Novel Approach for Optimizing the Transformer’s Critical Power Limit

El-Bayeh, Claude Ziad; Mougharbel, Imad; Asber, Dalal; Saad, Maarouf; Chandra, Ambrish; Lefebvre, S.

doi:10.1109/access.2018.2873077

Cited by 16 publications

(17 citation statements)

References 28 publications

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“…Negative impact on the PG due to high power demand from Base Load "1"; Base Load + EVs "2", or Both "3" [161][162][163][164][165][166] 1. It is hard to determine how many EVs will positively or negatively affect the PG and the transformer.…”

Section: Reduction Of Harmful Gases the Emission Of Harmful Gases Comentioning

confidence: 99%

Charging and Discharging Strategies of Electric Vehicles: A Survey

El-Bayeh

Alzaareer

Aldaoudeyeh

et al. 2021

WEVJ

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The literature covering Plug-in Electric Vehicles (EVs) contains many charging/discharging strategies. However, none of the review papers covers such strategies in a complete fashion where all patterns of EVs charging/discharging are identified. Filling a gap in the literature, we clearly and systematically classify such strategies. After providing a clear definition for each strategy, we provide a detailed comparison between them by categorizing differences as follows: complexity; economics and power losses on the grid side; ability to provide ancillary services for integrity of the power grid; operation aspects (e.g., charging timing); and detrimental impact on the EV, the power grid, or the environment. Each one of these comparison categories is subdivided into even more detailed aspects. After we compare the EV charging/discharging strategies, we further provide recommendations on which strategies are suitable for which applications. Then, we provide ratings for each strategy by weighting all aspects of comparison together. Our review helps authors or aggregators explore likely choices that might suit the specific needs of their systems or test beds.

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Section: Reduction Of Harmful Gases the Emission Of Harmful Gases Comentioning

confidence: 99%

Charging and Discharging Strategies of Electric Vehicles: A Survey

El-Bayeh

Alzaareer

Aldaoudeyeh

et al. 2021

WEVJ

Self Cite

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“…This condition indicates that the transformer is experiencing accelerated aging and its lifetime is reduced. The equivalent of the aging acceleration factor and daily transformer percent loss of life over a time period of a day can be written, as in Equations (16) and (17), respectively.…”

Section: Transformer Aging Modelmentioning

confidence: 99%

“…Reference [15] presents the technical and economical optimization of EV charging in a parking garage with photovoltaic (PV) and battery energy storage system (BESS) considering the impact on transformer aging. Reference [16] discusses optimized EV charging in the parking lot where the critical power limit of the distribution transformer is modeled with the ambient temperature and the aging acceleration factors. In reference [17], the optimal strategies of the home energy management system with EV charging for minimizing the distribution transformer aging were shown.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost

et al. 2020

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Electric vehicles (EV) replacing the internal combustion engine vehicle may be the solution for the particulate matter (PM) 2.5 pollution issue. However, the uncontrolled charging of EVs would challenge the power system operation. Therefore, it is necessary to implement some level of control over the EV charging procedure, especially in the residential network. In this paper, an optimization of EVs charging scheduling considering energy arbitrage and the distribution network cost of an urban village environment is presented. The optimized strategy focuses on decreasing the loss of EV owners’ energy arbitrage benefit, introduced as the penalty cost. Also, peak demand, power loss, and transformer aging are included in the estimation of the cost function for the distribution network. The optimization problem is solved using the genetic algorithm. As a case study, data from the urban village in Udon Thani, Thailand, are utilized to demonstrate the applicability of the proposed method. Simulation results show a reduction in the loss of energy arbitrage benefit, transformer peak load, power loss and the transformer loss of life. Therefore, the application of the optimized EV charging can prolong transformer lifetime benefiting both the EV owner and the distribution system operator.

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“… Other ST data: nameplate rating (e.g., 100 kVA), normal insulation life (e.g., 25 years), GPS location, number of phases, etc. b. ST calculates the transformer's critical power limit ( ) as it is presented in [22].…”

Section: A Sensors In the St Collect Weather And Local Data: Omentioning

confidence: 99%

A Novel Data-Energy Management Algorithm for Smart Transformers to Optimize the Total Load Demand in Smart Homes

et al. 2020

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The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might be created, and other solutions are required. Many researchers tried to solve the problem; however, limitations exist because of the decentralized topology of the network. The system operator is not allowed to control the end-users’ load due to security and privacy issues. To overcome this situation, we propose a novel data-energy management algorithm on the transformer’s level that controls the power demand profiles of the householders and exchange energy between them without violating their privacy and security. Our method is compared to an existing one in the literature based on a decentralized control strategy. Simulations show that our approach has reduced the electricity cost of the end-users by 3%, increased the revenue of the system operator, and reduced techno-economic losses by 50% and 42%, respectively. Our strategy shows better performance even with a 100% penetration level of EVs on the network, in which it respects the network’s constraints and maintains the voltage within the recommended limits.

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Novel Approach for Optimizing the Transformer’s Critical Power Limit

Cited by 16 publications

References 28 publications

Charging and Discharging Strategies of Electric Vehicles: A Survey

Charging and Discharging Strategies of Electric Vehicles: A Survey

Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost

A Novel Data-Energy Management Algorithm for Smart Transformers to Optimize the Total Load Demand in Smart Homes

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