Fault Identification in a Subsea ESP Power Distribution System Using Electrical Waveform Monitoring

2021 ◽  
Author(s):  
Larry Obst ◽  
Andrew Merlino ◽  
Alex Parlos ◽  
Dario Rubio

Abstract This paper describes the technology and processes used to identify in a timely matter the source of an Instantaneous Over Current (IOC) trip during an ESP re-start at Shell Perdido SPAR. Monitoring health condition of subsea ESPs is challenging. ESPs operate in harsh and remote environments which makes it difficult to implement and maintain any in-situ monitoring system. Shell operates five subsea ESPs and implemented a topside conditioning monitoring system using electrical waveform analysis. The Perdido SPAR had a scheduled maintenance shutdown in April 2019. While ramping the facility down on April 19, 2019 the variable frequency drive (VFD) for ESP-E tripped on a cell overvoltage fault. The cell was changed, but the VFD continued to trip on instantaneous overcurrent. During ramp up beginning April 29, 2019 most equipment came back online smoothly, but the VFD of the particular ESP labeled ESP-E continued to experience the problem that was causing overcurrent trips, preventing restart. Initial investigations could not pinpoint the source of the issue. On May 1, 2019 Shell sought to investigate this issue using high-frequency electrical waveform data recorded topside as an attempt to better pinpoint the source of this trip. Analysis of electrical waveform before, during and after the IOC trip found an intermittent shorting/arcing at the VFD and ruled out any issues with the 7,000-foot-long umbilical cable or ESP motor. Upon further inspection, a VFD technician was able to visually identify the source of the problem. Relying in part on electrical waveform findings, VFD technician found failed outer jackets in the MV shielded cables at the output filter section creating a ground path from the VFD output bus via the cable shield. The cables were replaced, and the problem was alleviated allowing the system to return to normal operation. Shell credits quick and accurate analysis of electrical waveform with accelerating troubleshooting activities on the VFD, saving approximately 1-2 days of troubleshooting time and associated downtime savings, that translate to approximately 50,000 BOE deferment reduction. Analysis of high-frequency electrical waveform using physics-based and machine learning algorithms enables one to extract long-term changes in ESP health, while filtering out the shorter-term changes caused by operating condition variations. This novel approach to analysis provides operators with a reliable source of information for troubleshooting and diagnosing failure events to reduce work-over costs and limit production losses.

2020 ◽  
Vol 13 (9) ◽  
pp. 1807-1818
Author(s):  
M. Jagabar Sathik ◽  
Kaustubh Bhatnagar ◽  
Yam P. Siwakoti ◽  
Hussain M. Bassi ◽  
Muhyaddin Rawa ◽  
...  

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3242 ◽  
Author(s):  
Muhammad Salman Saeed ◽  
Mohd Wazir Mustafa ◽  
Usman Ullah Sheikh ◽  
Touqeer Ahmed Jumani ◽  
Ilyas Khan ◽  
...  

Electricity fraud in billing are the primary concerns for Distribution System Operators (DSO). It is estimated that billions of dollars are wasted annually due to these illegal activities. DSOs around the world, especially in underdeveloped countries, still utilize conventional time consuming and inefficient methods for Non-Technical Loss (NTL) detection. This research work attempts to solve the mentioned problem by developing an efficient energy theft detection model in order to identify the fraudster customers in a power distribution system. The key motivation for the present study is to assist the DSOs in their fight against energy theft. The proposed computational model initially utilizes a set of distinct features extracted from the monthly consumers’ consumption data, obtained from Multan Electric Power Company (MEPCO) Pakistan, to segregate the honest and the fraudulent customers. The Pearson’s chi-square feature selection algorithm is adopted to select the most relevant features among the extracted ones. Finally, the Boosted C5.0 Decision Tree (DT) algorithm is used to classify the honest and the fraudster consumers based on the outcomes of the selected features. To validate the superiority of the proposed NTL detection approach, its performance is matched with that of few state-of-the-art machine learning algorithms (one of most exciting recent technologies in Artificial Intelligence), like Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN) and Extreme Gradient Bossting (XGBoost). The proposed NTL detection method provides an accuracy of 94.6%, Sensitivity of 78.1%, Specificity of 98.2%, F1 score 84.9% and Precision of 93.2% which are significantly higher than that of the same for the above-mentioned algorithms.


2013 ◽  
Vol 416-417 ◽  
pp. 781-784
Author(s):  
Mei Sun

With the development of domestic low-voltage power distribution technology, people have an increasingly higher demand on the intelligence of low-voltage power distribution cabinet. Combined with the authors several years of experience of practice, this thesis first of all makes a brief analysis of the general situation of power distribution system automation, followed by a key analysis and conclusion of the characteristics of the existing low-voltage monitoring mode. Based on it, digital signal processor with strong floating point calculation ability, a new low-voltage intelligent monitoring system is designed.


Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1376 ◽  
Author(s):  
Naveed Ashraf ◽  
Tahir Izhar ◽  
Ghulam Abbas ◽  
Valentina E. Balas ◽  
Marius M. Balas ◽  
...  

In this research, a new single-phase direct AC-to-AC converter, operating in buck and boost mode, with a bipolar voltage gain, is proposed. The operation is accomplished through high frequency direct and indirect PWM control of a single switch with low voltage stresses. This reduces, not only the control effort, but also the switching losses. The low voltage stresses across the high frequency switches, reduce the dv/dt problem significantly without any loss and bulky voltage snubber arrangement. The operation, in its all-operating modes, has a low inductor ripple current and switching current. The proposed converter may be employed as an AC voltage restorer in a power distribution system to cope with the voltage sag and swell issues. The detailed analysis of the proposed converter is carried out in order to compare its performance with the existing converters. The simulation results obtained using the MATLAB/Simulink environment are verified through experimental results.


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