Advanced Metering Infrastructure for Electric Vehicle Charging

Lam, Lun Ka; Ko, King-Tim; Tung, Hoi Yan; Tung, Hoi Ching; Lee, Wah Ching; Tsang, Kim Fung; Lai, Loi Lei

doi:10.4236/sgre.2011.24036

Cited by 18 publications

(7 citation statements)

References 10 publications

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“…These communication technologies can be wireless or over PLC that provides bidirectional communication between the network components. In [21], AMI is employed for the EV charging system, which its efficiency in charging schedule scenarios and dynamic pricing are investigated and they concluded that AMI could reduce energy consumption in peak‐load periods by 36%. In other words, AMI shifts 54% of the peak‐load energy demand to the off‐peak periods and reduce the pressure on the power grid during peak‐load demand periods.…”

Section: Proposed System Topologymentioning

confidence: 99%

“…Shao et al [20] proposed a charging control framework for a large number of EVs based on Benders decomposition to minimise operation cost without considering any CO 2 emission factors. In [21], Lam et al report the development of an advanced metering infrastructure (AMI) as an effective tool to reshape the load profile of EV charging by adopting appropriate demand-side management strategy. This paper solely focuses on power line communication (PLC) and demand response and ignores the optimisation of charging or discharging scheduling and stochastic behaviour of EV owners and different types of their EVs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units

Tashviri

Ghaffarzadeh

2020

IET Electrical Systems in Transportation

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Nowadays, running out of fossil fuels and more attention to reduce environmental pollutions are essential factors for the growing use of electric vehicles (EVs). Owing to these factors, it is important to present a method, which schedules charging or discharging of EVs and simultaneously considers economic and environmental aspects of the problem. This study proposes a multi-objective optimisation programme for charging or discharging of EVs in a smart distribution system by taking advantage of advanced metering infrastructure and uses a ɛ-constraint method for minimising operational costs and (CO 2) emissions. Simulating stochastic patterns of EV owner driving behaviour as well as considering different models and types of EVs with the help of trip planning algorithm are the main advantages of this study. Investigating the multi-objective problem in two cases shows the effectiveness and flexibility of this algorithm in real cases. Besides, vehicle-to-grid capability of EVs was also considered. This method was tested on a 33-bus distribution test system for over 24 h. As the results show, the total amount of scheduled power, the peak-to-valley difference of daily load, transmission power loss, CO 2 emission, and the total operational cost are reduced by the trip planning programme and EV owner revenue is increased.

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Section: Proposed System Topologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units

Tashviri

Ghaffarzadeh

2020

IET Electrical Systems in Transportation

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“…According to [6], in most of the cases, the distribution grid transfers energy without any kind of control mechanism. In a study done by [3] it was proposed an Advanced Metering Infrastructure (AMI), where it is possible to introduce a charging schedule system to advice the charging mode to avoid the peak consumption. The objective is to reduce the peak consumption, to relocate the EV energy demand to "off peak" consumption and to reshape the load profile.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The rapid growth of electric vehicle, associate with less autonomy, impacts definitely in increases of energy demand. The extra energy, demand of EV, can cause the distribution circuit congestion and affects the power quality [3]. However, before to think about the increase and quality of energy, it is necessary to investigate the impact on power system.…”

Section: Introductionmentioning

confidence: 99%

Residential Load Curve Analysis during Electric Vehicle Charging

Cortezzi¹,

Jota²

2017

JPEE

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With the objective to reduce the environmental pollution, alternative initiatives have favored the evolution of the electric vehicle (EV). As the electric vehicle depends solely on battery, the grid electric power is need for charging it. This new electric load can cause concern due to the impact of consume on power system. The behavior of main electric parameters is analyzed during the recharge of EV considering an actual condition of diary charge. In sequence, the data of these electric parameters obtained during EV charging were included on residential consumer energy from Brazil. The results contribute to the understanding of the recharge of EV in different time of the day which can affect the curve of residential consumer energy and consequently will affect in different way on Power System.

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“…Such a distributed structure is comprehensive and worth considering. In addition, the establishment of a reliable communication network can also facilitate transactions between EVs [29,30].…”

Section: Introductionmentioning

confidence: 99%

A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations

Huang

Lai

et al. 2021

Electronics

Self Cite

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This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be conducted by the charging system operator, to meet both personal interests and social benefits. After clearing the trading result, the charging system operator uploads the trading contract made in the day-ahead market to the blockchain. In the real-time market, the charging system operator checks the trading status and submits the updated trading results to the blockchain. This mechanism encourages participants in the double auction to pursue higher interests, in addition to rationally utilize the energy unmatched in the auction and to achieve the improvement of social welfare. Case studies are used to demonstrate the effectiveness of the proposed model. For buyers and sellers who successfully participate in the day-ahead market, the total profit increase for buyer and seller are 22.79% and 53.54%, respectively, as compared to without energy trading. With consideration of social welfare in the smart match mechanism, the peak load reduces from 182 to 146.5 kW, which is a 19.5% improvement.

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Advanced Metering Infrastructure for Electric Vehicle Charging

Cited by 18 publications

References 10 publications

Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units

Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units

Residential Load Curve Analysis during Electric Vehicle Charging

A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations

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