Search Results (354)

With the support of the dual-carbon strategy and related policies, China’s offshore wind power has experienced rapid development. However, constrained by the inherent intermittency and volatility of wind power, large-scale expansion poses significant challenges to grid integration and exacerbates government fiscal burdens. To address these critical issues, this paper proposes a multi-market coupling trading model integrating energy storage-equipped offshore wind power into electricity–carbon–green certificate markets for large-scale grid networks. Firstly, a day-ahead electricity market optimization model that incorporates energy storage is established to maximize power revenue by coordinating offshore wind power generation, thermal power dispatch, and energy storage charging/discharging strategies. Subsequently, carbon market and green certificate market optimization models are developed to quantify Chinese Certified Emission Reduction (CCER) volume, carbon quotas, carbon emissions, market revenues, green certificate quantities, pricing mechanisms, and associated economic benefits. To validate the model’s effectiveness, a gradient ascent-optimized game-theoretic model and a double auction mechanism are introduced as benchmark comparisons. The simulation results demonstrate that the proposed model increases market revenues by 17.13% and 36.18%, respectively, compared to the two benchmark models. It not only improves wind power penetration and comprehensive profitability but also effectively alleviates government subsidy pressures through coordinated carbon–green certificate trading mechanisms. Full article

Matrix converters (MC) offer a compact, bidirectional solution for power conversion; however, achieving precise reactive power control at the input terminals remains challenging under varying operating conditions. This paper presents an enhanced Singular Value Decomposition modulation technique (e-SVD) as a solution tailored to optimize reactive power management on the MC input side, enabling both active and reactive power control regardless of the power factor. The proposed method achieves input reactive power control based on a reactive power gain, a quantity derived from the apparent output power and defined by a mathematical expression involving electrical parameters and control variables. Experimental tests carried out on a low-power MC prototype to validate the proposal show that the measured reactive power gain closely aligns with theoretical predictions from the mathematical expressions. Overall, the proposed e-SVD modulation technique lays the foundation for more reliable reactive power regulation in applications such as microgrids and distributed generation systems, contributing to the development of smarter and more resilient energy infrastructures. Full article

Virtual power plants (VPPs) enable the efficient participation of distributed renewable energy resources in electricity markets by aggregating them. However, the profitability of VPPs is challenged by market volatility and regulatory constraints, such as price caps and imbalance penalties. This study examines the joint impact of varying price cap levels and imbalance penalty structures on the bidding strategies and revenues of VPPs. A stochastic optimization model was developed, where a three-stage scenario tree was utilized to capture the uncertainty in electricity prices and renewable generation output. Simulations were performed under various market conditions using real-world price and generation data from the Korean electricity market. The analysis reveals that higher price cap coefficients lead to greater revenue and more segmented bidding strategies, especially under asymmetric penalty structures. Segment-wise analysis of bid price–quantity pairs shows that over-bidding is preferred under upward-only penalty schemes, while under-bidding is preferred under downward-only ones. Notably, revenue improvement tapers off beyond a price cap coefficient of 0.8, which indicates that there exists an optimal threshold for regulatory design. The findings of this study suggest the need for coordination between price caps and imbalance penalties to maintain market efficiency while supporting renewable energy integration. The proposed framework also offers practical insights for market operators and policymakers seeking to balance profitability, adaptability, and stability in VPP-integrated electricity markets. Full article

With the increasing penetration of renewables, the importance of electrical energy storage (EES) for power supply stabilization is growing. The intermittency of renewable energy sources remains the main issue limiting their rapid integration; however, the development of high-capacity batteries capable of storing large quantities of energy offers a way to address this challenge. This article presents and describes dedicated algorithms for controlling the EES system to enable the provision of individual system services. Five services are planned for implementation: RES power stabilization; voltage regulation using active and reactive power; reactive power compensation; power stabilization of unstable loads; and power reduction on demand. The aim of this paper is to develop new, dedicated energy storage control algorithms for delivering these specific services. Additionally, the voltage regulation algorithm includes two operating modes: short-term regulation (voltage fluctuation stabilization) and long-term regulation (triggered by an operator signal). Full article

