[1]段俊东,付子恒,张普胜,等.平滑含DG配网功率波动的储能容量优化研究[J].郑州大学学报(工学版),2020,41(05):50-54.[doi:10.13705/j.issn.1671-6833.2020.03.011]
　DUAN Jundong,FU Ziheng,ZHANG Pusheng,et al.Optimized Study of Energy Storage Systems Capacity for Power Smoothing of Distribution Containing DG[J].Journal of Zhengzhou University (Engineering Science),2020,41(05):50-54.[doi:10.13705/j.issn.1671-6833.2020.03.011]
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平滑含DG配网功率波动的储能容量优化研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
41卷
期数:
2020年05期
页码:
50-54
栏目:
出版日期:
2020-10-01

文章信息/Info

Title:
Optimized Study of Energy Storage Systems Capacity for Power Smoothing of Distribution Containing DG
作者:
段俊东; 付子恒; 张普胜; 张永辉
河南理工大学电气学院,河南焦作454000, 国网河南省电力公司焦作供电公司,河南焦作454000

Author(s):
DUAN Jundong1;  FU Ziheng1;  ZHANG Pusheng2;  ZHANG Yonghui2
1.School of Electrical Engineering, Henan Polytechnic University, Jiaozuo 454000, China; 2.State Grid Henan Electric Power Company Jiaozuo Power Supply Company, Jiaozuo 454000, China
关键词:
Keywords:
energy storage system;  peak load shifting;  smoothing power;  capacity optimization
DOI:
10.13705/j.issn.1671-6833.2020.03.011
文献标志码:
A
摘要:
风电、光伏等分布式电源(distributed generation,DG)并网后,其间歇性、不稳定性与用电负荷的周期性、季节性相结合会加剧电网的功率波动。为抑制由DG并网造成的功率波动,研究了用于平滑功率波.动的储能系统(energy storage system, ESS)容量优化办法。利用经验模态分解(empirical mode decomposition, EMD)的方法,对含DG的配网功率样本进行EMD处理。基于分解结果,考虑ESS运行效率及荷电状态的约束,确定所需的ESS最小容量。算例表明:该方法可使含DG配网功率的波动明显降低，其中按曲线3配置的ESS可使含DG的配网功率在30min内最大波动率由53.46%降低至24.67%,且系统可正常稳定地运行,同时也具有一定的“削峰填谷”作用,减小电力系统“调峰”压力。
Abstract:
In DG, such as wind power generation or photovoltaic power generation being connected to the grid, the intermittence and instability of power generation and the periodicity and seasonality of the electric load would aggravate the power fluctuation of the distribution network, which could consequently destroy the power stability of the main power grid. In order to reduce DG power fluctuations on the distribution network, a capacity determination method of ESS was examined. The EMD method was used to decompose the distribution network which contained the DG power output samples. Based on the results, considering the ESS charge-discharge efficiency and the state of charge (SOC) constraints, the minimum ESS energy capacity was determined. Numerical outcomes proved that the capacity determination method of ESS could reduce the power volatility of the distribution network containing DG significantly. The example showed that the ESS which was configured as curve 3 could reduce the power volatility from 53.46% to 24.67% in 30 minutes, while keeping the system stable. Moreover, it had some peak load shifting effect which could lower the pressure of peak shaving of the electric power system.

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更新日期/Last Update: 2020-10-23