Peak Value Of Voltage Research Articles

Time-Domain Aggregation of Interharmonics from Parallel Operation of Multiple Sustainable Sources and Electric Vehicles

This paper examines the random nature of interharmonics generated by power converters connected to sustainable energy sources and loads, such as wind turbines, photovoltaic (PV) panels, and electric vehicles (EVs). Current research often overlooks the stochastic behavior of interharmonics and their impact on power system reliability and resilience, leading to gaps in effective modeling and mitigation strategies. Thus, this study examines a low-voltage installation with a PV panel, an EV and a microwave operating simultaneously, providing practical insights into real-world scenarios of interharmonic related disruptions and solutions for enhancing the reliability and resilience of sustainable energy grids. By leveraging real-time measurements of interharmonics, suitable probability distribution functions (PDFs) are initialized to develop a probabilistic model using Monte Carlo simulation. This enables the derivation of a time-domain aggregation model of interharmonics from multiple sources operating together at the point of common coupling (PCC). The findings reveal that the peak values of voltage or current fluctuations at the PCC are influenced by the randomness in the number of devices connected and the frequency components originating from different sources. Through multiple case studies, the dependency of these fluctuations on stochastic parameters is systematically established. Empirical relationships are formulated to predict aggregated interharmonic values under varying scenarios, enhancing the accuracy and applicability of the model. The results demonstrate that higher interharmonic frequencies and fewer randomly connected devices significantly increase the probability of elevated aggregated peak values. These insights can serve as benchmarks for grid operators and policymakers in mitigating interharmonic related issues in modern power systems.

State switch control of magnetically suspended flywheel energy storage system in uninterrupted power supply system

The magnetically suspended flywheel energy storage system (MS-FESS) is an energy storage equipment that accomplishes the bidirectional transfer between electric energy and kinetic energy, and it is widely used as the power conversion unit in the uninterrupted power supply (UPS) system. First, the structure of the FESS-UPS system is introduced, and the working principles at different working states are described. Furthermore, the control strategy of the FESS-UPS is developed, and the switch oscillation of the FESS-UPS system between the charging and discharging states is analyzed. Then, the switch strategy using the angle compensation of the flux linkage is designed to control the FESS-UPS system among different working states, and the peak values of current and voltage at the switch moment are suppressed. Finally, the simulations and experiments are performed to validate the performances of the switch strategy used in the FESS-UPS system, and the results prove that the current/voltage peaks during the switching process are effectively mitigated, so the impact on the power converter caused by the state switch is suppressed. Therefore, the control performance of the UPS using the MS-FESS could be further improved, and the FESS-UPS could realize the fast and safe discharge/charge for the grid source and three-phase loads.

Event-Driven Spiking Learning Algorithm Using Aggregated Labels.

Traditional spiking learning algorithm aims to train neurons to spike at a specific time or on a particular frequency, which requires precise time and frequency labels in the training process. While in reality, usually only aggregated labels of sequential patterns are provided. The aggregate-label (AL) learning is proposed to discover these predictive features in distracting background streams only by aggregated spikes. It has achieved much success recently, but it is still computationally intensive and has limited use in deep networks. To address these issues, we propose an event-driven spiking aggregate learning algorithm (SALA) in this article. Specifically, to reduce the computational complexity, we improve the conventional spike-threshold-surface (STS) calculation in AL learning by analytical calculating voltage peak values in spiking neurons. Then we derive the algorithm to multilayers by event-driven strategy using aggregated spikes. We conduct comprehensive experiments on various tasks including temporal clue recognition, segmented and continuous speech recognition, and neuromorphic image classification. The experimental results demonstrate that the new STS method improves the efficiency of AL learning significantly, and the proposed algorithm outperforms the conventional spiking algorithm in various temporal clue recognition tasks.

