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
16 - Distributed Optimization for Power and Energy Systems
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 electric power system is evolving toward a massively distributed infrastructure with millions of controllable nodes. Its future operational landscape will be markedly different from existing operations, in which power generation is concentrated at a few large fossil-fuel power plants, use of renewable generation and storage is relatively rare, and loads typically operate in open-loop fashion. This chapter provides an overview of the technical developments that aim to leverage advances in optimization and control to develop distributed control frameworks for next-generation power systems that ensure stability, preserve reliability, and meet economic objectives and customer preferences.
- Type
- Chapter
- Information
- Advanced Data Analytics for Power Systems , pp. 400 - 430Publisher: Cambridge University PressPrint publication year: 2021