
Key Technology Optimization and Development of New Energy Enterprises of Photovoltaic Power Generation
Author(s) -
Jiangping Nan
Publication year - 2021
Publication title -
distributed generation and alternative energy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.19
H-Index - 12
eISSN - 2156-3306
pISSN - 2156-6550
DOI - 10.13052/dgaej2156-3306.3716
Subject(s) - control theory (sociology) , waveform , total harmonic distortion , computer science , harmonic , tracking error , voltage , process (computing) , adaptability , current (fluid) , power (physics) , distortion (music) , noise (video) , tracking (education) , control (management) , engineering , telecommunications , electrical engineering , artificial intelligence , psychology , ecology , amplifier , pedagogy , physics , bandwidth (computing) , quantum mechanics , image (mathematics) , biology , operating system
In order to improve the algorithm of time-varying parameters and unknownparameters adaptability, avoid assuming the approximate part deviationcaused by the algorithm, this paper proposes a adaptive control algorithm, thealgorithm based on lyapunov direct method to predict the output voltage inthe process of estimating each parameter in a reasonable manner to parameterestimation error with the actual output current and current automatic adjust-ment. The adaptive control of current tracking is realized and the error causedby assuming voltage or current and neglecting line resistance is avoided inthe predictive current control algorithm. The simulation results show thatthe tracking current can track the target current with high precision fromt = 0 in the presence of random noise, and the power factor is close to 1,showing a good steady-state performance. Frequency domain waveform, thecalculated harmonic distortion rate is 2.2418%, waveform quality is good andeach harmonic amplitude is small. Conclusion: adaptive control algorithmcan quickly and accurately realize current tracking and greatly suppress thenoise.