influence of artificial intelligence (AI) on the accomplishment of SDG7 (affordable and clean energy) is necessary in light of AI’s development and expanding impact across numerous sectors. Microgrids are gaining popularity due to their ability to facilitate distributed energy resources (DERs) and form critical client-centered integrated energy coordination. However, it is a difficult task to integrate, coordinate, and control multiple DERs while also managing the energy transition in this environment. To achieve low operational costs and high reliability, inverter control is critical in distributed generation (DG) microgrids, and the application of artificial neural networks (ANNs) is vital. In this paper, a power management strategy (PMS) based on Inverter Control and Artificial Neural Network (ICANN) technique is proposed for the control of DC–AC microgrids with PV-Wind hybrid systems. The proposed combined control strategy aims to improve power quality enhancement. ensuring access to affordable, reliable, sustainable, and modern energy for all. Additionally, a review of the rising role and application of AI in the use of renewable energy to achieve the SDGs is performed. MATLAB/SIMULINK is used for simulations in this study. The results from the measures of the inverter control, m, VL-L, and Vph_rms, reveal that the power generated from the hybrid microgrid is reliable and its performance is capable of providing power quality enhancement in microgrids through controlling the inverter side of the system. The technique produced satisfactory results and the PV/wind hybrid microgrid system revealed stability and outstanding performance. Full article

A grid-connected converter is the interface between renewable energy power generation systems, such as solar power generation, wind power, hydropower, etc., and the power grid, responsible for the stable and efficient transmission of electric energy generated by renewable energy power generation systems to the grid. In order to realize local access for distributed photovoltaic power generation devices and energy storage devices, a composite three-port converter has the advantages of small size, low cost and high power density compared with a combined three-port converter. In view of the current problems of the existing compound three-port (AC/DC/DC) converters, such as DC and AC circulating current in current composite three-port converters and the harmonic control problem, the proposed compound three-port topology consists of a full-bridge inverter with six switching tubes, a zigzag transformer, two sets of filter inductors and two filter capacitors. Among them, the power frequency transformer adopts the zigzag connection method, which can effectively restrain the AC circulation and eliminate the DC magnetic flux of the iron core while introducing the third port. Firstly, the principle of AC/DC and DC/DC power conversion in the composite three-port topology is analyzed, which has higher efficiency than other topologies. Secondly, the topology control strategy is analyzed, and a two-loop hybrid current control method with improved current loop is proposed. When the DC-side voltage fluctuates, the DC offset of the battery can effectively improve the stability of the network side. Through the MATLAB/Simulink simulation experiment platform, the high efficiency of energy conversion and stable grid-connected operation characteristics are verified. Finally, the experiment of integrating into the power grid was carried out. Experiments were used to verify the effectiveness and feasibility of the proposed topology and strategy. The experimental results show that Total Harmonic Distortion (THD) can be controlled below 3%. Full article

The rapid growth of renewable energy and increasing electricity demand pose challenges to the reliability and flexibility of traditional distribution networks. To address these issues, the construction of AC/DC hybrid distribution networks (AC/DC-HDNs) based on existing AC grids has become a promising solution. However, planning the expansion of such networks faces challenges like complex device and line topologies, dynamic fluctuations in distributed generation (DG) and load, and high power electronics costs. This paper proposes a time- and space-integrated expansion planning method for AC/DC-HDNs. The approach builds a distribution grid model based on graph theory, integrating the spatial layouts of AC distribution lines, DGs, main grids, and loads, while capturing dynamic load and renewable energy generation characteristics through time-series analysis. A modified graph attention network (MGAT)-based deep reinforcement learning (DRL) algorithm is used for optimization, balancing economic and reliability objectives. The simulation results show that the modified algorithm outperforms traditional algorithm in terms of both training efficiency and stability, with a faster convergence and lower fluctuation in cumulative rewards. Additionally, the proposed algorithm consistently achieves higher cumulative rewards, demonstrating its effectiveness in optimizing the expansion planning of AC/DC-HDNs. Full article

