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Low-carbon power demand forecasting models for the performance optimization of new energy robotics systems

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  • HuiMing Zhang
  • CuiFang Zhang

Abstract

To improve the performance of new energy-powered robots, a method for optimizing the performance of new energy-powered robots has been proposed, based on a low-carbon power demand forecasting model. The approach advocated leveraging low-carbon power demand to optimize power system design and control strategies. Then, a model for forecasting robotic power demands was established, alongside the refinement of the power system evaluation mechanism. Results indicated a significant correlation between operational parameters linked to low-carbon power demand and system performance. The precision of our model was notably high, enabling the provision of specific performance optimization strategies tailored to diverse low-carbon contexts.

Suggested Citation

  • HuiMing Zhang & CuiFang Zhang, 2025. "Low-carbon power demand forecasting models for the performance optimization of new energy robotics systems," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 341-352.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:341-352.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf006
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