Research on Applications of Artificial Intelligence(AI) in Business Management of Power Grid Enterprises

Research on Applications of Artificial Intelligence(AI) in Business Management of Power Grid Enterprises

Table of Contents




Abstract

Due to the fast development of deep learning, products, and services based on artificial intelligence (AI) have been transformed from concept to reality. However, there still exist huge challenges when applying AI technologies in traditional industrial enterprises. This paper studies those key technologies that support business management applications from the power grid enterprise perspective, where state-of-the-art use cases have been investigated. Finally, potential developing trends of business management are foreseen by considering the innovation of AI technologies.

 

  • Author Keywords

    • Artificial intelligence(AI),
    • business management,
    • power grid enterprise,
    • speech recognition,
    • natural language processing,
    • image and video recognition,
    • knowledge graph
  • IEEE Keywords

    • Artificial intelligence(AI),
    • Speech recognition,
    • Companies,
    • Image recognition,
    • Power grids,
    • Natural language processing

 

Introduction

After AlphaGo conquered the world with sophisticated decision-making techniques and advanced intelligence, artificial intelligence (AI) has attracted considerable interests and intentions from the government, academy, and industries [1], [2]. China, America, European Unions, Japan, and Korea have all promulgated AI development strategies, with the aim of leading advanced information and communication technologies. Meanwhile, the submitted papers of top AI conferences have increased dramatically in recent years, e.g., IEEE Conference on Computer Vision and Pattern Recognition (CVPR), AAAI Conference on Artificial Intelligence (AAAI), and Annual Conference on Neural Information Processing Systems (NeurIPS) [3]. In addition, both the giant companies (e.g., Google, Alibaba) and unicorn companies (Tesla, SenseTime) have made great efforts to accelerate the adoption of AI technologies. Google Assistant, Alice customer service robot, Tesla autonomous driving system, SenseTime smart city solution have made great business success. Investors and consulting companies closely track artificial intelligence technology and industry application development.

As the pioneer power, internet companies and financial companies have shown their ambitions to apply AI techniques and looked for new business opportunities. However, the application and adoption of AI in the industry have not yet attracted enough attention. Experts and researchers argued that AI can enhance the efficiency and reliability of industrial production, operation, and maintenance with other information technologies, e.g., internet of things, 5G communication. A lot of white papers focus on AI architecture and application. However, there exist few surveys work on the adoption and application in the power grid. Although a lot of studies focus on AI methods in power generation, transmission, distribution, and usage, there still exist few studies on AI adoption and application in the business management of power grid enterprises.

State Grid Corporation of China Co, Ltd. (SGCC) is the largest public service enterprises in the world. Some use cases with AI technologies that have been implemented by the branch companies of SGCC. It is necessary to collect these use cases. Meanwhile, there exist common demands among companies with different areas in the business management area. Thus, it is meaningful to collect the use cases and decide the utilization of such cases in power grid enterprises. Besides the aforementioned cases, more intelligent applications can be realized with the fast development of AI technology in the near future. Thus, we shall investigate future applications in the business management of power grid enterprises. The main contributions are summarized as follows: 1) We analyze the key AI technologies that support business management: speech recognition, natural language processing, image, and video recognition, and knowledge graph. 2) We investigate the use of cases of business management in power grid enterprises and other enterprises. 3) We analyze future trends of AI applications in the business management of power grid enterprises. The remainder of this paper is organized as follows: Section II investigates the key AI techniques to support business management in enterprises. In Section III, we present the existing application cases and show how AI technologies help enterprises improve business management. In Section IV, the trend analysis of business management in power grid enterprises is given.

Conclusion

In this paper, we present key AI technologies used in business management. Then, we investigate the state-of-arts AI use cases to inspire power grid enterprises. Finally, we point out the future trend of AI applications in the business management area. In future work, we plan to track the latest trends and application cases and prepare a survey of AI applications in the business management of power grid enterprises.

Acknowledgment

This work is supported by State Grid Company Research Project under grant 5455HJ1800011 (The research on technical system and application of artificial intelligence in power systems) and Research Project of Ministry of Industry and Information Technology (Analysis of Application Status and Development Trend of Artificial Intelligence in Electric Power Field).

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FULL Paper PDF file:

Research on Applications of Artificial Intelligence in Business Management of Power Grid Enterprises

Bibliography

author

B. Chai, Q. Zhang, Q. Chen, T. Zhao and K. Gao,

Year

2019

Title

Research on Applications of Artificial Intelligence in Business Management of Power Grid Enterprises,

Publish in

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chengdu, China, 2019, pp. 683-688,

Doi

10.1109/IAEAC47372.2019.8997608

PDF reference and original file: Click here

 

 

 

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Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.

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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.