Development of fault section identification technique for low voltage DC distribution systems by using capacitive discharge current

Noh, Chul-Ho; Kim, Chul‐Hwan; Gwon, Gi-Hyeon; Oh, Yun-Sik

doi:10.1007/s40565-017-0362-4

Cited by 14 publications

(7 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reference [12] proposes a smart protection scheme which utilizes micro-phasor measurement units (µPMUs) to obtain continuous rapid synchronized phasor measurement data. Reference [13] proposes a precise and rapid technique for identifying the fault section in a low-voltage DC (LVDC) distribution system. These methods skillfully utilize the network structure information and fault characteristics to solve fault diagnostic tasks.…”

Section: Introductionmentioning

confidence: 99%

Fault Location and Classification for Distribution Systems Based on Deep Graph Learning Methods

Chen

et al. 2023

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

Accurate and timely fault diagnosis is of great significance for the safe operation and power supply reliability of distribution systems. However, traditional intelligent methods limit the use of the physical structures and data information of power networks. To this end, this study proposes a fault diagnostic model for distribution systems based on deep graph learning. This model considers the physical structure of the power network as a significant constraint during model training, which endows the model with stronger information perception to resist abnormal data input and unknown application conditions. In addition, a special spatiotemporal convolutional block is utilized to enhance the waveform feature extraction ability. This enables the proposed fault diagnostic model to be more effective in dealing with both fault waveform changes and the spatial effects of faults. In addition, a multi-task learning framework is constructed for fault location and fault type analysis, which improves the performance and generalization ability of the model. The IEEE 33-bus and IEEE 37-bus test systems are modeled to verify the effectiveness of the proposed fault diagnostic model. Finally, different fault conditions, topological changes, and interference factors are considered to evaluate the anti-interference and generalization performance of the proposed model. Experimental results demonstrate that the proposed model outperforms other state-of-the-art methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Fault Location and Classification for Distribution Systems Based on Deep Graph Learning Methods

Chen

et al. 2023

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

show abstract

“…T HE medium-voltage (MV) and low-voltage (LV) DC distribution systems have attracted increased attention in the past few years, owing to the advantages of concise structure, high economy, and convenient interface to energy storage devices (ESDs) and renewable power generators (RP-Gs) [1], [2]. However, the penetration of power-electroniccontrolled DC RPGs will lead to power quality issues [3].…”

Section: Introductionmentioning

confidence: 99%

Superconducting Magnetic Energy Storage Based DC Unified Power Quality Conditioner with Advanced Dual Control for DC-DFIG

Yang

Jin

Zhou

et al. 2022

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

The development of DC custom power protection devices is still in infancy that confines the sensitive loads integrated into medium-voltage (MV) and low-voltage (LV) DC networks. Considering the DC doubly-fed induction generator (DC-DFIG) based wind energy conversion system (WECS), this paper proposes a dual active bridge (DAB) based DC unified power quality conditioner (DC-UPQC) with the integration of superconducting magnetic energy storage (SMES) to maintain the terminal voltage of DC-DFIG and regulate the current flow. The principle of the proposed DC-UPQC has three parts, i.e., parallel-side DAB (PDAB), series-side DAB (SDAB), and SMES, used for the voltage compensation, current and power regulation, and energy storage, respectively. The circuit principle of the PDAB and SDAB and the modeling of SMES are analyzed in this paper. A DC dual control strategy is also proposed to deal with the DC voltage oscillation generated by the AC-side asymmetrical fault. A case study of DC-DFIG interfaced with DC power grid is carried out, integrated with the proposed SMES-based DC-UPQC to verify the high-power applications of the proposed structure. Finally, an experiment is implemented, and the results demonstrate the correctness of the theoretical analysis and the feasibility of the proposed structure.

show abstract

“…In [16], low-resistance and high-resistance faults were distinguished, and a fault detection and location estimation method using the voltage applied to the inductor for low-resistance faults and the ground fault current for high-resistance faults was proposed. In [17], a fault-area detection method was proposed using the capacitor discharge current. In [18], a new protection method was proposed combining the change in voltage (dv/dt) and the change in current (di/dt).…”

Section: Introductionmentioning

confidence: 99%

Development of New Protection Scheme in DC Microgrid Using Wavelet Transform

Seo¹

2022

Energies

View full text Add to dashboard Cite

The demand for a low voltage direct current (LVDC) microgrid is increasing by the increase of DC-based digital loads and renewable resources and the rapid development of power electronics technology. For the stable operation of an LVDC microgrid, it is necessary to develop a protection method. In this paper, the new protection scheme considering the fault section is proposed using wavelet transform (WT) in an LVDC microgrid. The fault sections are classified into DC side of the alternating current (AC)/DC converter, DC/DC converter connected to photovoltaic (PV) system, DC line, and DC bus. The characteristics of fault current at each fault section are analyzed. Based on these analyses, the new protection scheme including the fault section estimation is proposed using WT. The proposed scheme estimates the fault section using the detail component after performing WT and sends the trip signal to each circuit breaker according to the fault section. The proposed protection scheme is verified through various simulations according to the fault region and fault current using electromagnetic transient program (EMTP)/ATPDraw and MATLAB. The simulation results show that the fault section is accurately determined, and the corresponding circuit breaker (CB) operations are performed.

show abstract

Development of fault section identification technique for low voltage DC distribution systems by using capacitive discharge current

Cited by 14 publications

References 25 publications

Fault Location and Classification for Distribution Systems Based on Deep Graph Learning Methods

Fault Location and Classification for Distribution Systems Based on Deep Graph Learning Methods

Superconducting Magnetic Energy Storage Based DC Unified Power Quality Conditioner with Advanced Dual Control for DC-DFIG

Development of New Protection Scheme in DC Microgrid Using Wavelet Transform

Contact Info

Product

Resources

About