Condition assessment of power transformers status based on moisture level using fuzzy logic techniques

Rexhepi, Vezir; Nakov, Petar

doi:10.14203/j.mev.2018.v9.17-24

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…A linguistic variable might be considered a value variable, a fuzzy number, or a variable. The fuzzy logic of fuzzy set theory serves as a foundation for mathematical modeling and language, allowing for the accurate expression of highly advanced algorithms [25]. Fuzzy means blurred or unclear.…”

Section: B Fuzzy Logicmentioning

confidence: 99%

Water quality assessment monitoring system using fuzzy logic and the internet of things

Fakhrurroja,

Nuryatno,

Munandar

et al. 2023

J. Mechatron. Electr. Power Veh. Technol.

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Water utilization has recently been at its highest level of demand. The water needed to be clean, healthy, and determined to be suitable for consumption. Therefore, it is necessary to have a system that can monitor the water quality so thatinformation related to wate r suitability can be received regularly and in real-time. This paper addresses the critical need for real-time water quality monitoring systems. This study proposed a novel approach integrating the Tsukamoto fuzzy algorithm into an internet of things (IoT)-based framework, forming part of the Fuzzy Inference System. Our system serves as a decision support tool, enabling continuous assessment of water quality. The method categorizes water quality into three levels: good, moderate, and unhealthy, providing timely and precise suitability information. The results demonstrate the effectiveness of the fuzzy logic method in delivering accurate output. Through remotely deployed IoT devices, water suitability and status can be monitored and analyzed in real-time over the internet. This research bridges the gap between traditional water quality assessment methods and the demands of our modern, technology-driven society, ensuring a reliable supply of safe and consumable water.

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Section: B Fuzzy Logicmentioning

confidence: 99%

Water quality assessment monitoring system using fuzzy logic and the internet of things

Fakhrurroja,

Nuryatno,

Munandar

et al. 2023

J. Mechatron. Electr. Power Veh. Technol.

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“…In recent years, researchers have used intelligent techniques such as fuzzy theory (Rexhepi and Nakov, 2018), clustering (Eke et al, 2019), and neural networks (Islam et al, 2017) to fully combine and utilize the condition quantities of transformers, which can eventually assess the current health of transformers more accurately and thus avoid large-scale power accidents due to sudden failures. Many researchers have combined these intelligent techniques and their improved methods with the dissolved gas approach (DGA) for assessing the health of oil-immersed transformers.…”

Section: Introductionmentioning

confidence: 99%

Research on Variable Weight Synthesizing Model for Transformer Condition Assessment

et al. 2022

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Transformer is one of the important equipment in the power grid, which helps to integrate renewable energy into the transmission and distribution network efficiently. The safe and stable operation of transformer is of great importance for the reliable transmission of electricity generated from renewable energy and for the reliable use of electricity by the end users. Therefore, it is important to assess the condition to avoid the faults of the transformer. In this paper, a variable weight synthesizing assessment model is presented that combines the G1 method, the entropy weight method, and a variable-weight method proposed in this paper to assess the condition of transformer based on the offset of the transformer equivalent circuit parameters. First, we propose deterioration indexes oriented to the maintenance management needs, which can well reflect the degree of deterioration of each transformer component. Second, the various defects of the transformer are used as the assessment indexes, and the initial weight is given to the assessment indexes according to the damage degree of the defect. The initial weight is calculated comprehensively by the G1 method and the entropy weight method. Then, each index is scored according to the offset of the equivalent circuit parameters, and the weights are adjusted appropriately according to the scores of the indicators using a variable weighting method to emphasize the severity of the defect or the “sub-health” condition of the transformer. Finally, the respective scores and combined weights of the assessment indexes are weighted to obtain a comprehensive score. The simulation shows that the model is more sensitive to abnormal and “subhealth” conditions of the transformer, which verifies the feasibility of the variable weight synthesizing model to assess the condtion of the transformer.

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“…Such smart structure devices help to recognize the operation of transformer equipment and, among other things, affect the safety and diagnosis of its operating parameters. It should be noted that the assessment of the state of electrical, thermal, and mechanical parameters is one of the main elements for defining possible defects in transformers [7].…”

Section: Introductionmentioning

confidence: 99%

Monitoring parameters of power transformers in the electrical power system through smart devices

Rexhepi

Hulaj

2020

Journal of Energy Systems

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Nowadays the advancement of technology and equipment to monitor the operating performance of power transformer has achieved a high level. So, the monitoring system enables the continued investigation of the operational work of power transformer parameters as well as the prevention of failures and enhance reliability. However, the monitoring of power transformers is of unquestionable value for the electrical power systems and consumers to have more reliability in supplying. Therefore, given that monitoring involves a considerable number of parameters and elements of transformers, in the present case the overview of the monitoring of some of the most important parameters has been taken into account. Thus, the paper includes the monitoring parameters such as; partial discharges, oil and winding temperatures, bushing currents, tap changer, moisture and dissolved gas analysis. Also, in the paper are presented data for the operation of these parameters in different periods as well as with different loading regimes. The reports of events that correspond to the operational performance of the transformer, which are a good cause for diagnosis and preliminary actions in transformers, are also presented.

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Condition assessment of power transformers status based on moisture level using fuzzy logic techniques

Cited by 6 publications

References 13 publications

Water quality assessment monitoring system using fuzzy logic and the internet of things

Water quality assessment monitoring system using fuzzy logic and the internet of things

Research on Variable Weight Synthesizing Model for Transformer Condition Assessment

Monitoring parameters of power transformers in the electrical power system through smart devices

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