The Experts below are selected from a list of 99 Experts worldwide ranked by ideXlab platform

H. Gumilang - One of the best experts on this subject based on the ideXlab platform.

  • transformer paper expected life estimation using anfis based on oil characteristics and dissolved gases case study indonesian transformers
    Energies, 2017
    Co-Authors: Rahman A. Prasojo, K. Diwyacitta, H. Gumilang
    Abstract:

    This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS) for power transformer paper Conditions in order to estimate the transformer’s expected life. The dielectric characteristics, dissolved gasses, and furfural of 108 running transformers were collected, which were divided into 76 training datasets and another 32 testing datasets. The degree of polymerization (DP) of the transformer paper was predicted using the ANFIS model based on using the dielectric characteristics and dissolved gases as input. These inputs were analyzed, and the best combination was selected, whereas CO + CO2, acidity, interfacial tension, and color were correlated with the paper’s Deterioration Condition and were chosen as the input variables. The best combination of input variables and membership function was selected to build the optimal ANFIS model, which was then compared and evaluated. The proposed ANFIS model has 89.07% training accuracy and 85.75% testing accuracy and was applied to a transformer paper insulation assessment and an estimation of the expected life of four Indonesian transformers for which furfural data is unavailable. This proposed algorithm can be used as a furfural alternative for the general assessment of transformer paper Conditions and the estimation of expected life and provides a helpful assistance for experts in transformer Condition assessment.

Zhengbo Liang - One of the best experts on this subject based on the ideXlab platform.

  • Morphological, Structural, and Dielectric Properties of Thermally Aged AC 500 kV XLPE Submarine Cable Insulation Material and Its Deterioration Condition Assessment
    IEEE Access, 2019
    Co-Authors: Ruijin Liao, Jian Li, Zhengbo Liang
    Abstract:

    Cross-linked polyethylene (XLPE) has been widely used as insulation material for cables. In 2019, the highest voltage level AC 500 kV XLPE submarine cable has been operated in Zhoushan, China. The irreversible degradation poses a safety hazard to the operation of submarine cable. Therefore, it is necessary to investigate the physical, chemical and electrical properties of XLPE submarine cable insulation under aging Condition and explore the method for its Deterioration degree assessment. In this paper, the AC 500 kV XLPE submarine cable insulation material was thermally aged at 130 °C. The Deterioration characteristics of materials were analyzed based on morphology, chemical structure, mechanical property, thermal property and dielectric properties. Multiple characteristic parameters were extracted and new Deterioration Condition assessment model was established. Results show that the physicochemical characteristic parameters including retention rate of elongation at break, carbonyl index (CI) based on FTIR, full-width at half-maximum (FWHM) of the diffraction peak based on XRD, melting enthalpy based on DSC analysis, and the dielectric characteristic parameters including modified Cole-Cole model parameter χsα and AC breakdown strength are sensitive to Deterioration Condition of XLPE material. According to the change of elongation retention at break, the Deterioration Condition of XLPE sample was divided into enhanced stage, wear-out stage and disposal stage. The new multi-factor Deterioration Condition assessment model including six characteristic parameters (retention rate of elongation at break, CI, FWHM, melting enthalpy, modified Cole-Cole model parameter χsα, AC breakdown strength) was successfully established by grey correlation analysis. The new model can reflect the property of mechanical, chemical, thermal and dielectric property and has prominent effect in differentiating Deterioration degree of the AC 500 kV XLPE submarine cable insulation material.

Mahmoud-reza Haghifam - One of the best experts on this subject based on the ideXlab platform.

