Book contents
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- 15 Uncertainty-Aware Power Systems Operation
- 16 Distributed Optimization for Power and Energy Systems
- 17 Distributed Load Management
- 18 Analytical Models for Emerging Energy Storage Applications
- Part VI Game Theory
- Index
18 - Analytical Models for Emerging Energy Storage Applications
from Part V - Large-Scale Optimization
Published online by Cambridge University Press: 22 March 2021
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- 15 Uncertainty-Aware Power Systems Operation
- 16 Distributed Optimization for Power and Energy Systems
- 17 Distributed Load Management
- 18 Analytical Models for Emerging Energy Storage Applications
- Part VI Game Theory
- Index
Summary
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. This chapter provides a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. Subsequently, EMS optimization methods and designs are discussed.
- Type
- Chapter
- Information
- Advanced Data Analytics for Power Systems , pp. 455 - 480Publisher: Cambridge University PressPrint publication year: 2021