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Dynamic response analysis and control of power systems by combining differential equation models with power data

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Listed:
  • Jing Wang
  • Qiong Wang
  • Fangjun Li
  • Zhenfen Zhang
  • Jianyong Gao

Abstract

In response to the complex situation where the accuracy of describing the dynamic behaviour of the power system (PS) is low and the control strategy is difficult to cope with dynamic changes, this article combines differential equation models and power data to study the dynamic response analysis and control of the PS. Firstly, electricity data was collected from a certain power company, and the data was cleaned and standardised. Then, differential equation models were constructed for the generators, loads, and transmission lines in the PS, describing their dynamic behaviour and discretising the model. The MPC (Model Predictive Control) algorithm was used to define the objective function, set constraints, and solve the problem. The combination of differential equation modelling and MPC algorithm has improved the accuracy of describing the dynamic behaviour of the PS, and has good adaptability to complex dynamic changes, ensuring the safe and stable operation of the PS.

Suggested Citation

  • Jing Wang & Qiong Wang & Fangjun Li & Zhenfen Zhang & Jianyong Gao, 2026. "Dynamic response analysis and control of power systems by combining differential equation models with power data," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 48(1/2), pages 24-47.
    • Handle: RePEc:ids:ijgeni:v:48:y:2026:i:1/2:p:24-47
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