Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China

Research Article

A Forecasting Model for Fixed Assets Depreciation in Chinese Provincial Power Grid Enterprises

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  • @INPROCEEDINGS{10.4108/eai.2-12-2022.2327937,
        author={Yang  Li and Qian  Zhao and Yang  Wang and Linkun  Man},
        title={A Forecasting Model for Fixed Assets Depreciation in Chinese Provincial Power Grid Enterprises},
        proceedings={Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China},
        publisher={EAI},
        proceedings_a={ICICA},
        year={2023},
        month={3},
        keywords={existing assets; incremental assets; influencing factors; depreciation forecasting},
        doi={10.4108/eai.2-12-2022.2327937}
    }
    
  • Yang Li
    Qian Zhao
    Yang Wang
    Linkun Man
    Year: 2023
    A Forecasting Model for Fixed Assets Depreciation in Chinese Provincial Power Grid Enterprises
    ICICA
    EAI
    DOI: 10.4108/eai.2-12-2022.2327937
Yang Li1,*, Qian Zhao1, Yang Wang2, Linkun Man3
  • 1: State Grid Energy Research Institute Co., Ltd
  • 2: State Grid Liaoning Electric Power Co., Ltd
  • 3: State Grid Liaoning Electric Power Company, Limited Institute of Economics and Technology
*Contact email: liyang@sgeri.sgcc.com.cn

Abstract

The depreciation scale of fixed assets is an important parameter that affects the operational profits of power grid enterprises and transmission and distribution pricing. The forecasting of depreciation scale is of immense significance for power grid enterprises to comprehend their profitability and the transmission and distribution pricing trends, in advance. In this paper, we analyze the main factors affecting the depreciation level of fixed assets in provincial power grids, distinguish the structure of existing assets and incremental assets, build a depreciation forecasting model, and further conduct an empirical study to quantitatively analyze the influence of different business strategies on depreciation. The study results can support management and decision-making optimization of power grid assets and provide support for scientific decision-making by government departments.