Key Technologies and Innovation Prospects of Large-Capacity Voltage-Sourced Inverter in the Construction of New Power Systems
Year: 2025
Type: article
Abstract: [Objective] The large-capacity static var generator (SVG) based on modular multilevel technology can be used to realize various functions such as active network construction,reactive power compensation, harmonic suppression,and impedance remodeling,and is an important equipment to support the construction of new power systems. [Methods] This study discusses the key technologies and innovation prospects of large-capacity voltage-sourced inverters in the construction of new power systems, reviews the development history and basic topological principles of SVG,determines the evolutionary conversion relationship between SVG and modular multilevel converters, analyzes the quantitative evaluation formula of AC grid strength supported by SVG,and summarizes the advantages of SVG in ensuring the safe and stable operation of the new power system with a high proportion of new energy and power electronic equipment. Then, key technologies such as SVG-based multisource line commutation converter (SLCC) technology, active filter,grid-forming SVG,and energy storage-type SVG were analyzed. Finally,the key role that SVG plays in the construction of new power systems and the key research directions were discussed. [Results] In the construction of new power systems, large-capacity SVGs have broad application prospects in areas such as large-scale new energy island exports,weak-system voltage support, and wide-area harmonic suppression. [Conclusions] Further in-depth research is needed on SVG precharging and black start,as well as on coordinated control among multiple SVGs in isolated new energy systems.
Author: Weimin MA, Ming LI, Yinglin XUE, Yingxin WANG, Fangjie WU, Zheng ZHAO, Tan LI
Institution: State Grid Corporation of China (China)
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7084061808
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