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

Abstract

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.

Virtual Inertia Control for Power Electronics-Integrated Power Systems: Challenges and Prospects

“…RESs have prominent features such as environmental friendliness, low-cost power, and zero harmful emission elements [11,12]. However, a large-scale power electronic converter is needed to integrate these RESs into the grid, which exhibits some challenging features, such as frequency and voltage stability issues [13], low damping responses [14], and significant zero-inertia responses, because of the absence of rotating parts in RESs [15]. Inertia is a characteristic of synchronous generators, a fundamental component of most power systems [16].…”

Virtual inertia analysis of photovoltaic energy storage systems based on reduced-order model

“…If the equivalent reduced-order model of the photovoltaic energy storage system has been established, the next step is to evaluate the system's virtual inertia based on this model. Analytical methods such as state-space matrices and transfer functions (Wu et al, 2017;You et al, 2022;Zhu et al, 2023) are commonly used theoretical foundations for studying inertia issues in PVESSs. Based on the established state-space model of the networked AC/DC microgrids, it was found in literature (Zhang et al, 2021) that inappropriate control parameters can lead to negative damping factors of the eigenvalues.…”