Ensembled methodology for the comtrade analysis regarding medium voltage side in wind park

This research proposes a methodology for automated COMTRADE analysis using ensembled algorithms for fault analysis in medium voltage circuits, specifically for wind park feeders. Traditional fault detection methods face significant limitations, such as CT saturation and DC offset, underscoring the need for improved approaches. The proposed methodology integrates Random Committee, XGBoost (XGB), and Light XGB algorithms, optimized through grid search, achieving an accuracy of 99.397 %. This ensemble approach significantly reduces classification errors, false positives, and false negatives compared to single algorithm methods. This research has the analysis of 3929 events for training and 829 fault events for test, it revealed a high correlation between current and fault spectra; the methodology demonstrated superior performance in fault location analysis, with terminal faults showing the most severe transient recovery voltage (TRV) peak values, while kilometer faults exhibited higher transient recovery restoration voltage growth rates. The fault location analysis was conducted by comparing simulation-derived overvoltage with standard TRV graphs, aligned with IEC 62271-100 standards. Circuit breakers exhibited higher TRV tolerance with lower fault currents. Terminal faults, particularly symmetrical three-phase faults, were identified as the most severe, typically occurring at peak TRV values. Its findings reduced classification errors, from 41 to 5 events, and decreased the false negative rate from 1.81 % to 0.24 % compared to Random Forest. Validation with virtual relays showed a reduction in RCE from 5.3 % to 0.63 %.

Microgrid F36ault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling

The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current loops, imbalances, and potential short-circuit faults. To address these challenges, this study proposes a new approach to accurately locate and identify faults based on MG lines. Initially, characteristic indices such as fault voltage, voltage fundamentals at each MG measurement point, and extracted features like peak voltage values in specific frequency bands, phase-to-phase voltage differences, and the sixth harmonic components are utilized as model inputs. Subsequently, these features are classified using the Lightweight Gradient Boosting Machine (LightGBM), complemented by the bagging (Bootstrap Aggregating) ensemble learning algorithm to consolidate multiple strong LightGBM classifiers in parallel. The output classification results of the integrated model are then fed into a neural network (NN) for further training and learning for fault-type identification and localization. In addition, a Shapley value analysis is introduced to quantify the contribution of each feature and visualize the fault diagnosis decision-making process. A comparative analysis with existing methodologies demonstrates that the LightGBM-NN model not only improves fault detection accuracy but also exhibits greater resilience against noise interference. The introduction of the bagging method, by training multiple base models on the initial classification subset of LightGBM and aggregating their prediction results, can reduce the model variance and prevent overfitting, thus improving the stability and accuracy of fault detection in the combined model and making the interpretation of the Shapley value more stable and reliable. The introduction of the Shapley value analysis helps to quantify the contribution of each feature to improve the transparency and understanding of the combined model’s troubleshooting decision-making process, reduces the model’s subsequent collection of data from different line operations, further optimizes the collection of line feature samples, and ensures the model’s effectiveness and adaptability.

Investigation of the Influence of Machining Parameters and Surface Roughness on the Wettability of the Al6082 Surfaces Produced with WEDM.

Electrical Discharge Machining (EDM) is a non-conventional machining technique, capable of processing any kind of conductive material. Recently, it has been successfully utilized for producing hydrophobic characteristics in inherently hydrophilic metallic materials. In this work, Wire Electrical Discharge Machining (WEDM) was utilized for producing hydrophobic characteristics on the surface of the aluminum alloy 6082, and various parameters that can affect wettability were investigated. Adopting an orthogonal Taguchi approach, the effects of the process parameter values of peak current, pulse-on time, and gap voltage on the contact angles of the machined surfaces were investigated. After machining, all samples were observed to have obtained hydrophobic properties, reaching contact angles up to 132°. The peak current was identified as the most influential parameter regarding the contact angle, while the gap voltage was the less influential parameter. A contact angle variation of 30° was observed throughout different combinations of machining parameters. Each combination of the machining parameters resulted in a distinct surface morphology. The samples with moderate roughness values (3.4 μm > Sa > 5.7 μm) were found to be more hydrophobic than the samples with high or low values, where the contact angle was measured under 115°. In addition, the finite element modeling of the experimental setup, with parametric surfaces of uniform random and Perlin noise types of roughness, was implemented. Time dependent simulations coupling phase field and laminar flow for the modelingof the wetting of surfaces with different surface roughness characteristics showed that an increase in the Sa roughness and total wetted area can lead to an increase in the contact angle. The combination of experimental and computational results suggests that the complexity of the wettability outcomes of aluminum alloy surfaces processed with WEDM lies in the interplay between variations of the surface chemical composition, roughness, micro/nano morphology, and the surface capability of forming a composite air/water interface.

