A Hardware-in-the-Loop Based Co-Simulation Platform of Cyber-Physical Power Systems for Wide Area Protection Applications

Abstract

Abstract:With the development of smart grid technology, there has been an increasingly strong tendency towards the integration between the aspects of power and communication. The traditional power system has gradually transformed into the cyber-physical power system (CPPS), where co-simulation technologies can be utilized as an effective measure to describe the computation, communication, and integration processes of a power grid. In this paper, the construction methods and application scenarios of co-simulation platforms in the current research are first summarized. Then, a scheme of the real-time hardware-in-the-loop co-simulation platform is put forward. On the basis of power grid simulation developed with the Real-Time Laboratory (RT-LAB), and the communication network simulation developed with OPNET, the control center was developed with hardware devices to realize real-world control behavior instead of digital simulations. Therefore, the mixed-signal platform is capable of precisely simulating the dynamic features of CPPS with high speed. The distributed simulation components can be coordinated in a unified environment with high interoperability and reusability. Moreover, through a case study of a wide area load control system, the performance of the proposed platform under various conditions of control strategies, communication environments, and sampling frequencies was revealed and compared. As a result, the platform provided an intuitive and accurate way to reconstruct the CPPS environment where the influence of the information side of the CPPS control effects was verified.

Combining PDEVS and Modelica for describing agent-based models

“…A third approach is based in the application of co-simulation, [58][59][60][61] where multiple tools with different functionalities are combined to represent the final system. [62][63][64][65] These approaches present the following respective limitations: offering limited support for describing continuoustime equations by only using explicit ODE; requiring manual anipulations of the model equations to discretize them to apply any numerical integration approach for the simulation; and requiring to use a combination of different tools to describe the whole system, that usually involves learning how to use different tools, different modeling approaches, additional programming skills, and so on. The Modelica language represents the state-of-the art in equation-based modeling of continuous-time systems.…”

“…A third approach is based in the application of co-simulation, 58–61 where multiple tools with different functionalities are combined to represent the final system. 62–65…”

Real‐time cyber−physical system co‐simulation testbed for microgrids control

“…The time interval Δ t between a synchronisation time point and the corresponding event trigger point is called interaction latency containing two parts of time, which are communication latency and inherent latency respectively, as shown below: where t cl is the communication latency existed in the simulation of the actual network communication process through the OPNET simulation system, which is the main part of Δ t and determined by the communication scenario; t il is the inherent latency caused by physical factors during the data transmission between the two simulation systems, which is inescapable in the interaction interface. The average of the inherent latency t il is ∼0.588 ms [28], which is much smaller than the communication latency t cl . Therefore, the inherent latency t il has a negligible effect on the simulation accuracy.…”

Coordinated Defense of Distributed Denial of Service Attacks against the Multi-Area Load Frequency Control Services

“…The control center generates commands according to the control algorithm in order to realize the situation awareness and optimal control of the power grid. The flow process of data can be summarized as collection, uploading, processing, downloading, and execution [29].…”

“…The control master station is the bridge that implements the control logic and time synchronization between both simulators. Based on this, cyber-attack behavior can be realized in OPNET, and detection and recovery strategies can be generated in the control station and be fed back to OPNET and RT-LAB [29]. Therefore, the attack-defense simulation can be achieved.…”