Power Hardware in-the-Loop Testing to Analyze Fault Behavior of Smart Inverters in Distribution Networks

Ustun, Taha Selim; Sugahara, Shuichi; Suzuki, Masaichi; Hashimoto, Jun; Otani, Kenji

doi:10.3390/su12229365

Cited by 16 publications

(5 citation statements)

References 20 publications

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“…The green line represents the active power consumption of the HUT and it can be seen that it is almost negligible. Therefore, the dynamic behavior of the HUT can be simply modelled as a capacitor and using the reactive power value at the standard 230 V rms the default parasitic capacitance is approximated as shown in the following Equation (7).…”

Section: Scenario 2: Closed Loop Phil Simulationmentioning

confidence: 99%

“…This paper aims to investigate the same and to propose the required adjustments in a bid to improve the components performance. A very recent study by Ustun et al [7] analyzes the behavior of smart inverters during faults. It has also shown that software/hardware adjustments are required to study the inverters dynamics in simulation environments.…”

Section: Introductionmentioning

confidence: 99%

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Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

et al. 2021

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With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario.

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Section: Scenario 2: Closed Loop Phil Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

et al. 2021

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“…Characteristics of the voltage signal of the system are analyzed to detect various unsymmetrical faults. But the techniques used for the detection, classification, and location of faults need to be updated and should be based on modern technology [33]. So, that the power system can easily handle these problems that are making it unstable in operation.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Based Relay for Online Fault Detection, Classification, and Fault Location in a Grid-Connected Microgrid

et al. 2023

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In this article, a maiden attempt have been taken for the online detection of faults, classification of faults, and identification of the fault locations of a grid-connected Micro-grid (MG) system. A deep learning algorithm-based Long Short Term Memory (LSTM) network is proposed, for the first time, for the online detection of faults and their classifications of the considered MG system to overcome the issues that persist in the existing algorithms. Also, a combination of an LSTM network and feed-forward neural network (FFNN) with a back-propagation algorithm (BPA) is proposed to identify the exact locations of the faults since the identification of fault locations is more challenging than fault categorizations. To select a suitable deep learning network with multiple hidden layers for achieving the aforesaid objectives, a rigorous analysis has been done. To study the accuracy of the proposed techniques, different types of faults with different parameters are considered in this paper. An extensive simulation has been done in MATLAB/Simulink platform to study the performance of the system with the proposed techniques. To validate the effectiveness of the proposed techniques, the entire system is implemented in the real-time platform using the OPAL-RT digital simulator. Comparison has also been done for the results obtained using ANN and proposed techniques. The results show that the proposed techniques based on the deep learning network effectively detect, classify, and identify the location of different faults of an MG system with acceptable performances.

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“…Despite several studies on P-HIL for reconfigurable realtime grid emulator in power systems with high penetration of renewable and wideband-frequency grid impedance have been published in literature [13]- [18], only few of them use and analyse the P-HIL as a tool for testing the fault behavior of power converters in distribution networks [16]- [18]. In all these works, particular attention is given to the accuracy and the stability analysis of the P-HIL while emulating symmetrical grid faults [16], [17], while only few results of LVRT testing under asymmetrical grid conditions are provided in [18]. Here is concluded that, neither if the grid emulator is controlled in open loop nor in closed loop, the network asymmetrical voltage dips are generated accurately.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Asymmetrical Grid Faults for P-HIL Accuracy and Stability Analysis in LVRT Tests

Pugliese

Liserre

Rafiq

2023

IEEE Trans. on Ind. Applicat.

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The energy systems are evolving toward the comprehensive and massive integration of power electronics-based technologies, such as photovoltaic, wind turbines, and electric vehicles. All these emerging and promising power converters technologies must be tested to comply with the grid codes, especially during severe grid fault events, before their commercialization. Low-Voltage Ride-Through (LVRT) field tests are usually conducted to prove the ability of the converter to ride through faults. These field tests are expensive and require bulky equipment, while Power-Hardware-in-the-Loop (P-HIL) offers a more cost-effective and flexible alternative. However, the P-HIL must be stable and accurate to get reliable results. The accuracy of a P-HIL test is directly influenced by its interface algorithm. This paper proposes a frequency domain approach, based on the concept of singular values in Multi-Input Multi-Output systems, to study the P-HIL accuracy and stability in grid connected converter testing under asymmetrical line-to-line fault conditions. Accuracy and stability analysis have been performed analytically and validated by Matlab/Simulink simulations and by experimental P-HIL tests. This paper demonstrates that correct fault modeling leads to correct assessment of the reactive power injected under faults and of avoiding resonances.

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Power Hardware in-the-Loop Testing to Analyze Fault Behavior of Smart Inverters in Distribution Networks

Cited by 16 publications

References 20 publications

Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

Deep Learning Based Relay for Online Fault Detection, Classification, and Fault Location in a Grid-Connected Microgrid

Modeling of Asymmetrical Grid Faults for P-HIL Accuracy and Stability Analysis in LVRT Tests

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