Analysis of Gas Generated in Mineral Oil, Synthetic Ester, and Natural Ester as a Consequence of Thermal Faults

Przybyłek, Piotr; Gielniak, J.

doi:10.1109/access.2019.2917761

Cited by 25 publications

(16 citation statements)

References 22 publications

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“…In this study, a model control based on ANFIS is adopted for the controller. The proposed WECS factors and parameters are listed in the Appendix of this paper [8,9]. The state dynamic formulation of the WECS are at normal load point is described as follows,…”

Section: Wind Energy Conversion Systemmentioning

confidence: 99%

“…In the literature, many research papers have been directed to blade pitch control of WECS interconnected to power systems. It is a fact that modeling of the suitable blade pitch control scheme is the major requirement for WECS to preserve the power generated from the wind turbine at its highest value while improving aerodynamic characteristics [9], [10]. However, it is a challenging task to build a comprehensive WECS dynamical model due to the highly fluctuated profiles and nonlinearity [11].…”

Section: Introductionmentioning

confidence: 99%

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Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations

et al. 2021

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Wind speed fluctuations and load demand variations represent the big challenges against wind energy conversion systems (WECS). Besides, the inefficient measuring devices and the environmental impacts (e.g. temperature, humidity, and noise signals) affect the system equipment, leading to increased system uncertainty issues. In addition, the time delay due to the communication channels can make a gap between the transmitted control signal and the WECS that causes instability for the WECS operation. To tackle these issues, this paper proposes an adaptive neuro-fuzzy inference system (ANFIS) as an effective control technique for blade pitch control of the WECS instead of the conventional controllers. However, the ANFIS requires a suitable dataset for training and testing to adjust its membership functions in order to provide effective performance. In this regard, this paper also suggests an effective strategy to prepare a sufficient dataset for training and testing of the ANFIS controller. Specifically, a new optimization algorithm named the mayfly optimization algorithm (MOA) is developed to find the optimal parameters of the proportional integral derivative (PID) controller to find the optimal dataset for training and testing of the ANFIS controller. To demonstrate the advantages of the proposed technique, it is compared with different three algorithms in the literature. Another contribution is that a new time-domain named figure of demerit is established to confirm the minimization of settling time and the maximum overshoot in a simultaneous manner. A lot of test scenarios are performed to confirm the effectiveness and robustness of the proposed ANFIS based technique. The robustness of the proposed method is verified based on the frequency domain conditions that are driven from Hermite-Biehler theorem. The results emphases that the proposed controller provides superior performance against the wind speed fluctuations, load demand variations, system parameters uncertainties, and the time delay of the communication channels.

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Section: Wind Energy Conversion Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations

et al. 2021

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“…The dissolved gas analysis (DGA) with insulating oil can be implemented to identify the condition, interpret faults, and provide early warning of some problems inside the transformer. Many DGA techniques are widely used to diagnose significant faults; those techniques include electrical discharges, PD, electrical arcing, and thermal fault [5][6][7][8]. Reference [9] proposes the failure analysis based on the dissolved key gas concentration, total dissolved combustible gases (TDCG), and key gas.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Approach to Dissolved Gas Analysis for Power Transformer Failure Index and Fault Identification

Poonnoy

Suwanasri

2020

Energies

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This research focuses on problem identification due to faults in power transformers during operation by using dissolved gas analysis such as key gas, IEC ratio, Duval triangle techniques, and fuzzy logic approaches. Then, the condition of the power transformer is evaluated in terms of the percentage of failure index and internal fault determination. Fuzzy logic with the key gas approach was used to calculate the failure index and identify problems inside the power transformer. At the same time, the IEC three-gas ratio and Duval triangle are subsequently applied to confirm the problems in different failure types covering all possibilities inside the power transformer. After that, the fuzzy logic system was applied and validated with DGA results of 244 transformers as reference cases with satisfactory accuracy. Two transformers were evaluated and practically confirmed by the investigation results of an un-tanked power transformer. Finally, the DGA results of a total of 224 transformers were further evaluated by the fuzzy logic system. This fuzzy logic is a smart, accurate tool for automatically identifying faults occurring within transformers. Finally, the recommendation of maintenance strategy and time interval is proposed for effective planning to minimize the catastrophic damage, which could occur with the power transformer and its network.

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“…Several scholars have studied the gas production characteristics of natural ester and mineral oil. Piotr Przybylek et al analyzed the gas production characteristics of mineral oil, natural ester, and synthetic oil in electrical and thermal failure [8]. Zerye Ayalew et al showed that the fault of natural ester and mineral oil mainly produced H 2 , CO, CH 4 , C 2 H 2 , CO 2 , C 2 H 4 , and C 2 H 6 [9].…”

Section: Introductionmentioning

confidence: 99%

Difference Analysis of Gas Molecules Diffusion Behavior in Natural Ester and Mineral Oil Based on Molecular Dynamic Simulation

Hao

Chen³

et al. 2019

Molecules

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Natural ester, as a new environmentally green insulating oil, has been widely used in transformer. In an oil-immersed transformer, the normal aging, thermal failure, and discharge failure could easily lead to the decomposition of the oil-paper insulation system and produce different kinds of gases. Studying gas dissolution in natural ester and mineral oil could provide assistance in applying criteria to make a diagnosis of different kinds of faults in the transformer. In this paper, the molecular dynamics method was used to investigate the diffusion behavior of seven fault characteristic gases (including H2, CO, CH4, C2H2, CO2, C2H4, C2H6) in natural ester and mineral oil. The simulation parameters of free volume, interaction energy, mean square displacement, and diffusion coefficient were compared between the natural ester and mineral oil. Meanwhile, the influence of temperature on the diffusion of gas molecules in two kinds of oils was also analyzed. Results showed that the free volume, the interaction energy, and the relative molecular mass of gas molecules were the factors influenced by the diffusion of gas molecules in natural ester and mineral oil. The order of the diffusion coefficients of gas molecules in natural ester was as follows: H2 > CH4 > CO > C2H2 > C2H4 > CO2 > C2H6 and that in mineral oil was as follows: H2 > CH4 > CO> C2H2 > C2 H4 > C2H6 > CO2. By comparing the diffusion behavior of gas molecules in natural ester and mineral oil, it was found that the smaller free volume and higher interaction energy of gas molecules in natural ester were the major reasons for the gas molecules to be more difficult to diffuse in natural ester. The rising temperature could enhance the free volume and reduce the interaction energy between gas molecules and oil. The diffusion coefficient of gas molecules increased exponentially with the follow of temperature. However, the temperature didn’t affect the ordering of diffusion coefficient, free volume, and interaction energy of gas molecules in natural ester and mineral oil.

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Analysis of Gas Generated in Mineral Oil, Synthetic Ester, and Natural Ester as a Consequence of Thermal Faults

Cited by 25 publications

References 22 publications

Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations

Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations

Fuzzy Logic Approach to Dissolved Gas Analysis for Power Transformer Failure Index and Fault Identification

Difference Analysis of Gas Molecules Diffusion Behavior in Natural Ester and Mineral Oil Based on Molecular Dynamic Simulation

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