As the transition to clean energy accelerates, wind energy plays a crucial role in power generation, particularly in remote onshore and offshore locations. The integration of hybrid AC/DC networks with multi-terminal high-voltage direct current (MTHVDC) systems enhances power transfer capability and reliability. However, maintaining stable operation under both normal and disturbed conditions remains challenging. This paper applies the Flexible Universal Branch Model (FUBM) to hybrid AC/DC networks incorporating MTHVDC, providing a unified framework for power flow analysis. Unlike conventional methods that separately analyze AC and DC systems, the FUBM enables simultaneous modeling of both, improving computational efficiency and accuracy. Additionally, the paper introduces advanced control strategies to regulate active power transfer from offshore wind farms to onshore grids while maintaining voltage stability. The proposed approach is validated under steady-state and disturbance scenarios, including converter outages, within the CIGRE B4 system, which is a complex multi-terminal network interconnected with numerous converters. The results demonstrate the effectiveness of the FUBM in ensuring stable operation, offering new insights into unified power flow modeling. This study lays the groundwork for future advancements in AC/DC power systems with MTHVDC integration. Full article

The evolution of aircraft power systems has been driven by increasing electrical demands and advancements in aviation technology. Background: This study provides a comprehensive review and experimental validation of on-board electrical network development, analyzing power management strategies in both conventional and modern aircraft, including the Mi-24 helicopter, F-22 multirole aircraft, and Boeing 787 passenger airplane. Methods: The research categorizes aircraft electrical systems into three historical phases: pre-1960s with 28.5 V DC networks, up to 2000 with three-phase AC networks (3 × 115 V/200 V, 400 Hz), and post-2000 with 270 V DC networks derived from AC generators via transformer–rectifier units. Beyond theoretical analysis, this work introduces experimental findings on hybrid-electric aircraft power solutions, particularly evaluating the performance of the Modular Power System for Aircraft (MPSZE). The More Electric Aircraft (MEA) concept is analyzed as a key innovation, with a focus on energy efficiency, frequency stability, and ground power applications. The study investigates the integration of alternative energy sources, including photovoltaic-assisted power supplies and fuel-cell-based auxiliary systems, assessing their feasibility for aircraft system checks, engine startups, field navigation, communications, and radar operations. Results: Experimental results demonstrate that hybrid energy storage systems, incorporating lithium-ion batteries, fuel cells, and photovoltaic modules, can enhance MEA efficiency and operational resilience under real-world conditions. Conclusions: The findings underscore the importance of MEA technology in the future of sustainable aviation power solutions, highlighting both global and Polish research contributions, particularly from the Air Force Institute of Technology (ITWL). Full article

There is a paradigm shift to hybrid (AC/DC) networks that integrate both AC and DC to meet growing energy demands, mitigate global warming, and interconnect distributed energy sources (DERs). However, the unique characteristics of AC/DC faults, the mutual interaction of hybrid lines, the harmonic components of converters/inverters, multiple directions of energy flow, and varying current levels have challenged the existing protection algorithms. Therefore, this paper presents a data-driven coordination AC/DC fault protection algorithm. The algorithm utilizes faulty voltage and current signals to retrieve the precise time-domain characteristics of AC, DC, and intersystem (IS) faults to develop the algorithm. The proposed algorithm consists of four stages: stage 1 includes the detection of faults, stage 2 identifies the fault as either AC or DC, stage 3 classifies the respective AC and DC faults, and stage 4 locates the AC/DC fault precisely. The hybrid test system is developed in a MATLAB/Simulink environment, and the data-driven algorithm is trained and tested in Python. The extensive simulation results for multiple fault cases, either AC or DC, and the comparisons of various performance indicators confirm the effectiveness of the developed algorithm, which performs efficiently under a noisy and extended hybrid AC/DC network. Compared to other schemes, the proposed coordination protection approach can enhance the speed and accuracy of hybrid AC/DC networks. Full article

With the widespread integration of renewable energy into distribution networks, energy storage systems are playing an increasingly critical role in maintaining grid stability and sustainability. Hydrogen, as a key zero-carbon energy carrier, offers unique advantages in the transition to low-carbon energy systems. To facilitate the coordination between hydrogen and renewables, this paper proposes a flexible on-grid and off-grid control method for an electric–hydrogen hybrid AC-DC microgrid which integrates photovoltaic panels, battery energy storage, electrolysers, a hydrogen storage tank, and fuel cells. The flexible control method proposed here employs a hierarchical structure. The upper level adopts a power management strategy (PMS) that allocates power to each component based on the states of energy storage. The lower level utilises the master–slave control where master and slave converters are regulated by virtual synchronous generator (VSG) and active and reactive power (PQ) control, respectively. In addition, a pre-synchronisation control strategy which does not rely on traditional phase-locked loops is introduced to enable a smooth transition from the off-grid to on-grid mode. The electric–hydrogen microgrid along with the proposed control method is modelled and tested under various operating modes and scenarios. The simulation results demonstrate that the proposed control method achieves an effective power dispatch within microgrid and maintains microgrid stability in on- and off-grid modes as well as in the transition between the two modes. Full article

