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  • Open Access

    ARTICLE

    Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

    Haoyi Zhong, Yongjiang Zhao, Chang Gyoon Lim*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1757-1781, 2024, DOI:10.32604/cmes.2024.049208

    Abstract This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery (LiB) time series data. As the energy sector increasingly focuses on integrating distributed energy resources, Virtual Power Plants (VPP) have become a vital new framework for energy management. LiBs are key in this context, owing to their high-efficiency energy storage capabilities essential for VPP operations. However, LiBs are prone to various abnormal states like overcharging, over-discharging, and internal short circuits, which impede power transmission efficiency. Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and… More >

  • Open Access

    ARTICLE

    Peer-to-Peer Energy Trading Method of Multi-Virtual Power Plants Based on Non-Cooperative Game

    Jingjing Bai*, Hongyi Zhou, Zheng Xu, Yu Zhong

    Energy Engineering, Vol.120, No.5, pp. 1163-1183, 2023, DOI:10.32604/ee.2023.025553

    Abstract The current electricity market fails to consider the energy consumption characteristics of transaction subjects such as virtual power plants. Besides, the game relationship between transaction subjects needs to be further explored. This paper proposes a Peer-to-Peer energy trading method for multi-virtual power plants based on a non-cooperative game. Firstly, a coordinated control model of public buildings is incorporated into the scheduling framework of the virtual power plant, considering the energy consumption characteristics of users. Secondly, the utility functions of multiple virtual power plants are analyzed, and a non-cooperative game model is established to explore the… More >

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