Development of a method for measuring pulse currents of large magnitude

The paper presents the results of a study on the search for correct methods for measuring a high-value current pulse, which will be used to conduct research on the electroplastic effect. The electroplastic effect is the effect of electric current pulses on the plastic flow of metals. Electroplastic metal forming technology is a relatively new metal forming process that is energy efficient, environmentally friendly and versatile. In particular, it can be used to process metals or alloys that are difficult to process using conventional manufacturing processes. For the experimental study of the electroplastic effect, it became necessary to measure pulse currents of large magnitude, not only in amplitude, but also in the shape of the pulse. The pulsed current causes the formation of an alternating electromagnetic field near the conductors, so it can be measured with a Rogovsky current transformer. The results of the work present a schematic electrical diagram and a photograph with the appearance of an experimental installation for the study of the electroplastic effect. The results of measurements of the current value, the voltage drop on the sample and the dependence of the peak voltage values on the sample on the peak current value are shown. After making calculations and renormalising the data for the voltage drop on the sample according to the peak value of the current obtained on the transformer, the authors obtained the desired current values. The error of this method is estimated by calculating the total capacitance of capacitors, which does not exceed 2%.

An improved state‐space average model of the ultra‐high voltage inverter based on wavelet decomposition and reconstruction

SummaryUltra‐high voltage inverters are widely used as grid‐connected devices in new energy grids, and the state‐space average model is the most practical modeling method for the inverter. However, the accuracy of this modeling method is significantly reduced because it ignores the high‐frequency switching process, which contains overshoot voltage and other factors that affect system stability. Moreover, the amplitude of the overshoot voltage in the ultra‐high voltage inverter will be huge, which may lead to the damage to switching devices, circuit overheating, and even the collapse of the system. Therefore, the wavelet decomposition and reconstruction methods are used in this paper to extract the transient characteristics of the inverter and integrate them into the state‐space average model. Compared with the traditional state‐space average model, the improved model method can obtain a more accurate overshoot voltage peak value with the same simulation step size. Then, it can provide a more precise reference for the withstand voltage in the device selection of a high voltage level system. The single‐phase full‐bridge inverter is taken as an example to illustrate the construction process based on the wavelet decomposition and reconstruction method. Finally, the simulation waveform is verified to be in good agreement with the experiment.

Investigation of laser-induced single event effect on SiGe BiCMOS low noise amplifiers

With the further development of the complementary metal-oxide-semiconductor (CMOS) technology and the silicon-germanium (SiGe) epitaxy technology, SiGe bipolar CMOS (BiCMOS) low noise amplifiers (LNAs) are widely used in the first level of radio frequency (RF) transceiver system in space. The core part of SiGe BiCMOS LNA is SiGe heterojunction bipolar transistor (SiGe HBT) which naturally possesses excellent temperature characteristic and favorable build-in total ionizing dose and displacement damage resistance without any radiation hardening. However, the single event effect caused by the transient charge collection is the bottleneck problem, restricting its application in space. In this work, laser microbeam experiments were carried out on a SiGe BiCMOS LNA in which the sensitive region of single event effect was located. The experimental results indicate that the transient charge collection of SiGe HBT is the main reason of the single event effect of SiGe BiCMOS LNA. TCAD simulations show that the ionization track caused by ion incident in CMOS region will cross the deep trench isolation (DTI) structure, generate electron-hole pairs in SiGe HBT region and cause transient charge collection. The circuit simulations by ADS show that the peak value of the transient voltage will drop sharply when the SEE pulse transient voltage crosses the capacitor between the first stage and the second stage, which indicates that the capacitor plays an important role in transmitting the transient pulses caused by single event effect. The experimental and simulation results in this work provide technical support for radiation hardening by design (RHBD) of the single event effect of SiGe BiCMOS LNA.

Cadmium and COD Removal from Municipal Wastewater Using Chlorella sp. Biomass in Microbial Fuel Cells

The increasing generation of wastewater with high levels of pollutants has become a serious environmental challenge. In this context, sustainable technologies are required to treat wastewater efficiently. Therefore, it was proposed to evaluate the effect of the biomass of Chlorella sp. on the removal of cadmium and chemical oxygen demand (COD) from municipal wastewater in the district of Urpay, Pataz, La Libertad, Peru, and the generation of electric power through single-chamber microbial fuel cells (MFC). An experimental design was applied, where nine treatments were carried out evaluating three doses of Chlorella sp. (10%, 20% and 30%) at pH values of 6.5, 7.0, and 7.5 of the residual water. Managing to generate peak current and voltage values of 4.61 mA and 1118.5 mV in the MFC at a pH of 7.5 with a dose of 30% of Chlorella sp., this same MFC managed to decrease concentrations of cadmium and COD by 97.5 and 15% in 25 and 15 days, respectively. This investigation demonstrated the importance of Chlorella sp. for the reduction in these two parameters, managing to provide a new method for the elimination of these pollutants in wastewater.

