The rapid expansion of large-scale renewable energy systems has significantly increased the demand for highly reliable and fault-resilient power electronic converters capable of maintaining stable grid operation under component failures and fluctuating renewable power generation. This paper proposes a Fault-Tolerant Modular Power Converter (FTMPC) for large-scale renewable energy integration, incorporating a modular multilevel architecture, intelligent fault diagnosis, and adaptive reconfiguration control to ensure uninterrupted power conversion. The proposed converter continuously monitors semiconductor switches, capacitor voltages, converter currents, thermal conditions, and grid-side electrical parameters using an artificial intelligence-assisted monitoring framework. Upon detecting a fault, the adaptive controller rapidly isolates the defective module and dynamically redistributes power among the remaining healthy modules, thereby preserving voltage regulation, power quality, and system stability without interrupting converter operation. The modular design enhances scalability, redundancy, and maintenance flexibility while reducing system downtime and operational risks. The proposed control strategy is validated using MATLAB/Simulink under multiple operating scenarios involving renewable power fluctuations, grid disturbances, and converter fault conditions. Simulation results demonstrate that the proposed converter achieves a maximum efficiency of 98.6%, reduces total harmonic distortion to 1.9%, restores normal operation within 8 ms following a module failure, improves fault recovery capability by 94.8%, and maintains uninterrupted power delivery with superior voltage regulation and balanced power sharing. The proposed FTMPC offers a highly efficient, scalable, and intelligent solution for integrating photovoltaic and wind energy systems into future smart grids, enhancing converter reliability, operational resilience, and long-term sustainability in renewable energy applications.

Keywords - Fault-Tolerant Modular Power Converter; Modular Multilevel Converter (MMC); Renewable Energy Integration; Intelligent Fault Diagnosis; Adaptive Reconfiguration; Smart Grid.

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1. Yuan Y, Yu JL, Pan Y, Zheng S. Low-resolution phase shifter-based hybrid precoding for mmWave massive MIMO. EURASIP Journal on Wireless Communications and Networking. 2024 Nov 5;2024(1):85.
2. Zeng J, Liao B. Transmit and receive hybrid beamforming design for OFDM dual-function radar- communication systems. EURASIP journal on advances in signal processing. 2023 Mar 20;2023(1):37.
3. Maeng SJ, Yapici Y, Güvenç I, Dai H, Bhuyan A. Hybrid precoding for mmWave massive MIMO with one-bit DAC. IEEE Communications Letters. 2020 Aug 10;24(12):2941-5.
4. Morsali A, Haghighat A, Champagne B. Deep learning-based hybrid analog-digital signal processing in mmWave massive-MIMO systems. IEEE Access. 2022 Jul 5;10:72348-62.
5. Kassam J, Miri M, Magueta R, Castanheira D, Pedrosa P, Silva A, Dinis R, Gameiro A. Two-step multiuser equalization for hybrid mmwave massive mimo gfdm systems. Electronics. 2020 Jul 29;9(8):1220.
6. Xie H, Wang Y, Gao Z, Ganthia BP, Truong CV. Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm. Nonlinear Engineering. 2021 Jan 1;10(1):592-9.
7. Gu J, Wang W, Yin R, Truong CV, Ganthia BP. Complex circuit simulation and nonlinear characteristics analysis of GaN power switching device. Nonlinear Engineering. 2021 Jan 1;10(1):555- 62.
8. Rubavathy SJ, Venkatasubramanian R, Kumar MM, Ganthia BP, Kumar JS, Hemachandu P, Ramkumar MS. Smart grid based multiagent system in transmission sector. In2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) 2021 Sep 2 (pp. 1-5). IEEE.
9. Priyadarshini L, Kundu S, Maharana MK, Ganthia BP. Controller design for the pitch control of an autonomous underwater vehicle. Engineering, Technology & Applied Science Research. 2022 Aug 7;12(4):8967-71.
10. Zheng W, Mehbodniya A, Neware R, Wawale SG, Ganthia BP, Shabaz M. Modular unmanned aerial vehicle platform design: Multi-objective evolutionary system method. Computers and Electrical Engineering. 2022 Apr 1;99:107838.
11. Guo S, Li X, Guo Z, Zhao X, Meng S, Li Z. Polarization-independent optoelectronic modulator based on graphene ridge structure. Nanomaterials. 2021 Sep 29;11(10):2559.
12. Deng X, Li Z, Cao F, Hong E, Fang X. Woven fibrous photodetectors for scalable UV optical communication device. Advanced Functional Materials. 2023 Jun;33(23):2213334.
13. Guo FH, Hao LZ, Yu WZ, Li SQ, Liu GC, Hao JY, Liu YJ. High‐performance Si/VO2‐nanorod heterojunction photodetector based on photothermoelectric effect for detecting human radiation. Rare Metals. 2024 Mar;43(3):1177-85.

