A Multi-Time-Step Transmission Line Interface for Power Hardware-in-the-Loop Simulators

Tremblay, Olivier; Rimorov, Dmitry; Gagnon, Richard; Fortin-Blanchette, Handy

doi:10.1109/tec.2019.2941567

Cited by 17 publications

(14 citation statements)

References 22 publications

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“…By substituting ( 16) into (28) and then the resulted expression into (29), the relationship between the α component of the voltages in the feed-forward path between two subsystems in Fig. 8 can be described as…”

Section: B Asynchronous Coupling Modelmentioning

confidence: 99%

“…In [19], the impact of power amplifier (switched mode) on the stability of PHIL setups was analyzed and concluded that the approximation of power amplifier as time delay in s-domain was inappropriate as the power amplification itself impacted the stability of the PHIL setup. A number of techniques to improve the stability of PHIL setups have been proposed, such as the addition of hardware inductance in [26], feedback current filtering in [27], shifting impedance method in [17], multi-rate partitioning in [28], multi-time-step transmission line interface in [29], use of open-loop inverter as power amplifier in [30], with a comparison of a few of these approaches ( [17], [26]- [28]) presented in [31].…”

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confidence: 99%

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Applicability of Geographically Distributed Simulations

Syed

Hoang

Kontou

et al. 2022

IEEE Trans. Power Syst.

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Geographically distributed simulations (GDS) overcome the inherent limitations in capabilities of single research infrastructure to accurately represent large-scale complex power and energy systems within representative operating environments in real-time. The feasibility of GDS has been proven, however, there is a lack of confidence in its adoption owing to limited evidence of its stability and accuracy that ascertain its practical applicability. This paper presents detailed small signal stability models for GDS setups with two interface signals transformations. The models have been validated by empirical analysis and used for determining the boundaries for stable operation of GDS setups. For the common region of stability of the two transformations considered, accuracy analysis presented offers insights for their selection. This advancement, thereby, enables realisation of experimental setups that can cater for the growing need to design and validate operational schemes that ensure robust and resilient operation of critical national infrastructure.Index Terms-Accuracy, geographically distributed simulations (GDS), power hardware-in-the-loop (PHIL), stability. I. INTRODUCTIONH ARDWARE-in-the-loop has proven to be a valuable approach to accelerate the validation and deployment of novel technologies, with an increasing number of laboratories across the world adopting the approach [1]. The rapidly increasing complexity of power and energy systems (due to increased decentralization, decarbonization and digitalization) presents a challenge for single research laboratories, as existing capabilities (computational, expertise or equipment) will have to expand to encapsulate the growing complexity to ensure rigorous validation and roll-out of novel technologies at pace. This has encouraged the development and establishment of the concept of geographically distributed simulations (GDS), allowing for complementary expertise, additional equipment, domains and computational resources to be

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Section: B Asynchronous Coupling Modelmentioning

confidence: 99%

mentioning

confidence: 99%

Applicability of Geographically Distributed Simulations

Syed

Hoang

Kontou

et al. 2022

IEEE Trans. Power Syst.

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“…P HIL simulation, an advanced and efficient tool incorporating the physical power apparatus and large-scale power network into a real-time testing environment, has been widely utilized to promote the research and development in the power industry [1]- [11]. Owing to the merit of carrying out repeated, non-destructive, and in-depth investigation of the power apparatus and their interactions with the power network, PHIL has been extensively employed for prototyping applications [4]- [6], the verification of novel control paradigm [7], the black start testing of grid-forming converter [8], or the dynamic modelling and prototyping of renewable energy systems, such as variable-speed wind turbines [10], solar energy [6], and energy storage resources [5], [11].…”

