Abstract
Power hardware-in-the-loop (PHIL) systems are advanced, real-time platforms for combined software and hardware testing. Two paramount issues in PHIL simulations are the closed-loop stability and simulation accuracy. This paper presents a virtual impedance (VI) method for PHIL simulations that improves the simulation’s stability and accuracy. Through the establishment of an impedance model for a PHIL simulation circuit, which is composed of a voltage-source converter and a simple network, the stability and accuracy of the PHIL system are analyzed. Then, the proposed VI method is implemented in a digital real-time simulator and used to correct the combined impedance in the impedance model, achieving higher stability and accuracy of the results. The validity of the VI method is verified through the PHIL simulation of two typical PHIL examples.
Highlights
Power hardware-in-the-loop (PHIL) systems represent an emerging novel technique that is being increasingly applied in power systems for equipment testing and validation
Such a simulator is generally composed of three major parts: (I) the original power system (OPS), which is modeled in a real-time simulator; (II) the interface equipment (IE), which links the hardware and the simulated system [1]; and (III) the piece of hardware under test (HUT)
The reference signal is obtained on the OPS side, and it is applied to the terminals of the actual hardware through the IE to establish a virtual exchange of power between the simulated virtual network and the power HUT
Summary
Power hardware-in-the-loop (PHIL) systems represent an emerging novel technique that is being increasingly applied in power systems for equipment testing and validation. Such a simulator is generally composed of three major parts: (I) the original power system (OPS), which is modeled in a real-time simulator; (II) the interface equipment (IE), which links the hardware and the simulated system [1]; and (III) the piece of hardware under test (HUT). PHIL systems offer several advantages over other analysis and testing methods. These systems minimize the cost and risk of examining various extreme conditions and maximize the likelihood of identifying hidden defects in an apparatus before their impacts are discovered in actual operations.
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