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Title: Energy Management and Optimization Methods for Grid Energy Storage Systems

Abstract

Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.

Authors:
ORCiD logo; ; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1429960
Alternate Identifier(s):
OSTI ID: 1429962; OSTI ID: 1441476
Report Number(s):
SAND-2018-2962J
Journal ID: ISSN 2169-3536; 8016321
Grant/Contract Number:  
AC04-94AL85000; NA0003525
Resource Type:
Published Article
Journal Name:
IEEE Access
Additional Journal Information:
Journal Name: IEEE Access Journal Volume: 6; Journal ID: ISSN 2169-3536
Publisher:
Institute of Electrical and Electronics Engineers
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; 29 ENERGY PLANNING, POLICY, AND ECONOMY

Citation Formats

Byrne, Raymond H., Nguyen, Tu A., Copp, David A., Chalamala, Babu R., and Gyuk, Imre. Energy Management and Optimization Methods for Grid Energy Storage Systems. United States: N. p., 2018. Web. https://doi.org/10.1109/ACCESS.2017.2741578.
Byrne, Raymond H., Nguyen, Tu A., Copp, David A., Chalamala, Babu R., & Gyuk, Imre. Energy Management and Optimization Methods for Grid Energy Storage Systems. United States. https://doi.org/10.1109/ACCESS.2017.2741578
Byrne, Raymond H., Nguyen, Tu A., Copp, David A., Chalamala, Babu R., and Gyuk, Imre. Mon . "Energy Management and Optimization Methods for Grid Energy Storage Systems". United States. https://doi.org/10.1109/ACCESS.2017.2741578.
@article{osti_1429960,
title = {Energy Management and Optimization Methods for Grid Energy Storage Systems},
author = {Byrne, Raymond H. and Nguyen, Tu A. and Copp, David A. and Chalamala, Babu R. and Gyuk, Imre},
abstractNote = {Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.},
doi = {10.1109/ACCESS.2017.2741578},
journal = {IEEE Access},
number = ,
volume = 6,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1109/ACCESS.2017.2741578

Citation Metrics:
Cited by: 10 works
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