Dual-Consensus-Based Distributed Frequency Control for Multiple Energy Storage Systems

被引：46

作者：

Xing, Lantao ^{[1
]}

Mishra, Yateendra ^{[1
]}

Tian, Yu-Chu ^{[1
]}

Ledwich, Gerard ^{[1
]}

Su, Hongye ^{[2
]}

Peng, Chen ^{[3
]}

Fei, Minrui ^{[3
]}

机构：

[1] Queensland Univ Technol, Sch Elect Engn & Comp Sci, Brisbane, Qld 4001, Australia

[2] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China

[3] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

来源：

IEEE TRANSACTIONS ON SMART GRID | 2019年 / 10卷 / 06期

基金：

中国国家自然科学基金; 澳大利亚研究理事会;

关键词：

Frequency control; distributed control; battery energy storage systems (BESSs); state-of-charge; consensus; DROOP CONTROL;

D O I：

10.1109/TSG.2019.2904075

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Intermittent renewable energy sources are being increasingly integrated into modern power networks. This leads to severe frequency fluctuations in the networks. Energy storage systems can be used for frequency restoration due to their capability to provide in-time active power compensations. This paper examines the frequency control problem for power systems with multiple distributed battery energy storage systems (BESSs). A dual-consensus-based approach is presented for distributed frequency control. It consists of three main components: 1) tuning of the BESS control gain; 2) design of control signals as inputs to BESSs for proportional use of the preserved energy; and 3) estimation of BESS parameters for control implementation. A static parameter and a time-varying parameter are defined, and their average values are estimated through static average consensus (SAC) and dynamic average consensus (DAC) algorithms, respectively. Case studies are conducted to demonstrate our dual-consensus control approach.

引用

页码：6396 / 6403

页数：8

共 28 条

[1]

Aditya SK, 1999, INT J ENERG RES, V23, P247, DOI 10.1002/(SICI)1099-114X(19990310)23:3<247::AID-ER480>3.0.CO

[2]

2-T

[3]

[Anonymous], 2006, 45 IEEECONF DECISION, DOI [10.1109/CDC.2006.377078., DOI 10.1109/CDC.2006.377078]

[4]

[Anonymous], 2017, P 52 INT U POW ENG C, DOI DOI 10.1109/UPEC.2017.8231914

[5]

[Anonymous], 2017, National Electricity Transmission System Security and Quality of Supply Standard Version 2.3

[6] Distributed Control Scheme for Package-Level State-of-Charge Balancing of Grid-Connected Battery Energy Storage System [J].

Cai, He ;

Hu, Guoqiang .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (05) :1919-1929

[7] Penetration Rate and Effectiveness Studies of Aggregated BESS for Frequency Regulation [J].

Chen, Shuaixun ;

Zhang, Tian ;

Gooi, H. B. ;

Masiello, Ralph D. ;

Katzenstein, Warren .

IEEE TRANSACTIONS ON SMART GRID, 2016, 7 (01) :167-177

[8] Incorporating Short-Term Stored Energy Resource Into Midwest ISO Energy and Ancillary Service Market [J].

Chen, Yonghong ;

Keyser, Marc ;

Tackett, Matthew H. ;

Ma, Xingwang .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (02) :829-838

[9] Dynamic Available AGC Based Approach for Enhancing Utility Scale Energy Storage Performance [J].

Cheng, Yunzhi ;

Tabrizi, Mehriar ;

Sahni, Mandhir ;

Povedano, Alfredo ;

Nichols, David .

IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (02) :1070-1078

[10] Frequency response services designed for energy storage [J].

Greenwood, D. M. ;

Lim, K. Y. ;

Patsios, C. ;

Lyons, P. F. ;

Lim, Y. S. ;

Taylor, P. C. .

APPLIED ENERGY, 2017, 203 :115-127

← 1 2 3 →