The large-scale integration of renewable energy sources and new loads, such as distributed photovoltaics and electric vehicles, has resulted in frequent power quality issues within distribution networks. Traditional AC distribution networks lack the necessary flexibility and have limited capacity to accommodate these new energy sources and loads. Transforming the conventional distribution network into an AC-DC hybrid network using flexible interconnection devices like Voltage Source Converters can enhance the network’s flexibility, mitigating the power quality challenges arising from the integration of renewable energy and new loads. Electric buses, with their substantial capacity, mobility, and centralized management, offer potential as mobile energy storage. They can participate in the dispatching of the distribution network, thereby improving the network’s flexibility in power regulation. This paper proposes a coordinated optimization approach that integrates electric buses and VSCs for distribution network dispatch. This method enables electric buses to assist in power dispatch without interfering with their primary public transport duties, thus enhancing the network’s capacity to absorb new energy sources and loads. Firstly, considering the mobility characteristics of electric buses, a multi-layer stochastic Time–Space Network model is developed for bus dispatching. Secondly, an optimization model is constructed that accounts for the coordination of charging and discharging power between VSCs and electric buses, with the objective of minimizing the network losses in the distribution system. Finally, the proposed model is transformed into a second-order cone programming formulation, facilitating its solution through convex optimization techniques. The effectiveness of the proposed approach is demonstrated through a case study. Full article

The integration of hybrid alternating current (AC) and direct current (DC) networks has gained relevance due to the growing demand for more flexible, efficient, and reliable electrical systems. A key aspect of this integration is the parallelization of power converters, which presents several technical challenges, such as current sharing imbalances, circulating currents, and control complexity. This paper proposes a distributed control architecture for parallel resonant CLLC dual active bridge (DAB) converters to address these issues in hybrid AC–DC networks and microgrids. The approach includes a master voltage controller to regulate the output voltage and distributed local current controllers to ensure load balance. The approach minimizes the difference between the output and input voltages, allowing for independent control of power flow. Simulation and experimental results show significant improvements. The system stability has been demonstrated experimentally. Transient response has been improved with response time 80% lower using the feed-forward term. The system maintained stability with current sharing deviations below 3% under full and low load conditions. Finally, scalability is ensured by the proposed distributed controller because the central power controller is not affected by the number of units in parallel used in the application. This solution is suitable for advanced hybrid networks and microgrid applications. Full article

With the rapid development of the Internet, cloud computing, big data, artificial intelligence, and other information technologies, data centers have become a crucial part of modern society’s infrastructure, which puts forward very high requirements for the safety and reliability of power supply. Most of the servers, networks, and other equipment in data centers are DC-driven loads, which can significantly enhance resource utilization efficiency by efficiently accessing the DC power supply through voltage source converter-based high-voltage direct current transmission and distribution technology. For this reason, this paper first proposes a multi-level network topology design method for AC/DC distribution systems in the context of data centers. Based on the analysis of the adaptability of AC/DC distribution systems in data center access, the design and analysis of its multi-level network topology is carried out at the physical level for the construction of hybrid AC/DC distribution systems in data center. On this basis, a time series multi-scenario planning model of AC/DC distribution system with distributed generation in data center is established, the configuration strategy of AC/DC distribution system is investigated, and a time series multi-scenario optimization planning method for hybrid AC/DC distribution systems in data centers is proposed. Finally, the validity of the proposed method is verified by simulation examples. Full article