Section: Introductionmentioning

confidence: 99%

“…The impact of the non-ideal characteristics and the dynamics stemming from the PI on the PHIL system stability and accuracy has been extensively discussed in literature [20]- [24]. Many research efforts have been devoted to improve the stability and accuracy of the PHIL simulation, such as the impedance shifting method [4], multi-rate partitioning interface [19], Bergeron transmission line model based multitime-step interface [6], Smith-predictor based compensation [23], H ∞ optimal control based interface [5], the optimal compensation filter design [24], and other advanced methods as summarized in [25]. Detailed modelling principles, block diagrams, stability criteria, and accuracy metrics have been developed for the assessment of system properties such as stability and accuracy of respective approaches.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Sensitivity Analysis of Real-Time Power Hardware-in-the-Loop (PHIL) Systems

et al. 2022

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Power hardware-in-the-loop (PHIL) simulation leverages the advanced real-time emulation based technique to carry out in-depth investigations on novel real-world power components. Power amplifiers, sensors, and signal conversion units based power interfaces (PI) incorporate physical hardware systems and real-time simulation platforms into PHIL setups. However, the employment of any interfacing technique inevitably introduces disturbances such as sensor noise, switching harmonics, or quantization noise to PHIL systems. To facilitate quantitatively analyzing and assessing the impact of external disturbances on PHIL simulation systems, a framework for sensitivity analysis of PHIL setups has been developed in this paper. Detailed modelling principles related to the sensitivity analysis of PHIL systems and the inherent relationship between sensitivity transfer functions and stability criteria are elaborated along with theoretical and experimental validation. Based on this concept, accuracy assessment methods are employed in this framework to quantify generic sensitivity criteria. Moreover, physical passive load and converterbased PHIL setups are applied and experimental results are presented to characterize and demonstrate the applicability of the proposed framework.INDEX TERMS Power hardware-in-the-loop (PHIL) simulation systems, sensitivity analysis, power interface, system modelling, system theory, control systems, real-time simulation system.

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“…Most of the contributions on PHIL in the literature acknowledge that time delay is important [13]- [23], however a detailed study of time delay has not been published yet. Appropriate understanding of the time delay and its effect will lead to a reduced risk of instabilities and inaccuracies when performing PHIL experiments, allowing more resilient and accurate evaluation of complex power components [24]. A thorough characterization of delays in PHIL can also help to reduce the total loop delay and increase its accuracy.…”

mentioning

confidence: 99%

Characterization of Time Delay in Power Hardware in the Loop Setups

Guillo-Sansano

Syed

Roscoe³

et al. 2021

IEEE Trans. Ind. Electron.

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The testing of complex power components by means of power hardware in the loop (PHIL) requires accurate and stable PHIL platforms. The total time delay typically present within these platforms is commonly acknowledged to be an important factor to be considered due to its impact on accuracy and stability. However, a thorough assessment of the total loop delay in PHIL platforms has not been performed in the literature. Therefore, time delay is typically accounted for as a constant parameter. However, with the detailed analysis of the total loop delay performed in this paper, variability in time delay has been detected as a result of the interaction between discrete components. Furthermore, a time delay characterization methodology (which includes variability in time delay) has been proposed. This will allow for performing stability analysis with higher precision as well as to perform accurate compensation of these delays. The implications on stability and accuracy that the time delay variability can introduce in PHIL simulations has also been studied. Finally, with an experimental validation procedure, the presence of the variability and the effectiveness of the proposed characterization approach have been demonstrated. Index Terms-Time delay, power hardware-in-the-loop, delay identification, real-time simulation, component testing. NOMENCLATURE Abbreviations AC Alternating current. ADC Analog to digital converter. DAC Digital to analog converter. DC Direct current. DRTS Digital real time simulator. FPGA Field-Programmable Gate Array. GPS Global positioning system. HUT Hardware under test. IA Interface algorithm. ITM Ideal transformer method.

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A Multi-Time-Step Transmission Line Interface for Power Hardware-in-the-Loop Simulators

Cited by 17 publications

References 22 publications

Applicability of Geographically Distributed Simulations

Applicability of Geographically Distributed Simulations

A Framework for Sensitivity Analysis of Real-Time Power Hardware-in-the-Loop (PHIL) Systems

Characterization of Time Delay in Power Hardware in the Loop Setups

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