The rapid expansion of large-scale renewable energy systems has significantly increased the demand for highly reliable and fault-resilient power electronic converters capable of maintaining stable grid operation under component failures and fluctuating renewable power generation. This paper proposes a Fault-Tolerant Modular Power Converter (FTMPC) for large-scale renewable energy integration, incorporating a modular multilevel architecture, intelligent fault diagnosis, and adaptive reconfiguration control to ensure uninterrupted power conversion. The proposed converter continuously monitors semiconductor switches, capacitor voltages, converter currents, thermal conditions, and grid-side electrical parameters using an artificial intelligence-assisted monitoring framework. Upon detecting a fault, the adaptive controller rapidly isolates the defective module and dynamically redistributes power among the remaining healthy modules, thereby preserving voltage regulation, power quality, and system stability without interrupting converter operation. The modular design enhances scalability, redundancy, and maintenance flexibility while reducing system downtime and operational risks. The proposed control strategy is validated using MATLAB/Simulink under multiple operating scenarios involving renewable power fluctuations, grid disturbances, and converter fault conditions. Simulation results demonstrate that the proposed converter achieves a maximum efficiency of 98.6%, reduces total harmonic distortion to 1.9%, restores normal operation within 8 ms following a module failure, improves fault recovery capability by 94.8%, and maintains uninterrupted power delivery with superior voltage regulation and balanced power sharing. The proposed FTMPC offers a highly efficient, scalable, and intelligent solution for integrating photovoltaic and wind energy systems into future smart grids, enhancing converter reliability, operational resilience, and long-term sustainability in renewable energy applications.

Keywords - Fault-Tolerant Modular Power Converter; Modular Multilevel Converter (MMC); Renewable Energy Integration; Intelligent Fault Diagnosis; Adaptive Reconfiguration; Smart Grid.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Yuan Y, Yu JL, Pan Y, Zheng S. Low-resolution phase shifter-based hybrid precoding for mmWave massive MIMO. EURASIP Journal on Wireless Communications and Networking. 2024 Nov 5;2024(1):85.
2. Zeng J, Liao B. Transmit and receive hybrid beamforming design for OFDM dual-function radar- communication systems. EURASIP journal on advances in signal processing. 2023 Mar 20;2023(1):37.
3. Maeng SJ, Yapici Y, Güvenç I, Dai H, Bhuyan A. Hybrid precoding for mmWave massive MIMO with one-bit DAC. IEEE Communications Letters. 2020 Aug 10;24(12):2941-5.
4. Morsali A, Haghighat A, Champagne B. Deep learning-based hybrid analog-digital signal processing in mmWave massive-MIMO systems. IEEE Access. 2022 Jul 5;10:72348-62.
5. Kassam J, Miri M, Magueta R, Castanheira D, Pedrosa P, Silva A, Dinis R, Gameiro A. Two-step multiuser equalization for hybrid mmwave massive mimo gfdm systems. Electronics. 2020 Jul 29;9(8):1220.
6. Xie H, Wang Y, Gao Z, Ganthia BP, Truong CV. Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm. Nonlinear Engineering. 2021 Jan 1;10(1):592-9.
7. Gu J, Wang W, Yin R, Truong CV, Ganthia BP. Complex circuit simulation and nonlinear characteristics analysis of GaN power switching device. Nonlinear Engineering. 2021 Jan 1;10(1):555- 62.
8. Rubavathy SJ, Venkatasubramanian R, Kumar MM, Ganthia BP, Kumar JS, Hemachandu P, Ramkumar MS. Smart grid based multiagent system in transmission sector. In2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) 2021 Sep 2 (pp. 1-5). IEEE.
9. Priyadarshini L, Kundu S, Maharana MK, Ganthia BP. Controller design for the pitch control of an autonomous underwater vehicle. Engineering, Technology & Applied Science Research. 2022 Aug 7;12(4):8967-71.
10. Zheng W, Mehbodniya A, Neware R, Wawale SG, Ganthia BP, Shabaz M. Modular unmanned aerial vehicle platform design: Multi-objective evolutionary system method. Computers and Electrical Engineering. 2022 Apr 1;99:107838.
11. Guo S, Li X, Guo Z, Zhao X, Meng S, Li Z. Polarization-independent optoelectronic modulator based on graphene ridge structure. Nanomaterials. 2021 Sep 29;11(10):2559.
12. Deng X, Li Z, Cao F, Hong E, Fang X. Woven fibrous photodetectors for scalable UV optical communication device. Advanced Functional Materials. 2023 Jun;33(23):2213334.
13. Guo FH, Hao LZ, Yu WZ, Li SQ, Liu GC, Hao JY, Liu YJ. High‐performance Si/VO2‐nanorod heterojunction photodetector based on photothermoelectric effect for detecting human radiation. Rare Metals. 2024 Mar;43(3):1177-85.