Stability Analysis and Optimization of Power System in New Energy Grid Connection Control

Authors

  • Changgui Chen Power China Chengdu Engineering Corporation Limited, Chengdu 611130, Sichuan, China
  • Lili Wang Power China Chengdu Engineering Corporation Limited, Chengdu 611130, Sichuan, China
  • Chao Deng Power China Chengdu Engineering Corporation Limited, Chengdu 611130, Sichuan, China
  • Jianhong Jiang Power China Chengdu Engineering Corporation Limited, Chengdu 611130, Sichuan, China
  • Shunhong Zhong Power China Chengdu Engineering Corporation Limited, Chengdu 611130, Sichuan, China

Abstract

In response to the challenges that the volatility and uncertainty of new energy pose to the stability of the power system, this study applied the Long Short-Term Memory (LSTM) algorithm to establish a prediction model for new energy generation. By combining historical data and meteorological information, the stability of the system was analyzed in depth. The LSTM model adopted a multi-layer stacked structure, with the input layer receiving multidimensional features from the SDWPF (Spatial Dynamic Wind Power Forecasting) dataset and using 128 hidden units to capture dynamic features in the time series. This study combined Adam optimizer to improve training efficiency and introduced the Dropout mechanism to reduce the risk of overfitting. Based on the prediction results of LSTM, this study designed dynamic scheduling and energy storage system optimization strategies to
improve the stability of the power system. The dynamic dispatch strategy adjusted the power generation of the generator sets in real-time to match the load demand, and the energy storage system smooths wind power fluctuations by means of charge and discharge management, thereby maintaining the stability of the grid frequency and voltage. Experimental data show that the LSTM model performs well in terms of prediction, with a mean square error as low as 0.0021 and a mean absolute error of 0.037. When the wind speed fluctuates at low speeds, the dispatch strategy stabilizes within 5 seconds; when the fluctuation is high, the adjustment time and error increase. The energy storage system responds well to low fluctuations; but although it responds quickly to high fluctuations, it has reduced stability, highlighting the advantages and disadvantages of each strategy under different conditions.


Keywords: new energy stability, LSTM algorithm, power system dispatch, energy storage system optimization, load management

Cite As

C. Chen, L. Wang, C. Deng, J. Jiang, S. Zhong, "Stability Analysis and Optimization of Power System in New
Energy Grid Connection Control", Engineering Intelligent Systems, vol. 33 no. 6, pp. 621-630, 2025.

 

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Published

2025-11-01

Issue

Vol. 33 No. 6 (2025): International Journal of Engineering Intelligent Systems

Section

Article

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