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Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation.

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This study introduces a novel processor system for photovoltaic power generation that enhances reliability and performance. The new system is 5.58 times more reliable and 26% faster than existing solutions.

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DMRMPPTTMRadaptive switchingreliability

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Renewable Energy Systems

Background:

  • Photovoltaic (PV) power generation control systems require high-performance processors for advanced maximum power point tracking (MPPT) algorithms.
  • Processor reliability in complex PV field environments is a critical challenge impacting system stability and efficiency.

Purpose of the Study:

  • To develop a novel processor system that balances high performance and reliability for PV power generation.
  • To address the limitations of traditional MPPT controllers in demanding environmental conditions.

Main Methods:

  • Designed a redundancy-mode switchable three-core processor system utilizing error rate and performance as joint switching metrics.
  • Developed optimization methods to enhance reliability while maintaining high performance.
  • Employed an error injection method and analyzed an error rate probability model for system verification.

Main Results:

  • The proposed system demonstrated a reliability approximately 5.58 times greater than non-fault-tolerant systems.
  • System performance was enhanced by 26% compared to highly reliable triple modular redundancy systems.
  • Efficient adaptive switching was achieved through joint statistical analysis of error rate and performance.

Conclusions:

  • The redundancy-mode switchable processor system significantly improves both reliability and performance in PV applications.
  • The approach offers a viable solution for the increasing computational demands and environmental challenges in PV power generation.
  • This work contributes to the development of more robust and efficient intelligent control systems for solar energy.