Abstract
This paper presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the data-centric over message-centric communication approach are discussed in the context of smart grid applications. The data distribution service (DDS) is used to implement a data-centric common data bus for the smart grid. This common data bus improves the communication reliability, enabling distributed control and smart load management. These enhancements are achieved by avoiding a single point of failure while enabling peer-to-peer communication and an automatic discovery feature for dynamic participating nodes. The infrastructure and ideas presented in this paper were implemented and tested on the smart grid testbed. A toolbox and application programing interface for the testbed infrastructure are developed in order to facilitate interoperability and remote access to the testbed. This interface allows control, monitoring, and performing of experiments remotely. Furthermore, it could be used to integrate multidisciplinary testbeds to study complex cyber-physical systems (CPS).
Highlights
The future utility grid will be characterized by tight integration between power electronics, sensing, protection, control, communications technologies, and distributed energy resources (DER)
In order to show the capabilities of the developed framework, three experiments were carried out with different operation scenarios and scales
The developed infrastructure provides the capability of integrating different types of systems and components inside the testbed and connecting several testbeds to study the behavior of complex cyber-physical systems (CPS)
Summary
The future utility grid will be characterized by tight integration between power electronics, sensing, protection, control, communications technologies, and distributed energy resources (DER). A communication infrastructure needs to be designed to provide a more efficient and flexible way to manage the energy flow keeping interoperability in mind [2,3]. On one hand, this type of integration can dramatically improve the grid performance and efficiency, but on the other, it can introduce new types of vulnerabilities to the grid [4] complicating system analysis and the design process [5]. A hardware/software-based smart grid [6]
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