A Digital Twin Technology-Based Optimization Method for Energy Storage Evaluation of New Energy Power Systems

In new energy power systems, the stability and optimization evaluation of energy storage technology is of great importance, and digital twin technology can provide for the rapid, safe and low-cost development and optimization of energy storage systems. Various models are used in this paper. For example, fuzzy integrated evaluation, factor analysis, gray correlation analysis, Pearson correlation, particle swarm algorithm, simulated annealing and neural network prediction are implemented to comprehensively evaluate and predict the characteristics of different energy storage technologies. We also contribute to the energy storage technology for new energy power systems by verifying the usefulness of the technology for energy storage systems through real data.

• Publication year

  2023

• Venue

  2023 3rd International Conference on Energy Engineering and Power Systems (EEPS)

• Publication date

  2023-07-28

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/EEPS58791.2023.10256990
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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