Prospective Analysis of Distribution Network Reconstruction on Electric Vehicles access to Demonstration District

Liu, Yujun; Xu, Qingshan; Chen, Kai; Xu, Xiaohui

doi:10.5755/j01.eee.19.6.4554

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…From [9], the capacity of fast storage devices such as metaloxide supercapacitors is quite limited and their cost is high, so we a should use them rationally to keep the system within certain levels of fast adjustment ability. In [10], different control methods of batteries on electrical vehicles and their effects on the distribution network were analyzed. In [11], reliability indices were utilized in distribution networks to evaluate the effect of DGs on microgrid stability.…”

Section: Introductionmentioning

confidence: 99%

A classification control strategy for energy storage system in microgrid

Zeng

Ding³

et al. 2015

IEEJ Transactions Elec Engng

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Storage devices are indispensable elements in a microgrid to compensate for the power imbalance between loads and the distributed generator (DG) output. Different storage strategies give diverse performances in adjustment speed and capacity. Based on the performance of different storage devices and the features of power imbalance curve in different periods, a classification control strategy is proposed in this paper. First, storage devices are given priorities according to the adjusting speed, and the power imbalance curve is divided into two periods according to the changing speed. During an emergency, all the storages are employed to compensate the rapidly increasing power imbalance; during the steady period, storage device with higher priority is employed to track the instantaneous component of power imbalance, while storage device with lower priority is used to replace the kWh output of higher priority storage. The proposed strategy is tested in a microgrid within the subdistribution network of IEEE RBTS Bus6 system using Monte Carlo methods. Simulation results indicate that the classification control strategy could endow the system with fast adjusting ability through coordination between storages. Reliability indices of the testing system are utilized to demonstrate that the classification control strategy could improve the stability of the microgrid and reliability of the distribution network. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Section: Introductionmentioning

confidence: 99%

A classification control strategy for energy storage system in microgrid

Zeng

Ding³

et al. 2015

IEEJ Transactions Elec Engng

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“…In recent years, electric vehicles (EVs) are developing rapidly in many countries [1]. Many automotive companies have introduced their new EV products.…”

Section: Introductionmentioning

confidence: 99%

Research on the Performance of Electric Vehicles in Peak Load Shifting

Liu

Ding³

et al. 2014

Journal of Applied Mathematics

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Electric vehicles (EVs) are developing remarkably fast these years which makes the technology of vehicle-to-grid (V2G) easier to implement. Peak load shifting (PLS) is an important part of V2G service. A model of EVs’ capacity in V2G service is proposed for the research on PLS in this paper. The capacity is valued in accordance with three types of situations. Based on the model, three different scenarios are suggested in order to evaluate the capacity with MATLAB. The evaluation results indicate that EVs can provide potential energy to participate in PLS. Then, the principle of PLS with EVs is researched through the analysis of the relationship between their power and capacity. The performance of EVs in PLS is also simulated. The comparison of two simulation results shows that EVs can fulfill the request of PLS without intensely lowering their capacity level.

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Research on the evaluation method of capacity on electric-vehicle energy storage system

Liu

Zang

et al. 2014

2014 IEEE International Workshop on Intelligent Energy Systems (IWIES)

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With accelerated rollout of plug-in electric vehicles (EVs), large-scale EVs could constitute an energy storage system, called electric-vehicle energy storage system (EVESS). It is essential to evaluate how much power can be exchanged between EVESS and the grid. Charging capacity (CLC) and discharging capacity (CLD) are defined as two major properties of EVESS in this paper. Then, evaluation models of CLC and CLD are proposed in a probabilistic manner. Based on the connecting probability of EVs, three different scenarios are developed to evaluate CLC and CLD. The results indicate that the EVESS is sensitive to the charging strategy and capable of providing certain amount of capacity for energy exchange with the grid which shows its potential of participating in vehicle-to-grid services.

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Prospective Analysis of Distribution Network Reconstruction on Electric Vehicles access to Demonstration District

Cited by 3 publications

References 16 publications

A classification control strategy for energy storage system in microgrid

A classification control strategy for energy storage system in microgrid

Research on the Performance of Electric Vehicles in Peak Load Shifting

Research on the evaluation method of capacity on electric-vehicle energy storage system

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