  • Midterm system level maintenance scheduling of transmission equipment using inspection based model
    International Journal of Electrical Power & Energy Systems, 2019
    Co-Authors: Morteza Samadi, Hossein Seifi, Mahmoud-reza Haghifam
    Abstract:

    Abstract Condition Based Maintenance (CBM) using inspection data is one of the available maintenance approaches for power system equipment. In Inspection Based Maintenance (IBM) as a specific type of CBM, decisions about the time and type of the maintenance tasks are made after determining the Deterioration Condition of the equipment. In this paper, an IBM model is proposed for yearlong transmission equipment maintenance scheduling. In order to quantify the effect of the inspection and maintenance tasks, the probability distribution of the Deterioration Condition is calculated using the transition probability matrix of the Markov process. The problem of system level maintenance scheduling is formulated with binary variables as weekly inspection time during the year. Inspection time of equipment is optimized by minimizing the total cost, including inspection, maintenance, redispatch and failure costs while network security constraints are considered. The proposed model is implemented for the maintenance of transformers and transmission lines in IEEE-RTS and IEEE 57-bus test systems.

Rahman A. Prasojo - One of the best experts on this subject based on the ideXlab platform.

  • transformer paper expected life estimation using anfis based on oil characteristics and dissolved gases case study indonesian transformers
    Energies, 2017
    Co-Authors: Rahman A. Prasojo, K. Diwyacitta, H. Gumilang
    Abstract:

    This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS) for power transformer paper Conditions in order to estimate the transformer’s expected life. The dielectric characteristics, dissolved gasses, and furfural of 108 running transformers were collected, which were divided into 76 training datasets and another 32 testing datasets. The degree of polymerization (DP) of the transformer paper was predicted using the ANFIS model based on using the dielectric characteristics and dissolved gases as input. These inputs were analyzed, and the best combination was selected, whereas CO + CO2, acidity, interfacial tension, and color were correlated with the paper’s Deterioration Condition and were chosen as the input variables. The best combination of input variables and membership function was selected to build the optimal ANFIS model, which was then compared and evaluated. The proposed ANFIS model has 89.07% training accuracy and 85.75% testing accuracy and was applied to a transformer paper insulation assessment and an estimation of the expected life of four Indonesian transformers for which furfural data is unavailable. This proposed algorithm can be used as a furfural alternative for the general assessment of transformer paper Conditions and the estimation of expected life and provides a helpful assistance for experts in transformer Condition assessment.

Hasmat Malik - One of the best experts on this subject based on the ideXlab platform.

  • Make use of DGA to carry out the transformer oil-immersed paper Deterioration Condition estimation with fuzzy-logic
    Procedia Engineering, 2012
    Co-Authors: Hasmat Malik, Raj Kumar Jarial
    Abstract:

    Remaining Life of the oil-immersed transformer is decided due to Deterioration of the winding insulation paper (WIP). The DGA method is conventionally used to estimate the WIP Deterioration status Condition. This paper presented the four status Conditions assessment of paper Deterioration for oil-immersed transformer using fuzzy-logic (FL). In this paper the correlation between accumulated values of carbon dioxide (CO2) and carbon monoxide (CO) with insulation resistance in oil-filled power transformers is studied using FL. The authors have estimated the insulation paper Deterioration Condition using proposed method for 20 transformers or more. As a result, appropriate maintenance scenario can be planned.

  • Paper insulation Deterioration estimation of power transformer using fuzzy-logic
    Proceedings - 2011 Annual IEEE India Conference: Engineering Sustainable Solutions INDICON-2011, 2011
    Co-Authors: Hasmat Malik, Nikhil Kushwaha, Amit Kr. Yadav
    Abstract:

    Remaining Life of the oil-immersed transformer is decided due to Deterioration of the winding insulation paper (WIP). The DGA method is conventionally used to estimate the WIP Deterioration status Condition. This paper presented the four status Conditions assessment of paper Deterioration for oil-immersed transformer using fuzzy-logic (FL). In this paper the correlation between accumulated values of carbon dioxide (CO2) and carbon monoxide (CO) with insulation resistance in oil-filled power transformers is studied using FL. The authors have estimated the insulation paper Deterioration Condition using proposed method for 70 transformers or more. As a result, appropriate maintenance scenario can be planned.