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
17 - Distributed Load Management
from Part V - Large-Scale Optimization
Published online by Cambridge University Press: 22 March 2021
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
Summary
This chapter focuses on distributed control and learning for electric vehicle charging. After a brief survey, it covers three related sets of algorithms: (i) distributed control for electric vehicle charging based on a basic formulation; (ii) distributed control for an extension of the basic setting to include network capacity constraints; and (iii) distributed learning for an extension of the basic setting with limitations in the information flow. The chapter ends with a brief summary of open problems.
- Type
- Chapter
- Information
- Advanced Data Analytics for Power Systems , pp. 431 - 454Publisher: Cambridge University PressPrint publication year: 2021