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This paper studies a power system prediction model based on expert system, which aims to simulate the reasoning process of industry experts in order to predict the future trend of new power systems. By integrating data collection, pre-processing, knowledge base construction, and social network analysis techniques, the model identifies key keywords such as control strategy, virtual power plant, and energy storage. The findings reveal potential hotspots for new power systems, such as low-carbon technologies and renewable energy. Combining expert knowledge with historical data, the model uses logical reasoning and pattern recognition to provide researchers and decision makers with insights that can help anticipate and guide the development of new power systems.

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A New Power System Prediction Model Based on Expert System

  • 会议论文

  • 发表日期：

    2025年

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  • Wei Wang,
  • Yanbo Wang,
  • Tongxuan Chen,
  • Zhuo Yang

摘要

This paper studies a power system prediction model based on expert system, which aims to simulate the reasoning process of industry experts in order to predict the future trend of new power systems. By integrating data collection, pre-processing, knowledge base construction, and social network analysis techniques, the model identifies key keywords such as control strategy, virtual power plant, and energy storage. The findings reveal potential hotspots for new power systems, such as low-carbon technologies and renewable energy. Combining expert knowledge with historical data, the model uses logical reasoning and pattern recognition to provide researchers and decision makers with insights that can help anticipate and guide the development of new power systems.