A Model Predictive Control Scheme for Flying Capacitors and Neutral Point Voltages Control in Nested Piloted Neutral Point Clamped Inverter

Five-level nested piloted neutral point clamped (5L-NPNPC) inverter is a new version of nested neutral point clamped multilevel topologies. In 5L-NPNPC, voltage fluctuations in the flying capacitors (FCs) and neutral point (NP) increase as the output frequency decrease, which is not desirable for the safe operation of the inverter. In this paper, a new model predictive control-based solution is proposed to tackle this problem. First, feasible combinations of space voltage vectors are determined through which the reference voltage of the inverter is synthesized. Then, a two-step optimization process is proposed to select the optimal switching states. The voltages of FCs and NP are the control objects in the first and second optimization steps, respectively. The proposed control scheme mitigates FCs and NP voltage fluctuations in the entire frequency range while keeping the switching frequency fixed. Also, the peak value of common-mode voltage (CMV) is limited to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V_dc</i> /6. Furthermore, the proposed control scheme divides the optimization process into two steps, leading to a significant reduction in the computational burden of the processor. The mentioned achievements are important in medium-voltage (MV) motor drive applications. The simulation results and scaled-down experiments are provided to support the above claims.

Impact of temperature on dynamic characteristics of 4H-silicon carbide drift step recovery diodes

Silicon carbide (SiC) has advantages in high-temperature applications due to its high thermal conductivity and intrinsic temperature. However, the temperature also affects its physical properties thus the electrical characteristics of SiC-based devices. In this paper, the impact of temperature on the dynamic characteristics of 4H-SiC drift step recovery diode (DSRD) is studied. Both the pulse experiments and the two-dimensional numerical simulations are conducted at variable input voltage (Vin). The results show that both the peak value (Vpeak) of the output pulse voltage and the rising rate (dV/dt) of the pulse front decrease with the increased temperature. As the temperature rises from 25 °C to 125 °C, the Vpeak decreases from 1224 V to 820 V at Vin = 120 V, with a decrease ratio of 33 %. The dV/dt decreases from 214 V/ns to 92 V/ns at Vin = 100 V, with a decrease ratio of 57 %. The main reason for this phenomenon is that the increase in temperature leads to a significant decrease in carrier mobility. This work is of certain reference significance for the application of 4H-SiC DSRD in high-temperature situations.

A method for tracing impulse voltage peak value using weighted frequency components

This paper studies a method for synthesizing impulse voltage peak error based on frequency energy weight. The research designed three capacitive voltage dividers with a voltage rating of 1 kV, 10 kV, and 200 kV, respectively, and measured their response characteristics using the step wave response test. The scale factor and linearity of the 1 kV capacitor divider were measured at different frequencies and impulse voltages to verify the equivalence of voltage coefficients under power frequency and impulse. Using boundary conditions obtained from AC voltage standard sources and impulse voltage standard generators, the equivalence of 200 kV power frequency voltage coefficient and impulse voltage coefficient was derived.

Activated Carbon Electrodes for Bioenergy Production in Microbial Fuel Cells Using Synthetic Wastewater as Substrate

The growing global energy demand drives the need to develop new clean energy technologies. In this context, microbial fuel cells (MFC) are one of the emerging technologies with great potential for eco-friendly energy generation; however, the correct choice of electrode material is a significant limitation in the optimal configuration of MFCs. Therefore, this research evaluated the efficiency of activated carbon (AC) anode electrodes for bioenergy production in MFC using synthetic wastewater as a substrate. Peak values of voltage (1120 ± 0.050 mV), current (4.64 ± 0.040 mA), power density (208.14 ± 17.15 mW/cm2), and current density (5.03 A/cm2) were generated, and the Rint obtained was 214.52 ± 5.22 Ω. The substrate was operated at pH values from 5.31 to 7.66, maximum ORP values (858 mV) were reached, and turbidity was reduced to 25.11 NTU. The SEM-EDS (scanning electron microscopy–energy-dispersive X-ray spectroscopy) analyses allowed us to observe the morphology and composition of the AC electrodes, revealing a predominance of O, C, Si, Al, Fe, K, and Ca. It is concluded that the AC electrodes have the potential to produce bioenergy at a laboratory by means of MFC.

