Search Results (223)

For the precise description of gas physical processes in high-voltage direct current (HVDC) transmission, an advanced and robust numerical framework for the simulation of transient particle densities in the course of corona discharges is developed in this work. The aim is the scalable and consistent modeling of the space charge density under realistic conditions. The core component of the framework is a discontinuous Galerkin method that ensures the conservative properties of the underlying hyperbolic problem. The space charge density at the electrode surface is imposed as a dynamic boundary condition via Lagrange multipliers. To increase the numerical stability and convergence rate, a homotopy approach is also integrated. For the experimental validation, a measurement concept was realised that uses a subtraction method to specifically remove the displacement current component in the signal and thus enables an isolated recording of the transient ion current with superimposed voltage stresses. The experimental results on a small scale agree with the numerical predictions and prove the quality of the model. On this basis, the framework is transferred to hybrid HVDC overhead line systems with a bipolar design. In the event of a fault, significant transient space charge densities can be seen there, especially when superimposed with new types of voltage waveforms. The framework thus provides a reliable contribution to insulation coordination in complex HVDC systems and enables the realistic analysis of electrohydrodynamic coupling effects on an industrial scale. Full article

Driven by the environmental benefits associated with reduced greenhouse gas emissions, oil companies have intensified research efforts into reassessing the strategies used to meet the electrical demands of offshore production platforms. Among the various alternatives available, the deployment of onshore–offshore interconnections via High-Voltage Direct Current (HVDC) transmission systems has emerged as a promising solution, offering both economic and operational advantages. In addition to reliably meeting the electrical demand of offshore facilities, this approach enables enhanced operational flexibility due to the advanced control and regulation capabilities inherent to HVDC converter stations. Based on the use of interconnection through an HVDC link, aiming to evaluate the operation of the electrical system as a whole, this study focuses on evaluating dynamic events using the PSCAD software version 5.0.2 to analyze the direct online starting of a large induction motor and the sudden loss of a local synchronous generating unit. The simulation results are then analyzed to assess the effectiveness of both Grid-Following (GFL) and Grid-Forming (GFM) control strategies for the converters, while the synchronous generators are evaluated under both voltage regulation and constant power factor control operation, with a particular focus on system stability and restoration of normal operating conditions in the sequence of events. Full article

With the widespread application of DC technology in data centers, renewable energy, electric transportation, and high-voltage direct current (HVDC) transmission, DC rectangular busbars are becoming increasingly important in power transmission systems due to their high current density and compact structure. However, space constraints make the deployment of conventional sensors challenging, highlighting the urgent need for miniaturized, non-contact current measurement technologies to meet the integration requirements of smart distribution systems. This paper proposes a field-source inversion-based contactless DC measurement method for rectangular busbars. The mathematical model of the magnetic field near the surface of the DC rectangular busbar is first established, incorporating the busbar eccentricity, rotation, and geomagnetic interference into the model framework. Subsequently, a magnetic field–current inversion model is constructed, and the DC measurement of the rectangular busbar is achieved by performing an inverse calculation. The effectiveness of the proposed method is validated by both simulation studies and physical experiments. Full article

The increasing penetration of renewable energy sources presents significant challenges for power system stability and operation. Accurately assessing renewable energy absorption capacity is essential to ensuring grid reliability while maximizing renewable integration. This paper proposes a security-constrained sequential production simulation (SPS) framework, which incorporates grid voltage and frequency support constraints to provide a more realistic evaluation of renewable energy absorption capability. Additionally, hierarchical clustering (HC) based on dynamic time warping (DTW) and min-max linkage is employed for temporal aggregation (TA), significantly reducing computational complexity while preserving key system characteristics. A case study on the IEEE 39-bus system, integrating wind and photovoltaic generation alongside high-voltage direct current (HVDC) transmission, demonstrates the effectiveness of the proposed approach. The results show that the security-constrained SPS successfully prevents overvoltage and frequency deviations by bringing additional conventional units online. The study also highlights that increasing grid demand, both locally and through HVDC export, enhances renewable energy absorption, though adequate grid support remains crucial. Full article

