Effects of lifetime and loading factor on dissolved gases in power transformers

Diwyacitta, Karunika; Prasojo, Rahman Azis; Suwarno, &; Gumilang, Harry

doi:10.1109/icecos.2017.8167142

Cited by 13 publications

(5 citation statements)

References 10 publications

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“…Trend of DGA in operating time of transformer shows that CO and CO2 will gradually increases as the transformer operated [1] [9][11] [15][16][17][18][19]. On the other hand, some dielectric characteristics of oil insulation indicates ageing pattern with its strong correlation to transformer operating time.…”

Section: Introduction a Power Transformermentioning

confidence: 99%

Study on Correlation Among Oil Dielectric Characteristics, Dissolved Gases, and Operating Life of 150 kV Power Transformer

Diwyacitta¹,

Prasojo²,

Suwarno³

2017

ijeei

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Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper insulation degradation in transformer can be assessed through the change in oil characteristics and the dissolved gases. Data related to these parameters are abundant, but study on correlation among these parameters and the operating time of power transformer is still limited. This paper presents statistical insights into aging of transformer insulation system through oil characteristics, dissolved gases and the operating time of transformer. As much as 219 in service 150 kV transformers population testing data were included in this study. The data was analyzed using linear regression correlation analysis to Figureure out the dependency of each parameters. Statistical correlation between each properties of oil insulation, dissolved gases and operating time were carried out. There are some oil properties that have correlation with operating time, which are color scale, IFT and acidity. Moreover, color scale, IFT and acidity shows dependency among them. IFT tends to gradually decrease while acidity increases as operating time trend rises. On the other hand, operating time are also highly correlated with CO and CO2, which are commonly known as the main product of paper insulation degradation in transformers. Correlation among prior correlated parameters found that CO is strongly correlated with color and IFT. Subsequently, a high correlation coefficient of parameter to operating time could be interpreted that the ageing process happens during the life of a transformer changes certain parameters which these changes should be noticed for better decision making whether the transformer still feasible to be used in the system with certain maintenance or should be replaced.

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Section: Introduction a Power Transformermentioning

confidence: 99%

Study on Correlation Among Oil Dielectric Characteristics, Dissolved Gases, and Operating Life of 150 kV Power Transformer

Diwyacitta¹,

Prasojo²,

Suwarno³

2017

ijeei

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“…Batas dari parameterparameter isolasi minyak telah diusulkan pada CIGRE 761(2019). Ketika besaran hasil parameter uji mencapai batas yang telah ditentukan, peringatan dan tindakan untuk mencegah kegagalan isolasi minyak transformator dapat diusulkan [11]. Diagnosis kondisi transformator menggunakan metode scoring matrix diharapkan mampu memberikan jawaban atas kondisi minyak transformator secara aktual.…”

Section: Pendahuluanunclassified

Implementasi Metode Scoring Matrix dalam Menentukan Indeks Kondisi Minyak Isolasi pada Transformator Daya 150 kV

Prasojo

Safarina²,

Islam³

et al. 2023

elposys

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Transformers are critical equipment in electrical power system which assist in transmitting electrical energy from generators to consumers. Oil insulation is one of the key component in power transformer. Poor quality of oil insulation can be fatal to the transformer, especially when a disturbance occurs. Oil insulation can affect the aging of power transformers and the failure can disturb the continuity of electrical energy supplied to consumers. There are three things that affect the condition of transformer oil insulation, namely chemical, electrical, and physical. The test results of oil insulation parameters that were collected was assessed individually, such as Interfacial Tension (IFT), colour, breakdown voltage (BDV), acidity, and water content. Then, the condition assessment of power transformer oil insulation using a scoring matrix method proposed in CIGRE TB 761 was performed to determine the assessment index of oil insulation conditions of two 150 kV power transformers based on the results of various oil testing. Lastly, recommended action is provided based on the analysis.

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“…These processes can stem from factors such as design safety margins, operation, and maintenance practices [2]. The transformer anticipated failure rates become unacceptable if nothing is done since the transformer needs a long time to repair [3]. Also, the statistical analysis found an increase in the failure rate for transformers aged between 30 and 40 [4].…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Influence of Non-Routine and Derived Features in the Development of Early Detection Model for Transformer Health Index Classification

Azlan Mohmad,

Mohd Hatta Mohammed Ariff,

Mohd Ibrahim Shapiai

et al. 2024

ARASET

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Establishing an effective HI model is challenging because it involves balancing cost, risk, and performance. The currently developed Reduced Features Model (RFM) for the transformer Health Index (HI) prediction may lead to late prediction. The RFM utilised non-routine input features to achieve a high-accuracy model where data availability is the primary concern. Hence, the common goal of Transformer Asset Management (TAM) in achieving acceptable availability and reliability of the transformer may not be achieved. In this paper, the primary objective is to investigate the performance of the HI model by considering routine test features as a baseline for developing the Early Detection Model (EDM). The development of EDM is significant, as the model shall provide a sustainable solution to the utility and plant owners in establishing their TAM strategies. Hence, this paper's case studies include performance investigation using routine, non-routine, and derived features from the routine test. Support Vector Machine (SVM) was used for the prediction modelling, and the model's performance was validated based on a 5-fold cross-validation technique to avoid biases. As a result, it was found that the average accuracy performance of 88.4% was obtained by considering only routine test features during the model validation process. However, complementing the routine test with other features, which were non-routine and derived features, increased the average performance accuracy model to 95.3%. Hence, further development of EDM is feasible and crucial for sustainable TAM solutions.

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Effects of lifetime and loading factor on dissolved gases in power transformers

Cited by 13 publications

References 10 publications

Study on Correlation Among Oil Dielectric Characteristics, Dissolved Gases, and Operating Life of 150 kV Power Transformer

Study on Correlation Among Oil Dielectric Characteristics, Dissolved Gases, and Operating Life of 150 kV Power Transformer

Implementasi Metode Scoring Matrix dalam Menentukan Indeks Kondisi Minyak Isolasi pada Transformator Daya 150 kV

Investigation of the Influence of Non-Routine and Derived Features in the Development of Early Detection Model for Transformer Health Index Classification

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