AC/DC hybrid distribution networks with power electronic transformers (PETs) as distribution hubs are in line with the future development direction of the AC/DC hybrid distribution network. Unlike traditional transformers, power electronic transformers introduce new node types and may transform the network topology from radial to ring structures. These changes render traditional power flow calculation methods inadequate for achieving satisfactory results in AC/DC hybrid networks. In addition, existing commercial power flow calculation software packages are mainly based on the traditional AC power flow calculation method, which have limited support for the DC network. Especially when the DC network is coupled with the AC network, it is difficult to achieve a unified calculation of its power flow. To address these challenges, this paper proposes a novel power flow calculation method for ring AC/DC hybrid distribution networks with power electronic transformers. The proposed method is based on the alternating iterative method to ensure compatibility with mature AC power flow calculation programs in commercial software, thereby improving the feasibility of engineering applications. Firstly, the steady-state power flow calculation model of PET is constructed by analyzing that the working principle and control modes of power electronic transformer are proposed based on the source-load attributes of its connected subnetworks. According to the characteristics of the power electronic transformer, AC distribution network, and DC distribution network, a hybrid alternating iteration method combining the high computational accuracy of the Newton–Raphson (NR) method with the high efficiency of the Zbus Gaussian method in dealing with ring networks is proposed. On this basis, the power flow calculation model of the AC/DC hybrid distribution network with power electronic transformers is established. Finally, the simulation of the constructed 44-node ring AC/DC hybrid distribution network example is carried out. The simulation results show that the proposed method can not only converge reliably when the convergence accuracy is 1 × 10⁻⁶ p.u., but also ensure that the voltage magnitudes of all nodes are above 0.96 p.u. whose maximum offset value is 0.789% when the outputs of the connected distributed generations fluctuate, which verifies the effectiveness and accuracy of the proposed method. Full article

Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow convergence issues. Moreover, as electrical grid networks become increasingly connected, the risk of cyberattacks grows, and traditional physics-based anomaly detection methods face challenges such as reliance on predefined models, high computational demands, and limited scalability for complex, large-scale data. To address the limitations of the existing approaches, this paper first proposes a novel sigma-delta modulation (SDM) controller for BESSs in solar photovoltaic (PV)-connected microgrids. The performance of SDM has been compared with those of the proportional–integral (PI) controller and fuzzy logic controller (FLC). Also, this paper proposes an improved ensemble-based method to detect the false data injection (FDI) and denial-of-service (DoS) attacks on the BESS controller. The performance of the proposed detection method has been compared with that of the traditional ensemble-based method. Four PV-connected microgrid systems, namely the solar DC microgrid, grid-connected solar AC microgrid, hybrid AC microgrid with two BESSs, and hybrid AC microgrid with a single BESS, have been considered to show the effectiveness of the proposed control and detection methods. The MATLAB/Simulink-based results show the effectiveness and better performance of the proposed controller and detection methods. Numerical results demonstrate the improved performance of the proposed SDM controller, with a 35% reduction in AC bus voltage error compared to the conventional PI controller and FLC. Similarly, the proposed SAMME AdaBoost detection method achieves superior accuracy with an F1 score of 95%, outperforming the existing ensemble approaches. Full article

A fuzzy cascaded PI−PD (FCPIPD) controller is proposed in this paper to optimize load frequency control (LFC) in the linked electrical network. The FCPIPD controller is composed of fuzzy logic, proportional integral, and proportional derivative with filtered derivative mode controllers. Utilizing renewable energy sources (RESs), a dual-area hybrid AC/DC electrical network is used, and the FCPIPD controller gains are designed via secretary bird optimization algorithm (SBOA) with aid of a novel objective function. Unlike the conventional objective functions, the proposed objective function is able to specify the desired LFCs response. Under different load disturbance situations, a comparison study is conducted to compare the performance of the SBOA-based FCPIPD controller with the one-to-one (OOBO)-based FCPIPD controller and the earlier LFC controllers published in the literature. The simulation’s outcomes demonstrate that the SBOA-FCPIPD controller outperforms the existing LFC controllers. For instance, in the case of variable load change and variable RESs profile, the SBOA-FCPIPD controller has the best integral time absolute error (ITAE) value. The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. Furthermore, the work is expanded to include electric vehicle (EV), high voltage direct current (HVDC), generation rate constraint (GRC), governor dead band (GDB), and communication time delay (CTD). The result showed that the SBOA-FCPIPD controller performs well when these components are equipped to the system with/without reset its gains. Also, the work is expanded to include a four-area microgrid system (MGS), and the SBOA-FCPIPD controller excelled the SBOA-CPIPD and SBOAPID controllers. Finally, the SBOA-FCPIPD controller showed its superiority against various controllers for the two-area conventionally linked electrical network. Full article