This chapter reviews the traditional power systems control structure and discusses how it could evolve to incorporate all the new controllable devices which will be available in the future, as well as cope with the potential difficulties these may create. Given the scale of these problems, we place particular emphasis on distributed solutions. We provide an overview of relevant approaches and put them into perspective with regards to when and how they could be applied. Rather than a rigorous mathematical treatment of the presented methods, we use simple, indicative, power system based formulations and examples to illustrate how they work, establish similarities between them, and identify the challenges - both in mathematics and implementation - that still lie ahead. For the reader interested in mathematical proofs or extended results regarding a particular method, we provide an adequate number of relevant bibliographic references.

Chapter Contents:

• 6.1 Introduction
• 6.2 A look into current power systems control
• 6.3 Identifying the role of distributed methods
• 6.4 Distributed optimization definitions and scope
• 6.4.1 Distributed optimization fundamentals
• 6.4.2 Simple price-based decomposition
• 6.4.3 From optimization to control using prices
• 6.4.4 Making prices work
• 6.5 Decomposition methods
• 6.5.1 Improving price-updates
• 6.5.2 Decomposing an augmented Lagrangian
• 6.5.3 Proximal decomposition methods
• 6.5.4 Optimality Condition Decomposition
• 6.5.5 On other distributed methods
• 6.6 OPF insights
• 6.6.1 Decomposition structure considerations
• 6.6.2 Practical application considerations
• 6.7 The UC time frame
• 6.8 The ED time frame
• 6.9 Closer to real time
• 6.10 Conclusions
• Bibliography

Inspec keywords: power system control

Other keywords: decentralized control; mathematical treatment; power system control structure; distributed control

Subjects: Control of electric power systems; Power system control