Estimation of the Effect of Electric Vehicles on the Aging of Distribution Transformers Using Fuzzy Logic

Depending on industrialization and technological advancements worldwide, the demand for electrical energy, recognized as clean and dependable energy, is on the rise. Presently, electric energy consumption has notably increased alongside the rise in Electric Vehicles (EVs). The surge in EVs necessitates a thorough examination of the situation, anticipating the widespread adoption of Electric Vehicle Fast Charging Stations (EVFCS) in the near future and the subsequent escalation of their adverse impact on the grid. To mitigate these negative effects on the grid, proactive measures are essential. EVs function as capacitive loads due to their battery composition, and the harmonics produced during their grid connection detrimentally affect the quality of grid electricity, leading to constraints. Furthermore, the escalating EVFCS loads resulting from the rapid growth in EV numbers distribute the burden on distribution networks, posing a threat to network adequacy and reliability. Therefore, integrating EVFCS with distribution and generation units to minimize overloading, additional losses, and voltage fluctuations in the grid will enhance the efficiency of both systems. In addition, each EVFCS is only connected to the distribution transformer assigned to it or to the distribution transformers considered suitable in the city. Depending on the current drawn by one or more EVFCS linked to the feeder of each transformer, it can lead to overloading in transformers and chemical changes in windings and oils, resulting in the aging of transformers. In this context, a FL-based estimation is conducted to assess the impact of EVs' charging loads on transformer aging. The FL method utilizes transformer current load, EVFCS load, transformer temperature, and harmonic power quality data. The data utilized are derived from statistical information about a local distribution network and measured values from a feeder, and the aging effects on EVFCS distribution transformers are examined.

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Publication Details

Journal
Balkan Journal of Electrical and Computer Engineering
Published
2024-09-30
DOI
https://doi.org/10.17694/bajece.1503781
Citations
1
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.20
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article

Estimation of the Effect of Electric Vehicles on the Aging of Distribution Transformers Using Fuzzy Logic

Onur Akar
1 citations
Balkan Journal of Electrical and Computer Engineering
Advanced Battery Technologies Research
0.20
article

Estimation of the Effect of Electric Vehicles on the Aging of Distribution Transformers Using Fuzzy Logic

Onur Akar
article en
1 citations

Abstract

Depending on industrialization and technological advancements worldwide, the demand for electrical energy, recognized as clean and dependable energy, is on the rise. Presently, electric energy consumption has notably increased alongside the rise in Electric Vehicles (EVs). The surge in EVs necessitates a thorough examination of the situation, anticipating the widespread adoption of Electric Vehicle Fast Charging Stations (EVFCS) in the near future and the subsequent escalation of their adverse impact on the grid. To mitigate these negative effects on the grid, proactive measures are essential. EVs function as capacitive loads due to their battery composition, and the harmonics produced during their grid connection detrimentally affect the quality of grid electricity, leading to constraints. Furthermore, the escalating EVFCS loads resulting from the rapid growth in EV numbers distribute the burden on distribution networks, posing a threat to network adequacy and reliability. Therefore, integrating EVFCS with distribution and generation units to minimize overloading, additional losses, and voltage fluctuations in the grid will enhance the efficiency of both systems. In addition, each EVFCS is only connected to the distribution transformer assigned to it or to the distribution transformers considered suitable in the city. Depending on the current drawn by one or more EVFCS linked to the feeder of each transformer, it can lead to overloading in transformers and chemical changes in windings and oils, resulting in the aging of transformers. In this context, a FL-based estimation is conducted to assess the impact of EVs' charging loads on transformer aging. The FL method utilizes transformer current load, EVFCS load, transformer temperature, and harmonic power quality data. The data utilized are derived from statistical information about a local distribution network and measured values from a feeder, and the aging effects on EVFCS distribution transformers are examined.

Balkan Journal of Electrical and Computer EngineeringVol. 12(3)
Marmara University (TR)
Affordable and clean energy
Openalex Percentile: Top 49%
Advanced Battery Technologies Research
0.20
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