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.
| Original language | English |
|---|---|
| Title of host publication | 2011 9th IEEE International Conference on Control and Automation, ICCA 2011 |
| Pages | 521-526 |
| Number of pages | 6 |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
Publication series
| Name | IEEE International Conference on Control and Automation, ICCA |
|---|---|
| ISSN (Print) | 1948-3449 |
| ISSN (Electronic) | 1948-3457 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Wind power
- distributed battery energy storage
- model predictive control
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering
Fingerprint
Dive into the research topics of 'Model predictive control of distributed and aggregated Battery Energy Storage System for capacity optimization'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver