Comparison of Ideal Transformer Method and Damping Impedance Method for PV Power-Hardware-In-The-Loop Experiments

Summers, Adam; Hernández-Alvídrez, Javier; Darbali-Zamora, Rachid; Reno, Matthew J.; Johnson, Jay; Gurule, Nicholas S.

doi:10.1109/pvsc40753.2019.8980690

Cited by 14 publications

(10 citation statements)

References 11 publications

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“…IAs have been analyzed in detail [1,2,[7][8][9][10][11][12], including: the ideal transformer model (ITM), partial circuit duplication (PCD), transmission line model (TLM), damping impedance method (DIM), time variant first-order approximation (TFA), and advanced ideal transformer model (AITM); being the ITM and DIM are the most widely used techniques for connecting power equipment to a PHIL RTS. 2.…”

Section: Interface Algorithms For Fast Dynamics: Nowadays the Accuramentioning

confidence: 99%

“…In [12], the voltage ideal transformer method (ITM) and the voltage damping impedance method (DIM) were compared during unity and non-unity power factor setting and curtailed real power levels to a baseline, when connecting a physical photovoltaic (PV) inverter to a PHIL simulation. The ITM and DIM methods generally, in simulation, have a low pass filter (LPF) on the output of the RTS to increase stability of the system when the PV inverter connects.…”

Section: Stability and Accuracy Comparison For Different Interfacing mentioning

confidence: 99%

“…A low pass filter lead compensator (LPF LD) can be used to tune the introduced phase shift to minimize the synthetic reactive power injection in the simulation without removing the characteristics of the device under test (DuT). Results from [12] are shown in Table 1. The average error represents the summation of each individual error compared to a baseline, divided by the total number of tests.…”

Section: Stability and Accuracy Comparison For Different Interfacing mentioning

confidence: 99%

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Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

et al. 2020

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The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions.

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Section: Interface Algorithms For Fast Dynamics: Nowadays the Accuramentioning

confidence: 99%

Section: Stability and Accuracy Comparison For Different Interfacing mentioning

confidence: 99%

Section: Stability and Accuracy Comparison For Different Interfacing mentioning

confidence: 99%

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Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

et al. 2020

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“…The PV irradiance profiles were then smoothed based on the plant sizes using the Wavelet Variability Model [43][44][45][46] to account for spatial averaging with large PV systems. To understand the impact of spatial averaging on the irradiance profiles the reader is invited to review [47,48]. The final PV profiles are shown in Figure 5.…”

Section: Simulations With the Pnm Modelmentioning

confidence: 99%

“…The PNM model was simulated using P/Q data passed from the EPRI DER simulator to the RT power simulation using the Data Bus (DBus) exchange. The hardware PV inverter was interfaced using the Ideal Transformer Method (ITM) [48]. The simulated PV inverters connected to bus 12 and bus 14 were simulated using a P/Q controlled PV inverter model [49].…”

Section: Baseline Simulationmentioning

confidence: 99%

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

et al. 2020

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Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

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Overview of Interface Algorithms, Interface Signals, Communication and Delay in Real-Time Co-Simulation of Distributed Power Systems

Buraimoh,

Ozkan,

Timilsina

et al. 2023

IEEE Access

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In recent years, there has been growing research interest in the virtual integration of hardware and software assets across different geographical locations. However, achieving joint real-time simulation in virtually connected laboratories presents several challenges that must be addressed. One critical aspect involves selecting suitable interface algorithms to conserve energy, ensure signal decomposition, and reconstruct data accurately, thereby preventing distortions. Additionally, communication latencies must be taken into account to maintain experiment fidelity. The establishment of fast and reliable communication between real-time simulators in different laboratories through coupling interfaces, is of utmost importance for successful real-time cosimulation. Nevertheless, assuming the constant availability of reliable and delay-free communication is unrealistic, which can lead to performance degradation and system instability. These requirements pose significant obstacles to implementing virtual integration involving various real-time simulators and hardware-in-the-loop setups across diverse laboratories. The real-time co-simulation of power systems, in particular, is highly susceptible to ineffective interface algorithms, signal decomposition, and reconstruction, as well as communication delays, potentially causing loss of synchronism and negatively impacting simulation fidelity. Consequently, these limitations render such setups unsuitable for dynamic and transient studies. In light of these challenges, this paper aims to provide an overview of interface algorithms, signal decomposition and reconstruction techniques, communication protocols, and delay compensation approaches. The goal is to ensure system fidelity, enhance coupling point modeling, and improve the accuracy of real-time co-simulation in virtual environments across long distances while preserving ongoing research confidentiality, safeguarding intellectual property, and facilitating collaborative research.

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Comparison of Ideal Transformer Method and Damping Impedance Method for PV Power-Hardware-In-The-Loop Experiments

Cited by 14 publications

References 11 publications

Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Overview of Interface Algorithms, Interface Signals, Communication and Delay in Real-Time Co-Simulation of Distributed Power Systems

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