شارژ باتری شبکه از وسایل نقلیه الکتریکی
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شارژ باتری شبکه از وسایل نقلیه الکتریکی

عنوان فارسی مقاله: شارژ باتری شبکه از وسایل نقلیه الکتریکی
عنوان انگلیسی مقاله: Network security-aware charging of electric vehicles
مجله/کنفرانس: سیستم های قدرت و انرژی الکتریکی – Electrical Power and Energy Systems
رشته های تحصیلی مرتبط: مهندسی برق
گرایش های تحصیلی مرتبط: الکترونیک، سیستم های قدرت
کلمات کلیدی فارسی: وسایل نقلیه الکتریکی، شارژ بهینه، امنیت سیستم قدرت، آرامش لاگرانژی، تجزیه Benders
کلمات کلیدی انگلیسی: Electric vehicles, Optimal charging, Power system security, Lagrangian Relaxation, Benders decomposition
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journal List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.ijepes.2018.02.002
دانشگاه: Department of Electrical Engineering – Harbin Institute of Technology – China
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 4.574 در سال 2017
شاخص H_index: 88 در سال 2019
شاخص SJR: 1.276 در سال 2017
شناسه ISSN: 0142-0615
شاخص Quartile (چارک): Q1 در سال 2017
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 8
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
کد محصول: E7855
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Problem formulation


3- Solution approach


4- Case studies


5- Conclusion


Acknowledgement


References

نمونه متن انگلیسی مقاله

Abstract


Large-scale integration of electric vehicles (EV) and wind power could have significantly negative impacts on power systems security. So, it is becoming an increasingly important issue to develop an effective network security-aware charging strategy of EVs. This paper proposes a multi-objective formulation for the optimal charging schedule of EVs while considering N − 1 security constraints. An EV aggregator representing a cluster of controllable EVs is modeled for determining the optimal charging schedule based on a trilevel hierarchy. On the top level, the grid control center determines the EV charging strategy from the proposed formulation, where bus voltage fluctuations, network power losses, and EV charging adjustments are considered as multi-objective functions. To reduce the computational burden, Lagrangian Relaxation (LR) is introduced to handle time coupled constraints and Benders Decomposition is introduced to handle contingencies. Case studies have been conducted on the New England 39-bus system, and the results verify the necessity of considering N − 1 security constraints and the effectiveness of the proposed formulation and solution approach.


Introduction


Electric vehicles (EVs) have been receiving considerable attentions worldwide as they are clean and green. However, the large-scale integration of EVs, without coordination, may bring negative impacts on power systems operation, such as lower voltage quality, larger power losses, and more harmonics [1]. Therefore, effective strategies should be developed to schedule the charging of EVs to mitigate the negative impacts and even benefit the grid [2]. In the literatures, studies about EV charging schedule are concentrated on distribution network. Up to now, only a few literatures discussed the charging issues of EVs from the transmission network viewpoint. Ref. [3] presented a bi-level model for coordinating the charging/discharging schedules of EVs. The upper-level model minimizes the system load variance to implement peak load shifting by dispatching each aggregator, and the lower one traces the dispatching scheme determined by the upper-level decision-maker by figuring out an appropriate charging/discharging schedules throughout a specific day. Ref. [4] proposed a multi-objective non-linear mixed integer optimization model for EV charging scheduling considering the uncertainties of photovoltaic and wind power in regional power grids. The fuzzy theory was used to change the multi-objective optimization model into a single-objective non-linear optimization problem.

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