Cyber-Physical Co-Simulation of Shipboard Integrated Power System Based on Optimized Event-Driven Synchronization

Abstract

As the energy management system (EMS) participates in the closed-loop control of shipboard integrated power system (IPS), the information network of EMS is closely coupled with the power system and its characteristics affect power system performance significantly. To study the close-coupling relationship between the two systems, a cyber–physical co-simulation platform based on the high level architecture (HLA) framework is constructed in this paper. The proposed platform uses PSCAD and OPNET to simulate shipboard power system and information network respectively, and utilizes OPNET HLA nodes and PSCAD user-defined modules to implement co-simulation interfaces. In order to achieve a higher co-simulation precision without impairing efficiency, an optimized event-driven co-simulation synchronization method is also proposed. By pre-defining power system synchronization points and detecting information network synchronization points in the co-simulation process, both systems can be synchronized in time and the synchronization error is eliminated. Furthermore, the co-simulation efficiency is also improved by optimizing the data transmission in the synchronization process. A co-simulation model of shipboard power distribution network protection based on CAN bus communication is built and analyzed. Simulation results show that the proposed co-simulation platform and synchronization method are feasible and effective.

Enabling Parallelized-QEMU for Hardware/Software Co-Simulation Virtual Platforms

“…These test results are shown in Figure 8, using a logarithmic scale for all the axes. As it can be observed in Figure 8a, the number of synchronizations can be controlled by the icountMax and Th parameters, as indicated by Equation (2). It can be seen that the number of synchronizations shoots up exponentially as Th t and icountMax parameters are diminished.…”

“…To reduce this difficulty, virtual platforms are presented as a perfect solution for evaluating whole systems and analyzing hardware/software proposals before their implementation stage. These virtual platforms use hardware/software co-simulation techniques profusely described in the literature [2][3][4]. In those, the software and hardware designs are combined at different levels of abstraction and with different timing accuracy.…”

“…Furthermore, the modification applied in our solution does not introduce a substantial overhead (less than 10%) when running ParMiBench applications. Figure 11 shows the instructions and synchronizations executed by each vCPU in the first 100 seconds (wallclock) of the Linux boot in Setup#3, and it reflects the behavior described by Equation (2). In Zynq, CPU#0 behaves as the Master CPU; hence, vCPU#0 is the first to boot the system and later wakes up vCPU#1.…”

A Cascading Failure Model Considering Operation Characteristics of the Communication Layer

“…represents the set of nodes at the physical layer that can be detected by the scheduling center and meets the following requirements: (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) According to the information received, the dispatching center takes the minimum load loss as the objective function to carry out an optimization calculation and defines SC(P The dispatching center updates the electrical parameters to the working nodes of the communication layer along with the control instruction. A control information transmission failure occurs when the transmission delay is greater than the threshold MaxT , and the node receiving the control information adjusts the electrical properties according to P j∼ 12 .…”

“…[3][4][5][6][7][8][9][10][11] υ 1 is the set of nodes on the physical layer coupled to the communication layer's new failure nodes. N p is the working subset of the physical layer, and B ρυ 1 (ρυ 1 ,…”