Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12–14, 2024, Ningbo, China

Research Article

Research on the Operation and Optimisation of Smart Power Plant System Based on Artificial Intelligence

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  • @INPROCEEDINGS{10.4108/eai.12-1-2024.2347283,
        author={Xuhui  Peng and Peng  Luo and Zhenqiang  Han and Junliu  Xiong},
        title={Research on the Operation and Optimisation of Smart Power Plant System Based on Artificial Intelligence},
        proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12--14, 2024, Ningbo, China},
        publisher={EAI},
        proceedings_a={BDEDM},
        year={2024},
        month={6},
        keywords={artificial intelligence; system optimisation; smart power plants; data processing; data updating},
        doi={10.4108/eai.12-1-2024.2347283}
    }
    
  • Xuhui Peng
    Peng Luo
    Zhenqiang Han
    Junliu Xiong
    Year: 2024
    Research on the Operation and Optimisation of Smart Power Plant System Based on Artificial Intelligence
    BDEDM
    EAI
    DOI: 10.4108/eai.12-1-2024.2347283
Xuhui Peng1,*, Peng Luo1, Zhenqiang Han1, Junliu Xiong1
  • 1: PowerChina Jiangxi Electric Power Engineering Co., Ltd
*Contact email: jxepdi-pengxuhui@powerchina.cn

Abstract

This thesis constructs an intelligent power big data algorithm selection and evaluation system by investigating the evaluation and selection methods of supervised machine learning algorithms related to power big data. Based on the big data background of artificial intelligence, in order to make the system more suitable for the needs of power big data analysis, this paper needs to carry out an artificial pre-assessment of the mainstream machine learning algorithms to determine the key machine learning algorithms for power big data, and for this reason, it is necessary to construct a machine learning algorithm index system. The process of constructing the indicator system is to select a number of interrelated statistical indicators to form the indicator system. The principles that should be followed in selecting the indicators are the principle of purpose, the principle of comprehensiveness, the principle of feasibility, the principle of stability, the principle of coordination and the principle of integration. The principle of coordination and the principle of integration.