Requirement and Practice of Supply Chain Information Monitoring and Operation Planning for Large Energy Enterprises

In recent years, with the accelerated innovation of Internet, big data, cloud computing, artificial intelligence, blockchain and other technologies, and increasingly integrated into the whole process of economic and social development and energy, the digital economy has developed rapidly, with a wide range of radiation and unprecedented influence, and is becoming a key force in reconstructing global factor resources and reshaping the global economic structure. Change the global competition pattern. In this context, it is urgent for energy enterprises to carry out innovation, efficiency and power changes. It is of great significance to promote the development of energy enterprises in the direction of integration, intelligence and efficiency based on information transformation and big data science and technology as a powerful means. The energy industry needs to change the development mode driven by extensive investment and high-density investment, continuously improve the synergy efficiency of total factor production, improve the ability of intelligent scheduling and risk perception, and realize the high-quality and rapid development of the whole industry. Under the background of digital transformation, the core business support of energy enterprises extends to the direction of integration and coordination, the operation mode changes from “planned scheduling” to “real-time scheduling”, and the management means changes from “online” to “intelligent” to ensure the integrated and high-quality operation of energy enterprises.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865300
Primary Topic
Power Systems and Technologies
Type
article
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Requirement and Practice of Supply Chain Information Monitoring and Operation Planning for Large Energy Enterprises

Weiying Xu, Shishuai Zhang, Zhen Xing Kong, Hongyan Wang et al.
Power Systems and Technologies
article

Requirement and Practice of Supply Chain Information Monitoring and Operation Planning for Large Energy Enterprises

Weiying Xu, Shishuai Zhang, Zhen Xing Kong, Hongyan Wang, Hailong Zhang, Zhuang Ding
article en

Abstract

In recent years, with the accelerated innovation of Internet, big data, cloud computing, artificial intelligence, blockchain and other technologies, and increasingly integrated into the whole process of economic and social development and energy, the digital economy has developed rapidly, with a wide range of radiation and unprecedented influence, and is becoming a key force in reconstructing global factor resources and reshaping the global economic structure. Change the global competition pattern. In this context, it is urgent for energy enterprises to carry out innovation, efficiency and power changes. It is of great significance to promote the development of energy enterprises in the direction of integration, intelligence and efficiency based on information transformation and big data science and technology as a powerful means. The energy industry needs to change the development mode driven by extensive investment and high-density investment, continuously improve the synergy efficiency of total factor production, improve the ability of intelligent scheduling and risk perception, and realize the high-quality and rapid development of the whole industry. Under the background of digital transformation, the core business support of energy enterprises extends to the direction of integration and coordination, the operation mode changes from “planned scheduling” to “real-time scheduling”, and the management means changes from “online” to “intelligent” to ensure the integrated and high-quality operation of energy enterprises.

Digital China Health (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Power Systems and Technologies
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Requirement and Practice of Supply Chain Information Monitoring and Operation Planning for Large Energy Enterprises — Weiying Xu, Shishuai Zhang, et al. · (2024) | TGRS Research Map | TGRS