In the operation of a power distribution system, miniature circuit breakers (MCBs) are subjected to the synergistic effect of electrical and mechanical stresses in service, and their operational performance is progressively degraded, which is prone to bring significant losses to the users after failures occur. In order to accurately predict the remaining electrical life of MCBs in service, MCB mechanical characterization and dynamic simulation are carried out, and the initial closing angle of MCBs is selected as the degradation characteristic quantity, so as to deeply analyze the evolutionary characteristics of the initial closing angle in the degradation of MCBs and to construct the electrical degradation model of the one-dimensional linear Wiener process in the present study. With the help of the Monte Carlo method, we carry out the electric life simulation analysis to investigate the intrinsic correlation between the degradation of electric performance and the initial closing angle, and we implement the electric life experiment under the 63 A working condition to analyze the dynamic change in the stiffening angle of the test samples. The parameters of the electrical performance degradation model are identified through the synergistic driving of the electrical life simulation data and the experimental data, the remaining electrical life prediction is realized based on the degradation data of the same batch of products, and the maximum prediction error of the proposed method is controlled within 15%. Full article

The reliability of the electro-power equipment of electrical power transmission systems is essential in ensuring an uninterrupted power supply with the necessary voltage and frequency stability. This is especially important when performing lengthy procedures requiring the serviceability of the electrical equipment used, such as those related to foundries and metallurgical processes, or with the processes of testing complex means for the remote control of electromagnetic radiation within the implementation of the Sustainable development of the Competence Center “Quantum Communication, Intelligent Security Systems and Risk Management” (QUASAR) Project, funded with the participation of the EU under the “Research, Innovation and Digitalization for Smart Transformation” Program 2021.2027 according to procedure BG16RFPR002-1.014. One of the main issues in this case is related to the availability of information regarding the technical condition of the deployed or reserve energy resources. In this connection, this study proposes methods for determining the quantity of operational equipment that is either in use or in storage, based on the reliability testing of a representative sample of it. Full article

The project of the flexible direct transmission of renewable energy has become an inevitable development trend for the large-scale grid connection of renewable energy. Its two-terminal weakly fed AC system is often composed of 100% power electronic equipment, which leads to an essential transformation in fault characteristics and protection requirements. At present, in research, the traditional directional elements are limited by the negative-sequence control strategy, resulting in the decline of their sensitivity and reliability. Therefore, this paper proposes a model for identifying directional elements using composite electrical quantities that is not affected by the control strategy of the two-terminal weakly fed AC system and can reliably identify the fault direction. Firstly, the adaptability of traditional directional elements under the negative-sequence current suppression strategy on both sides of the system when faults occur in the AC line was analyzed. Secondly, based on the idea of model recognition, the model relationship of fault voltage and current in the case of ground faults and non-ground faults occurring at different locations was analyzed. Finally, a fitted voltage was constructed and the Kendall correlation coefficient was introduced to achieve fault direction discrimination. Simulation results demonstrate that the proposed pilot protection scheme can operate reliably under conditions of 300 Ω transition resistance and 25 dB noise interference. Full article

Sustainability can be achieved through the widespread adoption of electrification across multiple sectors of activity, which would thereby enable increased operational efficiency and reduce the environmental impact. The attainment of this purpose relies on electrical circuits that convert electrical energy from renewable power plants into forms that are compatible with the specific requirements of the load. Failure of the aforementioned circuits, denominated as power converters, can lead to financial losses resulting from unexpected shutdowns and, in critical systems, can pose significant risks to human life. This article focuses on the topic of fault diagnosis in power converters. Some of the most vulnerable components of these converters are the capacitors used in the DC-link, whose failure evolves gradually. When the capacitor internal resistance (ESR) or the capacitor capacitance (C) exceeds a certain threshold value, it is advisable to propose a system shutdown, as soon as possible, to replace the capacitor. The solution presented in this article combines signal processing techniques (SPTs) with a machine learning (ML) algorithm to determine the optimal time for capacitor replacement. The ML algorithm employed herein was a logistic regression (LR) algorithm which classified the capacitor into one of two states: normal operation (0) or failure (1). To train and evaluate the LR model, two different datasets were created using various electrical quantities that can be measured non-invasively. The model demonstrated excellent performance, achieving an accuracy, precision, recall, and F1 score above 0.99. Full article

