Fast Quasi-Static Time-Series Simulation for Accurate PV Inverter Semiconductor Fatigue Analysis with a Long-Term Solar Profile

Yunting Liu (), Leon M. Tolbert, Paychuda Kritprajun, Jiaojiao Dong, Lin Zhu, Thomas Ben Ollis, Kevin P. Schneider and Kumaraguru Prabakar
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Yunting Liu: Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
Leon M. Tolbert: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
Paychuda Kritprajun: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
Jiaojiao Dong: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
Lin Zhu: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
Thomas Ben Ollis: Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Kevin P. Schneider: Pacific Northwest National Laboratory, Richland, WA 99354, USA
Kumaraguru Prabakar: National Renewable Energy Laboratory, Golden, CO 80401, USA

Energies, 2022, vol. 15, issue 23, 1-24

Abstract: Power system simulations with long-term data typically have large time steps, varying from one second to a few minutes. However, for PV inverter semiconductors in grid-connected applications, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be approximately 100 μs. This small time step requires long computation times to process yearly power production profiles. In this paper, we propose a fast fatigue simulation for inverter semiconductors using the quasi-static time-series simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature using a fast Fourier transform. The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 min, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. The error of the proposed method is significantly less than the conventional averaged thermal profile. A PV inverter that responds to a transactive energy system is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to cosimulate with system-level simulation tools that also adopt the quasi-static time-series concept.

Keywords: aging; fatigue; inverters; solar power generation; systems simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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