Proceedings of the 2nd International Conference on Public Management, Digital Economy and Internet Technology, ICPDI 2023, September 1–3, 2023, Chongqing, China

Research Article

Joint Modeling Analysis of Production and Operation Indicators for Power Grid Enterprises

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  • @INPROCEEDINGS{10.4108/eai.1-9-2023.2338791,
        author={Liyu  Xia and Wan  He and Qian  Zhang and Bingxin  Zeng},
        title={Joint Modeling Analysis of Production and Operation Indicators for Power Grid Enterprises},
        proceedings={Proceedings of the 2nd International Conference on Public Management, Digital Economy and Internet Technology, ICPDI 2023, September 1--3, 2023, Chongqing, China},
        publisher={EAI},
        proceedings_a={ICPDI},
        year={2023},
        month={11},
        keywords={power grid enterprise production and operation indicator management joint modeling prediction technology},
        doi={10.4108/eai.1-9-2023.2338791}
    }
    
  • Liyu Xia
    Wan He
    Qian Zhang
    Bingxin Zeng
    Year: 2023
    Joint Modeling Analysis of Production and Operation Indicators for Power Grid Enterprises
    ICPDI
    EAI
    DOI: 10.4108/eai.1-9-2023.2338791
Liyu Xia1,*, Wan He1, Qian Zhang1, Bingxin Zeng1
  • 1: State Grid Energy Research Institute
*Contact email: xialiyu@sgeri.sgcc.com.cn

Abstract

Production and operation management is an important means of resource integration, allocation, coordination, and utilization in power grid enterprises. At present, there have been significant changes in the operating environment and profit models of power grid enterprises. The external situation is becoming increasingly severe. Production and operation are subject to multiple constraints. This article introduces production and operation indicators and exogenous factor indicators, considering the random differences of each individual, and constructs a longitudinal data joint model. Use joint models to predict and analyze production and operation indicators. The empirical research shows that the joint model takes into account the correlation between indicators and the difference between individuals, which is superior to the single model in structure, and has better accuracy and dynamics in prediction.