The dynamic behavior of large-scale systems containing diverse devices is a crucial focus for system operators, particularly in power systems where grid-connected devices generate AC electrical signals through various modulated methods. One of the main objectives of power systems is to transmit power. To this end, time-varying amplitude/frequency rotating vectors are used to describe different AC voltage and current signals, and then the active/reactive power separation mechanisms and characteristics for different signal-modulated power devices are explored. These mechanisms and characteristics are analyzed and verified through time-domain simulations. The theoretical contribution of this paper is that it thoroughly clarifies the misconception in current power theories by demonstrating that active power and reactive power naturally arise as inherent physical quantities rather than being solely mathematically defined. In terms of practicality, this paper can provide physically grounded insights for the power calculation methods and offer guidance for the design of power measurement in actual power system dynamic processes. Through the analysis presented in this study, the analysis, measurement, and control of the active/reactive components in renewable energy equipment based on the instantaneous reactive power calculation method or the traditional sinusoidal steady-state power calculation method do not need to be updated. Full article

SiC MOSFETs are widely employed in power converters due to their superior efficiency and reliability at high temperatures. For this reason, it is crucial to implement accurate thermal models capable of indirectly estimating the junction temperature and its fluctuations: both are caused by power losses in the device. In this framework, the evaluation of switching losses remains the most challenging task. To enable real-time monitoring of the junction temperature, this work presents the development of a virtual sensor specifically designed for SiC MOSFETs. The sensor relies on a num-analytical model (NAM), which employs only datasheet parameters and leverages electrical quantities—namely, bus voltage and current—available from sensors integrated into power converter systems. The proposed NAM is implemented in MATLAB using an iterative algorithm that accounts for the main physical phenomena involved in switching transitions. The computed energy losses are then used to thermally model the SiC MOSFETs within the PLECS environment, where a digital twin of an all-SiC board is created. Finally, the accuracy of the model is validated by comparing simulation results with experimental efficiency data obtained from a real half-bridge converter, with explicit consideration of measurement uncertainty. Full article

PMUs, through their ability to perform synchronized and accurate measurements of electrical quantities, enable real-time monitoring of the impact of RES on the grid. They enhance grid stability even in the presence of variable and distributed generation and help prevent blackouts and imbalances caused by sudden power fluctuations. These capabilities strongly support sustainability by facilitating an energy transition toward a low-carbon generation mix, in line with SDG 7. Despite their potential, the deployment of PMUs in distribution networks has remained limited due to high device costs, the large number of required monitoring points, and the inherently variable nature of the measured quantities. This study proposes a testing framework for evaluating the performance of a real PMU under realistic operating conditions. A test system was developed by replicating a section of a municipal distribution grid in Italy. By comparing waveforms measured by the PMU with those generated through Simulink simulations, the system’s operational effectiveness and measurement reliability were assessed. The procedure was applied under diverse scenarios, including equipment faults, connection or disconnection of large loads, and the integration of RES—all of which may affect accuracy. This work also contributes to SDG 9 by supporting innovation in distribution-level monitoring technologies. Full article

An exact solution of the collisionless time-dependent Vlasov equation is found. For the first time in a century, an analytical solution to the one-dimensional time-dependent Vlasov–Boltzmann equation has been found. It has been found that instead of the widely discussed damping, waves are subject to instability. By means of this solution, the behavior of the Langmuir waves in the nonlinear stage is considered. A symmetry method is found that allows us to establish the dependence on time of the desired quantity based on the dependence on the previous time. The analysis is restricted by the consideration of the first nonlinear approximation—keeping the second power of the electric strength. It is shown that in general the waves with finite amplitudes are not subjected to the damping. Conditions have been found under which waves can be unstable. Full article