With the increasing penetration of renewable energy, the scale of AC/DC hybrid transmission systems continues to grow, intensifying risks such as line overloads under N-1 contingencies, short-circuit current violations, and operational stability challenges arising from multi-DC coupling. This paper explores the complex coupling characteristics between AC/DC and multi-DC systems in hybrid configurations, proposing innovative evaluation indicators for coupling properties and a comprehensive assessment scheme for multi-DC coupling degrees. To enhance system stability, coordinated planning strategies are proposed for AC/DC hybrid transmission systems with multi-infeed High-voltage direct-current (HVDC) based on the AC/DC strong–weak balance principle. Specifically, planning schemes are developed for determining the locations, capacities, and converter configurations of newly added DC lines. Furthermore, to mitigate multi-DC simultaneous commutation failure risks, we propose an AC-to-DC conversion planning scheme and a strategy for adjusting the DC system technology route based on a through comprehensive multi-DC coupling strength assessment, yielding coordinated planning strategies applicable to the AC/DC hybrid transmission systems with multi-infeed HVDC. Finally, simulation studies on the IEEE two-area four-machine system validate the feasibility of the proposed hybrid transmission grid planning strategies. The results demonstrate its effectiveness in coordinating multi-DC coupling interactions, providing critical technical support for future hybrid grid development under scenarios with high renewable energy penetration. Full article

This study conducted experiments and simulations to examine the DC corona-generated space charge characteristics and understand the performance of high-voltage direct current (HVDC) transmission lines. In experimental studies, various gradient temperatures are tested on a standard model of the potential HVDC transmission line in Southern Africa using an indoor corona cage. Initial tests on the single-line model of aluminium TERN conductors measured the DC corona inception voltages (CIVs) as the ambient temperature increased from 25 °C to 42 °C. A daylight ultraviolet corona camera (CoroCam8) has been used for measurements and visualisation; the measurements record temperatures for positive and negative direct current (DC) voltages. Experimental investigations are supplemented by simulations utilising the finite element method (FEM)-based software COMSOL Multiphysics. Following the creation of 3D models of the corona cage and potential conductor arrangement, the electric field distribution on the surfaces of the conductors was examined. The CIV observations and modelling findings determine the setups’ corona inception electric field strengths. The study effectively integrated experimental data from a corona cage with FEM models to assess DC corona properties across different air temperatures thoroughly. The inception voltage levels of corona are significantly influenced by ambient temperature and the space charge generated by corona. The outcomes of the discussion will inform the design of the proposed HVDC transmission line in Southern Africa. Full article

High-voltage direct-current (HVdc) transmission lines are gaining more attention as an integral part of modern power system networks. Monitoring the dc current is important for metering and the development of dynamic line rating control schemes. However, this has been a challenging task, and there is a need for wireless sensing methods with high accuracy and a dynamic range. Conventional methods require direct contact with the high-voltage conductors and utilize bulky and complex equipment. In this paper, an ultra-high-frequency (UHF) radio frequency identification (RFID)-based sensor is introduced for the monitoring of the dc current of an HVdc transmission line. The sensor is composed of a passive RFID tag with a custom-designed antenna, integrated with a Hall effect magnetic field device and an RF power harvesting unit. The dc current is measured by monitoring the dc magnetic field around the conductor using the Hall effect device. The internal memory of the RFID tag is encoded with the magnetic field data. The entire RFID sensor can be wirelessly powered and interrogated using a conventional RFID reader. The advantage of this approach is that the sensor does not require batteries and does not need additional maintenance during its lifetime. This is an important feature in a high-voltage environment where any maintenance requires either an outage or special equipment. In this paper, the detailed design of the RFID sensor is presented, including the antenna design and measurements for both the RFID tag and the RF harvesting section, the microcontroller interfacing design and testing, the magnetic field sensor calibration, and the RF power harvesting section. The UHF RFID-based magnetic field sensor was fabricated and tested using a laboratory experimental setup. In the experiment, a 40 mm-diameter-aluminum conductor, typically used in 500 kV HVdc transmission lines carrying a dc current of up to 1200 A, was used to conduct dc current tests for the fabricated sensor. The sensor was placed near the conductor such that the Hall effect device was close to the surface of the conductor, and readings were acquired by the RFID reader. The sensitivity of the entire RFID sensor was 30 mV/mT, with linear behavior over a magnetic flux density range from 0 mT to $4.5$ mT. Full article

