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

Authors :
Liu, Yunting
Tolbert, Leon M.
Kritprajun, Paychuda
Dong, Jiaojiao
Zhu, Lin
Ollis, Thomas Ben
Schneider, Kevin P.
Prabakar, Kumaraguru
Source :
Energies (19961073); Dec2022, Vol. 15 Issue 23, p9104, 24p
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19961073
Volume :
15
Issue :
23
Database :
Complementary Index
Journal :
Energies (19961073)
Publication Type :
Academic Journal
Accession number :
160737938
Full Text :
https://doi.org/10.3390/en15239104