This article presents the simulation results of synchronization of a permanent magnet synchronous generator (PMSG) dedicated for a hydroelectric plant without power converter devices. The proposed machine design allows to connect a generator to the grid in two different ways. With the first method, the machine is connected to the grid in a similar way as in the case of an electrically excited synchronous generator. The second method is a direct line-start process based on asynchronous torque—similar to asynchronous motor start. Both methods can be used alternately. The advantages of the presented design are elimination of converter devices for starting the PMSG, possibility of use in small and medium hydroelectric power plants, operation with a high efficiency and high power factor in a wide range of generated power, and smaller dimensions in comparison to the generators currently used. The described rotor design allows for the elimination of capacitor batteries for compensation of reactive power drawn by induction generators commonly used in small hydroelectric plants. In addition, due to the high efficiency of the PMSG, high power factor, and appropriately selected design, the starting current during synchronization is smaller than in the case of an induction generator, which means that the structural elements wear out more slowly, and thus, the generator’s service life is increased. In this work, it is shown that PMSG with a rotor cage should have permanent magnets with an increased temperature class in order to avoid demagnetization of the magnets during asynchronous start-up. In addition, manufacturers of such generators should provide the number of start-up cycles from cold and warm states in order to avoid shortening the service life of the machine. The main objective of the article is to present the methods of synchronizing a generator of such a design (a rotor with permanent magnets and a starting cage) and their consequences on the behavior of the machine. The presented design allows synchronization of the generator with the network in two ways. The first method enables synchronization of the generator with the power system by asynchronous start-up, i.e., obtaining a starting torque exceeding the braking torque from the magnets. The second method of synchronization is similar to the method used in electromagnetically excited generators, i.e., before connecting, the rotor is accelerated to synchronous speed by means of a water turbine, and then, the machine is connected to the grid by switching on the circuit breaker. This paper presents electromagnetic phenomena occurring in both cases of synchronization and describes the influence of magnet temperature on physical quantities. Full article

There are numerous quantities and types of electrical loads, and their electrical characteristics have similarities and differences. To adapt to the development trend of refined management and scheduling on the load side, it is necessary to explore the electricity consumption patterns of loads and classify them. However, the classification performance is affected by data redundancy, the complexity of feature selection, and the diversity of power consumption behavior. To adapt to the development trend of refined management and scheduling on the load side, it is imperative to classify loads based on their electrical characteristics. Firstly, based on a statistical analysis of load-side electricity consumption data, the monthly electricity consumption of each load throughout the year is extracted to reflect the continuous electricity consumption characteristics of each load. By calculating the annual load rate, maximum load utilization hours, and rated capacity of each load and then using a Gaussian Mixture Model (GMM) for clustering analysis, the discrete electricity consumption characteristics of each load are obtained. Then, based on the K-prototypes clustering model, a load classification method is proposed based on continuous and discrete hybrid electricity characteristics. By setting the weight between continuous and discrete electrical characteristics, the optimal number of categories can be determined through the elbow method. Finally, using 86 industrial electricity-consuming enterprises in a region of Northwest China as experimental subjects, the results demonstrate that the method proposed in this study outperforms the K-means, GMM, and Gower. Full article

Recent environmental concerns have heightened attention toward new solutions across all fields to mitigate human impact. The power system community is also deeply committed to addressing this issue, with research increasingly focused on sustainable practices. For instance, there is a growing trend in designing new buildings to be net-zero emitters, while older structures are being retrofitted for energy efficiency to achieve similar goals. To this purpose, the study aims to enhance the energy management capabilities of an educational building by implementing a smart infrastructure. Equipped with photovoltaic panels and a distributed measurement system, the building captures voltage and current data and calculates power. These electrical quantities are then forecasted through an AI-driven framework that manages the data. The paper details the AI model used, including its experimental validation. The results show that the system provides reliable forecasts of electrical parameters. The evaluation of the distributed measurement system and the collected data offers valuable insights, which support more informed actions for optimizing energy management and system performance. A key novelty of this study lies in the exploration of model generalization across measurement nodes. This approach is supported by the correlation analysis of data, which highlights the potential for accurate predictions in case of data gaps. Moreover, the ease of deployment and the practical application of the system were highlighted as key factors for scalability, allowing for potential adaptation in similar infrastructures. Full article