Assessment of Energy Conversion in Passive Components of Single-Phase Photovoltaic Systems Interconnected to the Grid

This paper presents a mathematical analysis of how energy return in grid-connected single-phase photovoltaic systems affects the sizing of passive components. Energy return affects the size of the link capacitor, making it larger than reported in the literature. One of the main points of this article is that an inverter connected to the grid using a DC–DC converter with an appropriate link capacitor is analyzed. The energy return is caused by the value (in Henry units) of the L-filter, which is also analyzed in this paper. The analysis shows that there is a link between the value of the L-filter and the voltage of the DC bus. The analysis assumes two conditions: (1) the DC bus voltage is always higher than the peak value of the grid sinusoidal voltage, and (2) there is a unity power factor at the connection point between the grid and the L-filter. To operate in an open loop, a compensation phase angle is calculated and introduced in the single-phase inverter modulation; this phase angle compensates the phase shift caused by the L-filter, avoiding the use of a phase-locked-loop (PLL) control system. The L-filter ripple current is evaluated by Fourier analysis, and the DC bus ripple voltage is evaluated by considering the energy returned to the link capacitor. The results of the analyses are compared with existing methods reported in the literature. The results also show that, to minimize the value of the L-filter, the DC voltage must be almost equal to the maximum voltage of the grid. Equations to assess the value of the DC-link capacitor and the L-filter in function of their ripples are developed. The results were verified with simulations in Simulink and experimentally.

Preparation and Laser-Induced Thermoelectric Voltage Effect of Bi2Sr2Co2Oy Thin Films Grown on Al2O3 (0001) Substrate.

Bi2Sr2Co2Oy thin films were grown on 10° vicinal-cut Al2O3 (0001) single crystalline substrates by pulsed laser-deposition techniques with in situ annealing, post-annealing and non-annealing process, respectively. The pure phase Bi2Sr2Co2Oy thin film was obtained with a non-annealing process. The result of X-ray diffraction showed that Bi2Sr2Co2Oy thin film was obviously c-axis preferred orientation. The laser-induced thermoelectric voltage signals were detected in Bi2Sr2Co2Oy thin films, which originated from the anisotropy of the Seebeck coefficient. The maximum peak value of laser-induced thermoelectric voltage was strong and could reach as large as 0.44 V and the response time was 1.07 μs when the deposition time was 6 min. Furthermore, the peak voltage enhanced linearly with the single-pulse laser energy. These characteristics demonstrate that Bi2Sr2Co2Oy thin film is also an excellent choice for laser energy/power detectors.

Energy harvesting and dynamic response of SMA nano conical panels with nanocomposite piezoelectric patch under moving load

Nowadays, the application of advanced and intelligent materials such as piezoelectric, shape memory alloys (SMA), and multi-phase materials, are highly demanded, especially in self-powered energy structures. Therefore, to obtain maximum efficiency, it is crucial to study and analysis the mechanical behavior of the energy production rate of the employed materials. This research theoretically evaluated the impacts of moving load and the use of a piezoelectric patch on the level of energy harvesting and dynamic behavior of a Nano Conical Panel (NCP) made from SMA located on a frictional substrate using the First-order Shear Deformation Theory (FSDT). Based on mixture rule, boron nitride nanotubes (BNNTs) with smart properties are used to reinforce the piezoelectric patch. A two-phase nonlocal method was adopted to take nano-scale effects into account. Mechanical behaviors such as friction and torsional viscoelastic were considered for the foundation layer. To reproduce the pseudo-elastic characteristics of SMA, the Hernandez-Lagoudas model was employed. In addition to these, Integral Quadrature (IQ), Differential Quadrature (DQ), and Newmark methods were coupled together to solve the equations regarding the output voltage, electric power and dynamic deflection. The computational outcomes showed that by applying a positive voltage to a piezoelectric patch, the maximum strain, as well as the energy harvesting capacity of NCP, were increased. Placing the NCP on a frictional viscoelastic-torsional layer led to deteriorated peak values of dimensionless dynamic displacement and dimensionless voltage by about 50.3% and 44.5%, respectively, compared with those of the system without the medium. At load resistance of 400 nano ohm, increasing the moving load velocity to 6.5 nm/ns, piezoelectric patch length to NCP length ratio up to 0.5, and applying CFCF boundary conditions led to enhancement of maximum output power by 30%, 88.3%, and 377%, respectively. Also, increasing the weight fraction of Boron Nitride Nanotubes (BNNT) up to 0.4% in the piezoelectric layer was found to be a suitable strategy to simultaneously decrease the dimensionless dynamic displacement and enhance dimensionless voltage by 23.4% and 21%, respectively.

