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Research on Energy Storage Economic Allocation of Photovoltaicand Energy-Storage Integrated Charging StationConsidering Load Optimization(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2021年02期
Page:
15-21
Research Field:
电气工程
Publishing date:

Info

Title:
Research on Energy Storage Economic Allocation of Photovoltaicand Energy-Storage Integrated Charging StationConsidering Load Optimization
Author(s):
Xu Qiang; Wang Wei; Ji Tongzhou; Xu Yanwei
NARI School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210023,China
Keywords:
energy storage allocation; peak valley electricity price; energy storage operation strategy; bi-level programming model; load optimization
PACS:
TM76
DOI:
10.3969/j.issn.1672-1292.2021.02.003
Abstract:
In order to cushion the blows of electric vehicles charging on the power grid and improve the economy of charging station,the energy storage configuration of photovoltaic and energy-storage integrated charging station is studied. Firstly,this paper analyzes the load characteristics of electric vehicles in charging station,and the energy storage operation strategy is formulated on the basis of the peak valley electricity price. Then,a bi-level programming model of energy storage configuration is established to ensure the maximum optimization of charging station load and realize price arbitrage. Finally,through the analysis of an example,the energy storage economic configuration scheme of charging station in commercial district is obtained. Compared with the traditional energy storage configuration scheme with peak valley difference as the optimization index,the results show that the proposed scheme effectively increases the total peak load shifting amount and further reduces the annual power purchase cost of the charging station.

References:

[1] DHARMAKEERTHI C H,MITHULANANTHAN N,SAHA T K. Impact of electric vehicle fast charging on power system voltage stability[J]. International Journal of Electric Power and Energy Systems,2014,57:241-249.
[2]SINGH J,TIWARI R. Impact analysis of different charging models for optimal integration of plug-in electric vehicles in distribution system[J]. The Journal of Engineering,2019,18:4728-4733.
[3]修晓青,李建林,惠东. 用于电网削峰填谷的储能系统容量配置及经济性评估[J]. 电力建设,2013,34(2):1-5.
[4]DENG J X,SHI J,LIU Y,et al. Application of a hybrid energy storage system in the fast charging station of electric vehicles[J]. IET Generation Transmission & Distribution,2016,10(4):1092-1097.
[5]孙玉树,唐西胜,孙晓哲,等. 风电波动平抑的储能容量配置方法研究[J]. 中国电机工程学报,2017,37(增刊1):88-97.
[6]XU Y X,SINGH C. Power system reliability impact of energy storage integration with intelligent operation strategy[J]. IEEE Transactions on Smart Grid,2014,5(2):1129-1137.
[7]DING H J,HU Z C,SONG Y H. Value of the energy storage system in an electric bus fast charging station[J]. Applied Energy,2014,157:630-639.
[8]李文超,童亦斌,张维戈. 计及电池使用寿命的电动汽车充电站储能容量配置方法[J]. 电工电能新技术,2019,39(4):55-63.
[9]方超明,张宇,王育飞,等. 基于排队理论的储能式快充站容量优化配置[J]. 现代电力,2017,34(2):62-66.
[10]吕跃春,汪会财,李志勇,等. 电动汽车充储放电站储能系统容量配置方法[J]. 电力系统及其自动化学报,2017,29(11):133-137.
[11]何阳,张宇,王育飞,等. 考虑负荷优化的电动汽车光伏充电站储能容量配置[J]. 现代电力,2018,36(5):76-81.
[12]段雪. 考虑电动汽车规模化接入的配电网承载能力的研究[D]. 成都:电子科技大学,2019.
[13]周楠,樊玮,刘念,等. 基于需求响应的光伏微网储能系统多目标容量优化配置[J]. 电网技术,2016,40(6):1709-1716.
[14]吴杰,温晨阳,李珊,等. 基于分时电价的光伏—储能系统容量优化配置[J]. 电工电能新技术,2018,37(1):23-30.
[15]谢桦,滕晓斐,张艳杰,等. 风/光/储微网规划经济性影响因素分析[J]. 电力系统自动化,2019,43(6):70-82,115.

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Last Update: 2021-06-30