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Abstract The growth of marine resources exploitation has led to increased research interest in electro‐hydraulic systems for marine simulation. This study proposes a proportional plus resonant (PR) controller to achieve high tracking performance for electro‐hydraulic systems. Due to the complex structure and non‐linear flow dynamics, establishing accurate mathematical models of electro‐hydraulic systems is challenging. The local linearization technique is applied to simplify the process of model establishment. The system gain is limited by the stability margin due to the input delay, resulting in a phase delay between the real trajectory and the desired reference. To compensate for the phase delay in tracking periodic reference with the traditional proportional and integral controller, a resonant item is added into the controller. The stability analysis of the closed‐loop system is performed using Routh‐Hurwitz criterion. Furthermore, the controller parameters are tuned based on the frequency characteristic to achieve high tracking performance and maintain the adequate stability margin. The effectiveness of the proposed PR controller in tracking periodic references is validated through numerical simulations and practical experiments.

The increasing adoption of renewable energy, particularly photovoltaic (PV) power, has highlighted the importance of accurate PV power forecasting. Despite advances driven by deep learning (DL), significant challenges remain, particularly in capturing the long-term dependencies essential for accurate forecasting. This study presents TransPVP, a novel transformer-based methodology that addresses these challenges and advances PV power forecasting. TransPVP employs a deep fusion technique alongside a multi-task joint learning framework, effectively integrating heterogeneous data sources and capturing long-term dependencies. This innovative approach enhances the model’s ability to detect patterns of PV power variation, surpassing the capabilities of traditional models. The effectiveness of TransPVP was rigorously evaluated using real data from a PV power plant. Experimental results showed that TransPVP significantly outperformed established baseline models on key performance metrics including RMSE, R2, and CC, underscoring its accuracy, predictive power, and reliability in practical forecasting scenarios.

Abstract The monitoring and control of DC-DC converters have become key issues since DC-DC converters are gradually playing increasingly crucial roles in power electronics applications such as electric vehicles and renewable energy systems. As an emerging and transforming technology, the digital twin, which is a dynamic virtual replica of a physical system, can potentially provide solutions for the monitoring and control of DC-DC converters. This work discusses the design and implementation of the digital twin DC-DC converter in detail. The key features of the physical and twin systems are outlined, and the control architecture is provided. To verify the effectiveness of the proposed digital twin method, four possible cases that may occur during the practical control scenarios of DC-DC converter applications are discussed. Simulations and experimental verification are conducted, showing that the digital twin can dynamically track the physical DC-DC converter, detect the failure of the physical controller and replace it in real time.

To easily control distributed photovoltaic power stations and provide fast responses for their regulation, this paper proposes an optimal cluster partitioning method based on a graph-based genetic algorithm (GA). In this approach, a novel structure utilizing a graph model is designed for chromosomes, and enhancements are made to the selection, crossover, and mutation models of the evolutionary to generate a search population for dividing distributed photovoltaic (PV) power grids into clusters. Moreover, the modularity and active power balance degree of the classic Girvan–Newman algorithm are employed as optimal objectives to establish a basis and evaluation system for cluster partitioning. Additionally, a Simulink simulation platform is established for the IEEE 33-bus time-varying scenario to validate its performance. A comparative analysis with some classic PV cluster partitioning algorithms demonstrates that the proposed method can achieve a more accurate and stable division of distributed PV units.

Abstract Electric power information has garnered particular interest in conventional electrical power systems because it plays a crucial role in the electric power industry. Additionally, electric power communication networks ensure the overall power system's reliability and safety. The concepts and techniques used in digital twin (DT)‐based online tools for electric power communication networks are introduced in this paper. Moreover, online DT tools are proposed as daily learning and training resources for both new staff and communication commissioners, which can be used for the internet and the company intranets. Users can control DT and physical equipment simultaneously, and device status can be seen in real time. The design, modelling, control principles, data collection, and visual display of the DT tools are all covered in this study. To validate the applicability of the proposed framework, a case study for optical fibre damage and the recovery process in a typical communication interruption malfunction is investigated. The research presented in this paper has the potential to provide useful tools and new paradigms for designing online DT training and education systems.

Truck hoisting detection constitutes a key focus in port security, for which no optimal resolution has been identified. To address the issues of high costs, susceptibility to weather conditions, and low accuracy in conventional methods for truck hoisting detection, a non-intrusive detection approach is proposed in this paper. The proposed approach utilizes a mathematical model and an extreme gradient boosting (XGBoost) model. Electrical signals, including voltage and current, collected by Hall sensors are processed by the mathematical model, which augments their physical information. Subsequently, the dataset filtered by the mathematical model is used to train the XGBoost model, enabling the XGBoost model to effectively identify abnormal hoists. Improvements were observed in the performance of the XGBoost model as utilized in this paper. Finally, experiments were conducted at several stations. The overall false positive rate did not exceed 0.7% and no false negatives occurred in the experiments. The experimental results demonstrated the excellent performance of the proposed approach, which can reduce the costs and improve the accuracy of detection in container hoisting.

