Model predictive control of distributed and aggregated Battery Energy Storage System for capacity optimization

Author

Khalid, Muhammad ; Savkin, Andrey V.

Author_Institution

Sch. of Electr. Eng. & Telecommun., Univ. of New South Wales, Sydney, NSW, Australia

fYear

2011

fDate

19-21 Dec. 2011

Firstpage

521

Lastpage

526

Abstract

This paper presents a methodology to optimize the capacity of a Battery Energy Storage System (BESS) in a distributed configuration of wind power sources. A new semi-distributed BESS scheme is proposed and the strategy is analyzed as a way of improving the suppression of the fluctuations in the wind farm power output. The model is tested for a similar wind power profile where the turbines are located at close geographic locations with similar geographic conditions. This power profile is also assessed under a variety of hard system constraints for both the proposed and conventional BESS configurations. It was proved that the performance of the proposed semi-distributed BESS scheme is better than that of conventional approaches, based on the results validated with real-world wind farm data.

Keywords

power control; predictive control; primary cells; wind power plants; battery energy storage system; capacity optimization; model predictive control; power output fluctuation suppression; semi-distributed BESS scheme; wind power source; Batteries; Power smoothing; Smoothing methods; Turbines; Wind farms; Wind power generation; Wind power; distributed battery energy storage; model predictive control;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation (ICCA), 2011 9th IEEE International Conference on

Conference_Location

Santiago

ISSN

1948-3449

Print_ISBN

978-1-4577-1475-7

Type

conf

DOI

10.1109/ICCA.2011.6137882

Filename

6137882