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This paper presents a fully analog demonstrator based on power system emulation for high-speed power system stability analysis. A benchmark using afixed two-machine topology has been implemented. The characteristics of the emulated components (i.e., generators and transmission lines) are reprogrammable and short circuits can be emulated at different(More)
This paper presents an ultra-high speed hardware platform dedicated to power system dynamic (small signal) and transient (large signal) stability. It is based on an intrinsic parallel architecture which contains hybrid mixed-signal (analog and digital) circuits. For a given model, this architecture overcomes the speed of the numerical simulators by means of(More)
This paper examines two mixed-signal hardware circuits dedicated to transient power system emulation. They both use a flexible, modular and very high-speed emulation approach based on a field programmable power network system (FPPNS). This promising approach is dedicated to emulate multiple nodes power system dynamics. The speed limit of such approach(More)
This paper joins a series of papers dealing with high-speed power system emulators. It clarifies the last details about the system level of the AC emulation approach by analyzing and quantifying the systematic errors introduced during modeling. Thereby a new optimized generator model has been developed. Its main advantage is improved stability. The(More)
This paper presents a fully integrated, reconfigurable inductance, developed for high-speed power system transient stability emulation. Known active inductance topologies are not suitable for this application for two main reasons. Firstly, most active inductors are used at very high frequencies, due to their RF applications, and secondly, the DC(More)
This paper presents an innovative 3D hardware architecture for power system dynamic and transient stability. Based on an intrinsic parallel architecture by means of mixedsignal circuits (analog and digital) it overcomes the speed of numerical simulators for given models. This approach does not competing the accuracy and model complexity of the high(More)
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