Abstract
The reliable performance of the smart grid is a function of the configuration and cyber–physical nature of its constituting sub-systems. Therefore, the ability to capture the interactions between its cyber and physical domains is necessary to understand the effect that each one has on the other. As such, the work in this paper presents a co-simulation platform that formalizes the understanding of cyber information flow and the dynamic behavior of physical systems, and captures the interactions between them in smart grid applications. Power system simulation software packages, embedded microcontrollers, and a real communication infrastructure are combined together to provide a cohesive smart grid cyber–physical platform. A data-centric communication scheme, with automatic network discovery, was selected to provide an interoperability layer between multi-vendor devices and software packages, and to bridge different protocols. The effectiveness of the proposed framework was verified in three case studies: (1) hierarchical control of electric vehicles charging in microgrids, (2) International Electrotechnical Committee (IEC) 61850 protocol emulation for protection of active distribution networks, and (3) resiliency enhancement against fake data injection attacks. The results showed that the co-simulation platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the smart grid, as they were experimentally verified, down to the packet, over a real communication network.
Highlights
Today, the reliable operation of the smart grid is mainly based on the cyber–physical nature of its components and their configuration
Data Distribution Service (DDS) supports automatic network discovery and has a rich set of quality of service (QoS) profiles which are configured depending on the applications’ needs [13,14,15]. Another reason for choosing the DDS as a common data bus for the developed platform is that it has an application programing interface (API) that facilitates mapping of other industrial protocols such as Common Information Model (CIM), International Electrotechnical Committee (IEC) 61850 Generic Object Oriented Substation Event (GOOSE) messages and sampled measured values (SMV) messages into DDS, as will be explained later
0.56 were simulated on MATLAB/Simulink SimPowerSystems to model the physical system dynamics, whereas all control logic was implemented on embedded microcontrollers communicating over a
Summary
The reliable operation of the smart grid is mainly based on the cyber–physical nature of its components and their configuration. The aforementioned research denotes a significant step to achieve proper modeling techniques for the physical and cyber domains of cyber–physical systems These schemes are not being deployed over an actual communication network. For the research conducted in [8], phasor measurement units were connected to a real time digital simulator through an IEC 61850 bus for passive islanding schemes modeling The former implementations have two main drawbacks, they are application specific, and it is difficult to scale up the system and deal with the complicated communication requirements for the other applications of the smart grid. Protocol integration is based on a proprietary distributed test manager; it cannot be scaled and special libraries are required to interface with it Both approaches for modeling are single sided and do not offer a complete framework to properly model cyber–physical systems and their interactions.
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