Due to the highly demanding operating conditions of the Modular Multilevel Converter (MMC), as well as its inherently complex structure, electric field analysis of the MMC valve is crucial for the safe and stable operation of MMC-HVDC (MMC high voltage direct current) transmission systems. In this paper, a high-speed modeling method for an MMC valve based on data derivation is proposed. Firstly, the relationship between the MMC valve electric field calculation model parameters and the MMC-HVDC transmission system parameters was studied. Based on this, the data derivation system for the electric field calculation model parameters of all components of the MMC valve was established. A modeling parameters database based on empirical knowledge is also used in the calculation process of the data derivation system. The output model parameter matrix includes the geometric parameters, position parameters, and electrical parameters of the components. Based on the output matrix, the electric field calculation model of the converter valve can be quickly generated. Furthermore, to improve the accuracy of the calculations and reduce computation time, a discrete modeling method that combines mesh optimization was proposed. In the process of discretized electric field modeling, a mesh division influence factor based on the accuracy of electric field calculation is proposed. By adjusting the mesh division influence factor during the electric field calculation, the accuracy of the electric field calculation can be optimized rapidly. Finally, the effectiveness and practicality of the high-speed modeling method for the MMC valve are verified through comprehensive case studies conducted on the ±320 kV onshore MMC-HVDC valve. It is demonstrated that the high-speed modeling method proposed in this paper can significantly reduce the modeling time of the converter valve and greatly improve the accuracy of electric field calculation. Full article

Converter stations are pivotal in high-voltage direct current (HVDC) systems, enabling power conversion between an alternating current (AC) and a direct current (DC) while ensuring efficient and stable energy transmission. Fault detection in converter stations is crucial for maintaining their reliability and operational safety. This paper focuses on image-based detection of five common faults: metal corrosion, discoloration of desiccant in breathers, insulator breakage, hanging foreign objects, and valve cooling water leakage. Despite advancements in deep learning, existing detection methods face two major challenges: limited model generalization due to diverse and complex backgrounds in converter station environments and sparse supervision signals caused by the high cost of collecting labeled images for certain faults. To overcome these issues, we propose InvMOE, a novel fault detection algorithm with two core components: (1) invariant representation learning, which captures task-relevant features and mitigates background noise interference, and (2) multi-task training using a mixture of experts (MOE) framework to adaptively optimize feature learning across tasks and address label sparsity. Experimental results on real-world datasets demonstrate that InvMOE achieves superior generalization performance and significantly improves detection accuracy for tasks with limited samples, such as valve cooling water leakage. This work provides a robust and scalable approach for enhancing fault detection in converter stations. Full article

Transforming the existing key HVAC transmission lines into High Voltage Direct Current (HVDC) transmission systems is a new type of transmission capacity expansion scheme that has been applied in power systems in Germany, the United Kingdom and other regions. After the occurrence of AC/DC intersystem faults, the fault characteristics are complex, and the protection adaptability will be affected. At present, there is no specific protection scheme for AC/DC intersystem faults. In this paper, a protection scheme based on the same side current similarity characteristics of AC and DC transmission lines is proposed, and the Hausdorff distance algorithm is introduced to measure two sets of current waveforms under different fault scenarios. The proposed protection scheme can complete the fault identification within a few milliseconds after the fault and has good rapidity and application prospects, and the effective value of the scheme is verified on the simulation platform. Full article

The global energy landscape is witnessing a transformational shift brought about by the adoption of renewable energy technologies along with power system modernisation. Distributed generation (DG), smart grids (SGs), microgrids (MGs), and advanced energy storage systems (AESSs) are key enablers of a sustainable and resilient energy future. This review deepens the analysis of the fulminating change in power systems, detailing the growth of power systems, wind and solar integration, and next-generation high-voltage direct current (HVDC) transmission systems. Moreover, we address important aspects such as power system monitoring, protection, and control, the dynamic modelling of transmission and distribution systems, and advanced metering infrastructure (AMI) development. Emphasis is laid on the involvement of artificial intelligence (AI) techniques in optimised grid operation, voltage control, stability, and the system integration of lifetime energy resources such as islanding and hosting capacities. This paper reviews the key aspects of current advancements in grid technologies and their applications, enabling the identification of opportunities and challenges to be addressed toward achieving a modern, intelligent, and efficient power system infrastructure. It wraps up with a perspective on future research paths as well as a discussion of potential hybrid models that integrate AI and machine learning (ML) with distributed energy systems (DESs) to improve the grid’s resilience and sustainability. Full article

