An adaptive neural fuzzy virtual inertia control method for VSC-HVDC system

Autor: Lin Zhu, Qi Liu, Shan Liu, Zhen Wang, Jianhui Meng, Likang Gu, Zixin Zhou
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Frontiers in Energy Research, Vol 10 (2023)
Druh dokumentu: article
ISSN: 2296-598X
DOI: 10.3389/fenrg.2022.1109277
Popis: Compared to conventional DC transmission, Voltage source converter based high voltage direct current transmission (VSC-HVDC) has the advantages of independently controllable transmission power, no commutation failure, no reactive power compensation and low harmonic levels. However, VSC-HVDC transmission cannot provide effective frequency support and regulation for the system after grid connection. For this reason, an adaptive neural fuzzy virtual inertia control method is proposed to impose a control strategy on the converter at the receiving end of a VSC-HVDC transmission. The method uses the frequency change rate and the amount of change of frequency as constraints to dynamically adjust the virtual inertia and damping coefficients. It provides larger inertial support when the frequency fluctuation is large and smaller inertial support when the frequency fluctuation is small, thus adapting to different operating conditions. Finally, a hardware-in-the-loop simulation platform is built. The superiority and application prospect of the proposed strategy in frequency stability of the system are verified by comparing the proposed strategy with the traditional virtual control strategy.
Databáze: Directory of Open Access Journals