Relationship between PD magnitude distribution and pulse burst for positive coronas

Tang, Ju; Luo, Xinyu; Pan, Cheng

doi:10.1049/iet-smt.2018.5039

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…The steps for evaluating the reliability of IES are described as follows: Step 1 : Input the load data, original data of IES, including equivalent parameters of gas turbines, parameters of conventional power plant and wind farm, and so on. Let j = 1. Step 2 : Randomly generate a uniformly distributed random number in (0, 1), simulate the wind speed v ( j ) [24], the operating states of wind turbines s wg ( j ) [25], gas turbines s gt ( j ) and conventional generators s tp ( j ). Then calculate the output power of wind farm P wt ( j ), gas turbines P gt ( j ), and conventional power plant P tp ( j ). Step 3 : Calculate the total generation power, and check the load curtailment state of IES.…”

Section: Reliability Assessment Of Ies Considering Uncertainty Of Ngpesmentioning

confidence: 99%

“…Step 2 : Randomly generate a uniformly distributed random number in (0, 1), simulate the wind speed v ( j ) [24], the operating states of wind turbines s wg ( j ) [25], gas turbines s gt ( j ) and conventional generators s tp ( j ). Then calculate the output power of wind farm P wt ( j ), gas turbines P gt ( j ), and conventional power plant P tp ( j ).…”

Section: Reliability Assessment Of Ies Considering Uncertainty Of Ngpesmentioning

confidence: 99%

See 1 more Smart Citation

Reliability assessment of integrated energy system considering the uncertainty of natural gas pipeline network system

Yang

Zhang

et al. 2019

IET Generation, Transmission & Distribution

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Section: Reliability Assessment Of Ies Considering Uncertainty Of Ngpesmentioning

confidence: 99%

Section: Reliability Assessment Of Ies Considering Uncertainty Of Ngpesmentioning

confidence: 99%

Reliability assessment of integrated energy system considering the uncertainty of natural gas pipeline network system

Yang

Zhang

et al. 2019

IET Generation, Transmission & Distribution

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“…It will cause partial discharge (PD) as soon as the field strength exceeds a certain threshold, which is also the most common fault in high-voltage equipment [2]. In order to reduce the harmful effects of PD to the power system, recently, related scholars have researched from new insulation materials [3,4], online monitoring methods [5][6][7][8] and machine learning identification [9,10] etc. However, it is difficult for inspection workers to find PD in a short period, especially in noisy operating sites of switchgear.…”

Section: Introductionmentioning

confidence: 99%

Study on characteristics gases of metal protrusions partial discharge in 10‐kV air‐insulated switchgear

Tan

Song

Wang

et al. 2023

IET Science Measure & Tech

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Air‐insulated switchgear plays an important role in distribution network and partial discharge (PD) is one of the common faults in its operation. The method of gas component analysis, which is to detect chemical gas products, is a novel one to discover PD. In order to study the feasibility of the method, the monitoring experiment of characteristic gases, comprising carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), of metal protrusion PD is carried out. This paper conducts the comparative experiments on three main factors affecting PD: voltage, air humidity and degree of protrusion, as well as studies how they affect the formation of characteristic gases. According to the experimental result, higher applied voltage promotes the formation of characteristic gases in the same conditions. In addition, with the increase of humidity from 40% to 75%, the generation of gases is inhibited. Furthermore, when the needle–plate distance is 30 mm, the gas concentration has almost no change within 6 h, which is different from that of 10 mm. In conclusion, the difference in gases concentration reveals the influence of three main factors on the generation of characteristic gases and provides an analytical basis for PD detection by gas composition analysis.

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“…It is concluded that due to the dependence of electrical and optical discharge of SBUV, the optical energy measurement should not only count the pulses but should also consider the pulses heights. In addition, the optical measurement should consider a statistical variation similar to that of electrical discharge measurements, as well [15].…”

Section: Introductionmentioning

confidence: 99%

Opto-Electronics Review

Coetzer,

West

2021

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Solar-blind ultraviolet cameras with image intensifier with CMOS detector typically use various count methodologies to measure the optical energy of an electrical corona. However, these count methodologies are non-radiometric without considering parameters such as distance, focus-, zoom-, and gain setting of a camera. An algorithm which considers the calibration and radiometric measurement of optical energy for the slow frame rate intensifier type cameras is presented. Furthermore, it is shown how these calibration data together with the flowcharts are used for the conversion from raw measured data to radiometric energy values.

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Relationship between PD magnitude distribution and pulse burst for positive coronas

Cited by 3 publications

References 21 publications

Reliability assessment of integrated energy system considering the uncertainty of natural gas pipeline network system

Reliability assessment of integrated energy system considering the uncertainty of natural gas pipeline network system

Study on characteristics gases of metal protrusions partial discharge in 10‐kV air‐insulated switchgear

Opto-Electronics Review

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