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Evaluation Technology of Power Regulation Data Assets

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Digital Multimedia Communications (IFTC 2022)

Abstract

With the rapid development of the Internet and big data technology and the in-depth application in the field of power regulation, power regulation data shows explosive growth. Power regulation data runs through all aspects of power dispatching production and management. After years of operation, various business systems have accumulated rich information resources, which can bring huge profits to power grid enterprises. At present, the management and operation mode of data is relatively rough, and it is still used and managed by various business departments. As an intangible asset, the value of data has not been paid enough attention and deeply explored. Based on the characteristics of power regulation data and the factors affecting the value of data assets, combined with traditional evaluation algorithms, this paper studies the data asset value evaluation methods applicable to the field of power regulation; Based on the improved value evaluation method, a data asset evaluation model covering the cost, intrinsic value and use value of power regulation data is established to provide basic support for reasonable determination of big data asset value.

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Acknowledgment

This work is supported by Science and Technology Program of State Grid Corporation of China under Grant No. 5442DZ210027.

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Correspondence to Yan Wang .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, Y. et al. (2023). Evaluation Technology of Power Regulation Data Assets. In: Zhai, G., Zhou, J., Yang, H., Yang, X., An, P., Wang, J. (eds) Digital Multimedia Communications. IFTC 2022. Communications in Computer and Information Science, vol 1766. Springer, Singapore. https://doi.org/10.1007/978-981-99-0856-1_40

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  • DOI: https://doi.org/10.1007/978-981-99-0856-1_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0855-4

  • Online ISBN: 978-981-99-0856-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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