Extraction of Typical Duty Cycle Curves of Energy Storage Battery Based on Time-series Correlation and Clustering Method

被引：0

作者：

Yang S. ^{[1
]}

Hou C. ^{[1
]}

Xu S. ^{[1
]}

Zhao L. ^{[1
]}

Sun B. ^{[2
]}

Chen J. ^{[1
]}

机构：

[1] National Key Laboratory on Operation and Control of Renewable Energy and Energy Storage, China Electric Power Research Institute, Beijing

[2] School of Electrical and Electronic Engineering, North China Electric Power University, Beijing

来源：

Yang, Shuili (yangsl@epri.sgcc.cn) | 2018年 / Automation of Electric Power Systems Press卷 / 42期

基金：

中国国家自然科学基金;

关键词：

Clustering method; Duty cycle curve; Energy storage battery; Time-series correlation;

D O I：

10.7500/AEPS20170905006

中图分类号：

学科分类号：

摘要：

Extensive concern has arisen on how to evaluate and test the actual working characteristics of energy storage battery, while no authoritative method gets established yet. Based on several duty cycle of battery under the typical application scenarios, this paper studies the eigenfactors and static configurations with different confidence coefficients while neglecting the time-series correlation. Then a method of extracting typical duty cycle curves of battery based on the time-series correlation analysis and the clustering method is proposed. The periodic variational regularity, operating modes, and mode exchanging orders and frequency of energy storage battery output when operating are analyzed, and the operation track of state of charge (SOC) of battery is described. The duty cycle curves, which can control and evaluate the energy storage battery output in the real-time and SOC of battery, are extracted. Finally, taken the application of a battery energy storage system tracking the planed wind power output of a certain wind farm as an example, the effectiveness and feasibility of the proposed method is verified. © 2018 Automation of Electric Power Systems Press.

引用

页码：188 / 194

页数：6

共 14 条

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