Contribution to stability analysis of power hardware‐in‐the‐loop simulators

Tremblay, Olivier; Fortin-Blanchette, Handy; Gagnon, Richard; Brissette, Yves

doi:10.1049/iet-gtd.2016.1574

Cited by 25 publications

(6 citation statements)

References 22 publications

(25 reference statements)

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“…In addition, real-time simulation speed can be reached. Such simulation model can be used for prototype operation and control tests [41]. It has been adopted to validate the implementation feasibility of different PV controllers systems [42,43].…”

Section: Hil Testmentioning

confidence: 99%

Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

Yang

Shu

et al. 2018

Journal of Renewable and Sustainable Energy

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In order to achieve the maximum power point tracking (MPPT) of Photovoltaic (PV) systems in the presence of time-varying stochastic operation conditions and various uncertainties/disturbances, a passivity-based fractional-order sliding-mode control (PbFoSMC) scheme is proposed. The design can be classified into two steps, i.e., (a) Construct a storage function in terms of the tracking error of DC-link voltage, DC-link current and q-axis current for the PV system, upon which the actual characteristics of each term is thoroughly analyzed. Moreover, the beneficial terms are carefully retained to enhance the dynamical responses of the closed-loop system while the detrimental terms are fully removed to realize a global control consistency; (b) Based on the passivized system, a fractional-order sliding-mode control (FoSMC) is incorporated as an additional input, which can considerably improve the control performance with the aim of rapid uncertainties/disturbances rejection. Four case studies, including the solar irradiance change, temperature variation, power grid voltage drop, and PV inverter parameter uncertainties, are undertaken to evaluate the effectiveness of PbFoSMC in comparison to that of PID control, passivity-based control (PBC), and sliding-mode control (SMC), respectively. At last, a dSpace based hardware-in-loop (HIL) test is carried out to validate the implementation feasibility of PbFoSMC.

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Section: Hil Testmentioning

confidence: 99%

Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

Yang

Shu

et al. 2018

Journal of Renewable and Sustainable Energy

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“…A lot of research has been carried out to improve in general the accuracy of the PHIL simulation [10][11][12], compensation of the PHIL simulation interface [13], and design considerations [14]. The issues related to stability of a PHIL experiment are also highlighted in detail in referenced studies [15][16][17]. Similarly Zha et al [18] discusses the accuracy of the complete setup using virtual impedance method.…”

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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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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“…In the early development stage of the power converters, the rapid prototyping and validation of the power converters can effectively be implemented by the hardware‐in‐the‐loop (HIL) simulation technique. The involved power HIL and controller HIL simulation can test the power converters as well as the associated controllers without the truly‐built physical plants [3]. The HIL simulation requires the physical model to be solved in real time on the processor.…”

Section: Introductionmentioning

confidence: 99%

Device‐level modelling and FPGA‐based real‐time simulation of the power electronic system in fuel cell electric vehicle

Bai

Liu

et al. 2019

IET Power Electronics

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Power electronic converters are essential components in the fuel cell electric vehicle (FCEV) powertrain, which precisely control the power output of the fuel cell stack, the charging and discharging process of the battery, and the operation of the traction motor. The hardware-in-the-loop (HIL) simulation plays an important role in the rapid validation of power converters in their early development stages. In this study, a device-level model of the power converters in FCEV powertrain is developed for the FPGA-based real-time simulation. By fulfilling the circuit topology partitioning and the switch model partitioning, the FCEV power electronic system can be simulated with sub-microsecond time-step while producing the detailed switching waveforms with 5 ns resolution. Therefore, the device electrical stress, and the switching power losses can be evaluated in real time. Furthermore, the electro-thermal converter model is developed accordingly, which makes it possible to evaluate the IGBT/ Diode thermal behaviour in the HIL simulation. In this study, the FPGA hardware is designed with the NI LABVIEW FPGA module and implemented on the NI-7975R FLEXRIO FPGA board. The accuracy of the FPGA-based simulation results is evaluated by the results from offline simulation tools. The effectiveness of the proposed model is then validated by the controller HIL experiments.

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Contribution to stability analysis of power hardware‐in‐the‐loop simulators

Cited by 25 publications

References 22 publications

Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

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

Device‐level modelling and FPGA‐based real‐time simulation of the power electronic system in fuel cell electric vehicle

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