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<p>Modular multilevel converters (MMCs) are widely used in medium-voltage direct-current (MVDC) applications due to their high modularity and controllability. However, their key components (power devices and capacitors) experience varying power loss stress under different operating conditions. Existing submodule loss optimization methods only focus on either power devices or capacitors, failing to realize collaborative optimization of key components within the submodule. Aiming to address this issue, this paper proposes a key component collaborative operation optimization (KC-COO) strategy for submodules (SMs). The strategy evaluates the aging degree of capacitors and power devices based on their status data, classifies and scores them, and then incorporates the scoring results into the capacitance voltage to form an elastic capacitance voltage for sorting. Combined with the modulation strategy, KC-COO determines the current flow path in the bridge arm through SM key components, achieving collaborative optimization by adjusting their average current through these components. Simulations in MATLAB/Simulink and experiments on a small MMC prototype validate the efficacy of the proposed KC-COO strategy.</p>

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The active regulation of SM operation modes for collaborative optimization control of key components in MMC–MVDC inverter applications

  • 期刊论文

  • 发表日期：

    2026年1月5日

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  • Chang Liu

摘要

Modular multilevel converters (MMCs) are widely used in medium-voltage direct-current (MVDC) applications due to their high modularity and controllability. However, their key components (power devices and capacitors) experience varying power loss stress under different operating conditions. Existing submodule loss optimization methods only focus on either power devices or capacitors, failing to realize collaborative optimization of key components within the submodule. Aiming to address this issue, this paper proposes a key component collaborative operation optimization (KC-COO) strategy for submodules (SMs). The strategy evaluates the aging degree of capacitors and power devices based on their status data, classifies and scores them, and then incorporates the scoring results into the capacitance voltage to form an elastic capacitance voltage for sorting. Combined with the modulation strategy, KC-COO determines the current flow path in the bridge arm through SM key components, achieving collaborative optimization by adjusting their average current through these components. Simulations in MATLAB/Simulink and experiments on a small MMC prototype validate the efficacy of the proposed KC-COO strategy.