In stationary power generation units such as distributed remote site power systems and ship power systems, diesel engine generator systems are essential for supplying electricity. This paper proposes a digital twin diesel generator system for teaching and research purposes. A five-layer resilient architecture, including a web interface layer, server cluster layer, real-time data layer, controller layer, and equipment layer, is proposed in this paper. Based on the resilient architecture, users are able to build, implement and monitor the digital twin through web interfaces. Apart from MATLAB/Simulink, a modeling tool called M2PLink is developed to allow users to create mathematical models using a block diagram editor similar to Simulink. Various basic blocks for control systems are provided for users to form sophisticated models. These models are converted into executable codes which are downloaded to the simulator in the controller layer, where the real-time simulations are implemented. A web-based real-time monitoring interface with many widgets such as charts, oscilloscopes, and three-dimensional (3D) animation is also provided for users to customize their monitoring interface. All the signals can be traced and all the parameters can be tuned in the monitoring interface. The users are able to interact with the digital twin just like they do with the real system. The proposed system can not only be used for research such as digital twin-assisted real-time online monitoring but also for educational purposes, which is not only cost-effective but can also ensure the safety of the user as well as the equipment.

Abstract Online experimental systems that include remote and virtual experiments based on the Internet has become a new form of experiment in engineering education. This paper proposes a virtual experiment for the complex process control system. It is based on the networked control system laboratory (NCSLab), which provides a reliable framework for virtual thermal experiment. Taking the combustion system of 1000 MW ultra‐supercritical coal‐fired once‐through boiler‐turbine units as an example, the framework and the implementation process of the online system are given in this paper. A new presentation form for complex processes control experiment is provided, which could be a solution for simulating physical experimental equipment in virtual environments. The potential danger in practical experiments could be avoided. Additionally, the real‐time operation for complex control systems could be presented in a 3D scene. Meanwhile, the flexibility and efficiency could be increased in engineering experimental education. Moreover, using the experiment evaluation method, the references and feedback for teaching and assessment are provided in this paper.

Universality is crucial for systems to provide services to users with different backgrounds. A good language system can remove language barriers to help to improve system universality. To improve user experience and provide new features to users, the Networked Control System Laboratory (NCSLab) has been redeveloped based on React. To achieve toward an international platform, this paper introduces a web-based multi-language system for remote and virtual laboratories based on React. The language system is implemented based on an open source tool named react-intl-universal. The architecture and modular design concept of the language system are investigated and the design and implementation are explored in detail from the perspective of the front-end and back-end separation scheme. The proposed language system has been integrated into the new React-based NCSLab system, which is scalable and can improve universality to serve not only domestic users in China, but also international users from all over the world.

To achieve load disaggregation in non-intrusive load monitoring (NILM) system, a load event matching method based on graph theory is proposed, which is built on the improved Kuhn-Munkras algorithm. In this method, firstly, an adaptive fitting method using time window is applied to detect the load whether it is switched on and/or off. Particularly, to avoid the fluctuation of load signatures, the kernel density estimation is then built by a number of the independent features of the load switching on, including the active and reactive power signatures. The distribution of load signatures is thereby obtained, allowing the load event to be classified by its features. The load matching, which is based on the improved KM algorithm, is then utilized to resolve the matrix formed by the matching probability of the load event. Similarly, load identification can also be realized by matching the features of events with the signatures in the database. Finally, the experimental results using datasets of our lab and REDD demonstrate that the proposed method can obtain the desirable result for load event matching, and promote the performance in load identification.

Online laboratories are offering new experimental potential for research and education purposes. This paper investigates the design and implementation of a web-based hybrid laboratory framework for research and education. Based on the previous work of the Networked Control System Laboratory (NCSLab), a hybrid laboratory with a highly modular design providing plug-in free online experiments is discussed. The proposed modular design of the NCSLab is provided in four aspects as hardware, software, control algorithms, and deployment, which covers all of the phases that compose an online experimental platform. The experiments that are integrated into the NCSLab for research and education are also explored in detail. To verify the effectiveness of the proposed modular design, a virtual wiring fan speed control system and a physical wireless power transfer system are deployed as examples to illustrate the virtual and remote experiments, respectively. The modular hybrid laboratory has been applied to research and engineering education at Wuhan University, and the corresponding pedagogical evaluation verified the effectiveness of the NCSLab.