Due to system failures and the limited overcurrent capability of semiconductor devices, overcurrent in modular multilevel converters (MMC) is a key factor affecting the safe and stable operation of offshore wind power MMC-HVDC (modular multilevel converter high-voltage direct current) transmission systems. This paper proposes a field–circuit coupling analysis method for overcurrent research in MMC valve. The method integrates the electric field characteristics of valves with the analysis of MMC-HVDC systems. Firstly, the development process and influencing factors of overcurrent in valves in offshore wind power MMC-HVDC systems are analyzed. A field–circuit coupling model and an electric field calculation model for MMC valves are established. The electric field characteristics and stray parameters of MMC valves are analyzed synchronously and the result are incorporated into the field–circuit coupling model. The nonlinear transient parameters of surge arresters are calculated, and the results are incorporated into the field–circuit coupling model. Finally, a reasonable overcurrent suppression strategy for offshore MMC-HVDC valves is proposed based on the proposed method. The effectiveness and practicality of the field–circuit coupling overcurrent analysis method are verified through comprehensive case studies conducted on the ±500kV offshore MMC-HVDC valve overcurrent calculation and suppression. Full article

Large photovoltaic stations, wind farms and high-voltage direct current (HVDC) transmission systems are being integrated into the grid, which is causing the stability of frequency and voltage of new power systems to decline, thereby imposing high requirements on the evaluation of power grid strength in regional grids. Taking into account the indicators of stability margin of frequency and voltage, this paper builds a key technical indicator system for the system of multi-type synchronous control equipment connected to the grid, including the equivalent inertia enhancement factor, steady-state frequency deviation reduction factor, voltage stiffness and steady-state voltage deviation. Considering that the objective weighting and subjective weighting can, respectively, be achieved by the independent information entropy weighing method (IIEWM), the analytic hierarchy process method (AHPM) and the integrating principal component analysis method (PCAM), an improved layered integration weight allocation method based on IIEWM-AHPM-PCAM is proposed. Meanwhile, a multi-objective comprehensive evaluation model for power grid strength is established, and a power grid strength evaluation method is proposed to accurately evaluate the support strength of frequency and voltage of grid-connected systems including multi-type synchronous control equipment. Finally, a modified model of IEEE-39 node systems is constructed using Matlab to verify the reliability of the proposed method. The results showed that, compared to IIEWM and AHPW, a better ability to reflect the degree of data independence and volatility is possessed by the proposed method. Full article

When a line-commutated converter–high-voltage direct current (LCC-HVDC) transmission system with large-scale integration of renewable energy encounters HVDC-blocking events, the sending-end power system is prone to transient overvoltage (TOV) risks. Renewable energy units that are connected via power electronic devices are susceptible to large-scale cascading disconnections due to electrical endurance and insulation limitations when subjected to an excessively high TOV, which poses a serious threat to the safe and stable operation of the system. Therefore, the prediction of TOV at renewable energy stations (RES) under DC blocking (DCB) scenarios is crucial for developing strategies for the high-voltage ride-through of renewable energy sources and ensuring system stability. In this paper, an approximate analytical expression for the TOV at RES under DCB fault conditions is firstly derived, based on a simplified equivalent circuit of the sending-end system that includes multiple DC transmission lines and RES, which can take into consideration the multiple renewable station short-circuit ratio (MRSCR). Building on this, a knowledge-embedded enhanced deep neural network (KEDNN) approach is proposed for predicting the RES’s TOV for complex power systems. By incorporating theoretical calculation values of the TOV into the input features, the task of the deep neural network (DNN) shifts from mining relationships within large datasets to revealing the correlation patterns between theoretical calculations and real values, thereby improving the robustness of the prediction model in cases of insufficient training data and irrational feature construction. Finally, the proposed method is tested on a real-world regional power system in China, and the results validate the effectiveness of the proposed method. The approximate analytical expression for the TOV at RES and the KEDNN-based TOV prediction method proposed in this paper can provide valuable references for scholars and engineers working in the field of power system operation and control, particularly in the areas of overvoltage theoretical calculation and mitigation. Full article