A Comparative Study of Static VAR Systems for ImprovingVoltage Stability in Expansion of Mining Projects with Gearless Motor Drives

In the next decade, the demand for copper is expected to grow by 25%, posing a challenge for mining facilities to increase their production by opening new mines or upgrading existing ones. To optimize the electrical infrastructure of mining facilities, the integration of flexible AC transmission systems (FACTSs) can be instrumental in mitigating voltage stability issues that may arise during the installation of new gearless motor drives (GMDs). The purpose of this paper is to conduct a comparative analysis of the dynamic performance of static VAR systems (SVSs) as a means of enhancing voltage stability in mining expansion projects, particularly in the context of the integration of new GMDs into the system. This paper presents a case study of an existing three crushing-line mine configuration that has been upgraded with two new GMD systems. The primary contribution of this research is a comprehensive methodology designed to enhance the stability of a mining system through the integration of an SVS, which includes the sizing of the SVS system, an analysis of costs, as well as a determination of the required installation surface and optimal placement of the SVS within the system. The simulation results conclusively demonstrate the effectiveness of the SVS systems in reducing the voltage drop by 2% upon activation of new GMDs, as well as mitigating the adverse impact of transient disturbances on the system. Specifically, the first oscillation voltage peak value is improved by 3.5%, following a three-phase short circuit of 1 second duration, while overvoltage is reduced by 1% in response to sudden load changes. When compared with the system without an installed SVS, these findings highlight the significant advantages and benefits of integrating SVSs into mining operations.

Bioelectricity generation through Microbial Fuel Cells using Serratia fonticola bacteria and Rhodotorula glutinis yeast

Nowadays, there is great interest in microbial fuel cells because of the different substrates that can be used in them for electric energy generation. In order to find an alternative and contribute with eco-friendly technologies, this research used the Serratia fonticola bacteria and Rhotula glutinis yeast as a fuel source through laboratory scale microbial fuel cells. A single chamber microbial fuel cell with air cathode was fabricated with a copper foil and a graphite plate as anode and cathode electrode respectively. For the characterization of the cells, physicochemical parameters such as voltage, electric current, pH and electrical conductivity were measured for 30 days and at room temperature (18 ± 2.2 °C). It was possible to generate peak voltage and current values of 0.53 ± 0.01 V and 0.55 ± 0.02 V and current values of 1.76 ± 0.16 mA and 1.52 ± 0.02 mA, for MFCs with bacteria and yeast respectively. In addition, acidic operating pH was observed, and its conductivity peak values around 242 mS/cm. Finally, this work demonstrates the great potential that microorganisms have for the generation of electric current, giving a new and promising way to generate electricity

Effect of Space Charge on Stationary and Transient Electric Field Distribution of HVDC Cable Joint

The conversion of AC XLPE cable lines into direct-current (DC) operation has been proven to be an effective means to improve the transmission capacity of the system. Prefabricated joints are the weakest points of a cable line because of the complex structures, and composite interfaces contained. Therefore, it is of great theoretical and engineering significance to study the field strength distribution of XLPE AC cable prefabricated joints under DC voltage, effectively evaluate their DC tolerance characteristics, and provide a basis for the construction and transformation of XLPE cable DC distribution network system. This paper takes the silicone rubber (SIR), and ethylene-propylene-diene monomer (EPDM) prefabricated joints of 10kV XLPE cables as an example, the cable joint temperature field, and electric field coupling simulation model is established by the finite element analysis software COMSOL Multiphysics. The steady and transient electric field simulation of the joints under different DC voltages and load conditions are carried out considering the influence of space charge. The results show that with the increase of applied voltages and load level, the space charge injection increases, and the maximum steady state field strength in the joint is concentrated at the root of the stress cone, showing an increasing trend. Compared with the SIR joint, the field strength in the EPDM joint is higher. The capacitive component of the field strength in the joint is proportional to the peak value of the impulse voltage under the DC superimposed impulse voltage. In other words, the transient electric field equation meets the superposition principle applied.