Optimizing the natural frequency is crucial for dc-to-load efficient wireless power transfer (WPT) applications on high voltage (HV) power transmission lines. However, a comprehensive optimization approach with the coupling factor and the losses on power electronics both taken into consideration is still in absence. By modeling losses dissipated on various parts, including the class-D inverter, the rectifier, and the resonant loops, a numerical approach is proposed in this paper to evaluate the optimal natural frequency for maximum dc-to-end efficiency. As the system efficiency is also affected by the operating frequency, which is resilient for practical operation, practical operating strategies are applied to determine the working parameters. Furthermore, considering that the HV WPT systems may work with various coupling factors, optimal natural frequencies for various coupling factors are analyzed and compared. Several groups of experiments are conducted to verify the effectiveness of the proposed numerical approach. Experimental results show that the approach can effectively predict the optimal natural frequency. When compared with the cases where the natural frequency is 100 or 600 kHz, an efficiency enhancement of about 20% can be achieved using the optimized natural frequency. When compared with the cases where the natural frequency is optimal for maximum Q value, an efficiency of 9% can still be achieved for loosely coupled occasions.

ToTo prevent the degradation of battery life and reduce switching loss in inductive power transfer (IPT) systems for electric vehicles (EVs), it is vital to realize constant current/voltage (CC/CV) charging and zero-voltage-switching (ZVS) operation. However, due to the existence of couplings between the charging and ZVS operating control loops, the controllers are neither optimal nor robust. In this paper, a model-based decoupled control method is proposed to improve the performance of the charging and ZVS operating controllers. Since the operating point of the CC and CV modes are different, two dynamic models for the corresponding charging modes are built and linearized. Besides, the couplings between the charging and ZVS operating control loops are analyzed, and in turn, decoupled by designing compensators. To optimize the system performance, we chose PI controllers, and their parameters are obtained by calculating the settling time and overshoot of the close-loop dominant poles according to the control performance requirements. In the experiment, a 500-W series-series IPT system prototype is built and tested to verify the improvement of the control performance. Compared with the coupled control method and the traditional closed-loop control feedback method, the recorded response curves and transient waveforms demonstrate that the proposed decoupled control method brings a better performance to the system.

With the large-scale penetration of demand-side distributed generations (DG), the conventional low-voltage distribution network is becoming increasingly complex in the terms of synchronization stability and control. This paper presents the evolution process of energy transfer topology in the mathematical model, analyzes the network model and the synchronization stability of large-scale DGs in a low-voltage active distribution network. Topological mathematical models are established as the object to research incorporate DGs into three networks (i.e., star-shaped, circle-shaped, and tree-shaped networks) without changing the network architecture. Based on the Kuramoto oscillator form from a complex network theory perspective, the large-scale DGs with the frequency-droop controllers in the network can be transformed into a generalized Kuramoto model. Accordingly, by comparing the above proposed models with the standard networks (i.e., fully coupled network, NW small world network, and BA scale-free network), we discuss the synchronization stability for different topology structures of an active distributed network. The effectiveness and the superiority of the proposed topology structure are further demonstrated through numerical simulation methods, including frequency stability, phase stability, order parameters, and spectrum analysis. Furthermore, the improvement of Iceland 189-node grid is employed to prove the better stability with the star-shaped connection.

Online laboratories have been widely used in education, research, and industrial applications. For online laboratories, various architectures have been constructed to provide good user experience and powerful capabilities for online experimentation, in which the controller is a crucial part to connect the server with a controlled test rig. Regarding the physical nature of the controllers and test rigs used in online laboratories, a specific control process can be called a simulation, hardware-in-the-loop, rapid control prototyping, or physical control. This article presents an overview of the most commonly used controllers in current online laboratories, focusing on the functionalities, use purposes, and types of different controllers, as well as their role in online laboratories for teaching and learning. In particular, the low-cost PC controller used in the Networked Control System Laboratory, which provides both remote and virtual experiments, is introduced. The limitations and potential development directions of online laboratories are identified.

This paper introduces a networked closed-loop model for smart on-site maintenance of substation equipment using mobile networks, which is composed of a field-side Smart Operation and Maintenance (SOM) box with its related APP and a centre-side system platform for Operation and Maintenance (OM). As a bridge to connect the operation sites and data centre, the networked equipment maintenance model enables bidirectional communication among the management, maintenance teams, and diversely located equipment. This model not only realizes the formal data uploading in real-time, but also can provide the workers on site with guidance from the data centre.

Wireless power transfer (WPT) based on inductive coupling could be potentially applied in many practical applications. It has attracted a lot of research interests in the last few years. In this paper, the modelling, design, and implementation of a 2-coil WPT system are represented. The prototype system can be implemented using conventional power electronic devices such as MOSFETs with very low costs as it works in relative low frequency range (less than 1 MHz). In order to find out about the optimal working area for the WPT system, the circuit model based on the practical parameters from the prototype is built. The relationships between the exciting frequency, coupling, and output power are analyzed based on the circuit and magnetic principles. Apart from the theoretic study, the detailed implementation of the WPT prototype including the coil design, digital frequency generation, and high frequency power electronics is also introduced in this paper. Experiments are conducted to verify the effectiveness of the circuit analysis. By carefully tuning the circuit parameters, the prototype is able to deliver 20 W power through 2.2 meter distance with 20–30% efficiency.