SMTD Co-Simulation Framework With HELICS for Future-Grid Analysis and Synthetic Measurement-Data Generation

Bharati, Alok Kumar; Ajjarapu, Venkataramana

doi:10.1109/tia.2021.3123925

Cited by 26 publications

(13 citation statements)

References 36 publications

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“…When dealing with pure software power systems' models and simulators, different solutions are proposing co-simulation technologies to interconnect heterogeneous simulation environments by means of an orchestrator entity that manages time evolution, regulation, and data exchange between different simulator entities. For instance, Bharati et al [11] implement a complex transmission and distribution co-simulation framework based on HELICS to effectively provide innovative algorithms for future power grid planning, validation of controls under critical contingencies, and validation of various widearea monitoring and controls. However, these solutions cannot deal with the time-domain analysis (e.g.…”

Section: Related Workmentioning

confidence: 99%

Stability and Accuracy Analysis of a Distributed Digital Real-Time Cosimulation Infrastructure

Barbierato

Pons

Mazza

et al. 2022

IEEE Trans. on Ind. Applicat.

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Co-simulation techniques are gaining popularity amongst the power system research community to analyse future scalable Smart Grid solutions. However, complications such as multiple communication protocols, uncertainty in latencies are holding up the widespread usage of these techniques for power system analysis. These issues are even further exacerbated when applied to Digital Real-Time Simulators (DRTS) with strict realtime constraints for Power Hardware-In-the-Loop (PHIL) tests. In this paper, we present an innovative Digital Real-Time Cosimulation Infrastructure that allows interconnecting different DRTS through the Aurora 8B/10B protocol to reduce the effects of communication latency and respect real-time constraints. The proposed solution synchronizes the DRTS interconnection by means of the IEEE 1588 Precision Time Protocol (PTP) standard to align executions and results obtained by the co-simulated scenario. The Ideal Transformer Method (ITM) Interface Algorithm (IA), commonly used in PHIL applications, is used to interface the DRTS. Finally, we present time-domain and frequency-domain accuracy analyses on the obtained experimental results to demonstrate the potential of the proposed infrastructure. With the presented setup, a time step duration down to 50 µs is shown to be stable and accurate in running an Electro-Magnetic Transients (EMT) co-simulated power grid scenario by interconnecting two commercial DRTS (i.e. RTDS NovaCor), extending the scalability of future Smart Grid real-time simulations.

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Section: Related Workmentioning

confidence: 99%

Stability and Accuracy Analysis of a Distributed Digital Real-Time Cosimulation Infrastructure

Barbierato

Pons

Mazza

et al. 2022

IEEE Trans. on Ind. Applicat.

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“…Phasors-based CIA [19] is well-recognised to be the current state-of-the-art solution to facilitate the geographically distributed co-simulation as it exhibits a higher degree of simulation fidelity than other methods. The previously proposed CIAs [19][20][21][22] are mostly focussed on interfacing transmission and distribution systems that exhibit slow transients and less complexity as compared to performing co-simulation at multiple transmission systems.…”

Section: Related Workmentioning

confidence: 99%

“…Further, the scalability in cyber systems is accomplished by leveraging computational resources, such as server racks from other CPS testbeds, and modelling virtual sensors and actuators to emulate physical devices. Grid Emulation (Fidelity) : Emulates substation and control centre networks with industry‐grade communication protocols while simulating complex power system dynamics in a HIL environment. This provides a high fidelity representation of geographically dispersed grid elements for industrial, academic, and broader public users. Remote Access : Provides remote access capability to multiple users using internet‐based network interfaces to conduct multiple and coordinated cybersecurity‐based attack‐defence experiments [20]. Testing , Validation , and Evaluation : Since the current operational systems cannot be utilised to perform cyber‐physical security‐related experiments, the NEFTSec provides a platform to test, validate, and evaluate the performances of state‐of‐the‐art research and engineering solutions in real time. Demonstration and Training : Provides a unique demonstration platform by simulating realistic cyberattacks and possible defence measures [23, 24].…”

Section: Applications Architecture and Designmentioning

confidence: 99%

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NEFTSec: Networked federation testbed for cyber‐physical security of smart grid: Architecture, applications, and evaluation

Singh

Manimaran

Porschet

et al. 2022

IET Cyber-Phy Sys Theory & Ap

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As today's power grid is evolving into a densely interconnected cyber‐physical system (CPS), a high fidelity and multifaceted testbed environment is needed to perform cybersecurity experiments in a realistic grid environment. Traditional standalone CPS testbeds lack the ability to emulate complex cyber‐physical interdependencies between multiple smart grid domains in a real‐time environment. Therefore, there are ongoing research and development (R&D) efforts to develop an interconnected CPS testbed by sharing geographically dispersed testbed resources to perform distributed simulation while analysing simulation fidelity. This paper presents a networked federation testbed for cybersecurity evaluation of today's and emerging smart grid environments. Specifically, it presents two novel testbed architectures, including cyber federation and cyber‐physical federation, identifies R&D applications, and also describes testbed building blocks with experimental case studies. It also presents a novel co‐simulation interface algorithm to facilitate distributed simulation within cyber‐physical federation. The resources available at the PowerCyber CPS security testbed at Iowa State University (ISU) and the US Army Research Laboratory are utilised to develop this platform for performing multiple experimental case studies pertaining to wide‐area protection and control applications in power system. Finally, experimental results are presented to analyse the simulation fidelity and real‐time performance of the testbed federation.

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“…The development of future grid analysis tools is a growing area of interest for researchers and industries around the world [11]. Melbourne Energy Institute proposed a plan in [12] for a future Australian grid relying 100% on renewable resources.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Security Analysis Framework for Future Large Grids With High Renewable Penetrations

et al. 2023

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The 100% renewable energy targets from the policymakers for the future grids have drawn a significant amount of interest. The high renewable penetration made future large interconnected grids (LIGs) more volatile and harder to understand using historical observations. This led to the need to study future LIGs using a wide range of future-year operating conditions and contingencies. However, existing planning tools are not sufficient for the dynamic security assessment (DSA) of these future LIGs due to a lack of detailed modeling capabilities and computational limitations when processing a wide range of scenarios. This paper addresses these two challenges by proposing; 1) an efficient modeling framework that can generate large grid's dynamic data with cascade behaviors for a wide range of scenarios. This data is generated by respecting the constraints of production cost models and their respective AC power flow dynamic simulation models at an hourly resolution; 2) an unsupervised machine learning(ML)-based approach for fast scanning the DSA data. The proposed approach uses feature engineering techniques and fast Fourier transforms to transform the time series signals into visually distinguishable frequency domain signals for DSA. The proposed simulation framework is used to generate 1.485 terabytes of dynamic simulation data for the 2028 WECC system containing 4455 scenarios. The proposed ML framework used the 2028 WECC system to demonstrate its effectiveness and speed in identifying critical scenarios.INDEX TERMS Dynamic security assessment, unsupervised learning, feature engineering, large grids.

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SMTD Co-Simulation Framework With HELICS for Future-Grid Analysis and Synthetic Measurement-Data Generation

Cited by 26 publications

References 36 publications

Stability and Accuracy Analysis of a Distributed Digital Real-Time Cosimulation Infrastructure

Stability and Accuracy Analysis of a Distributed Digital Real-Time Cosimulation Infrastructure

NEFTSec: Networked federation testbed for cyber‐physical security of smart grid: Architecture, applications, and evaluation

Dynamic Security Analysis Framework for Future Large Grids With High Renewable Penetrations

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