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Data Value-Added Service Comprehensive Evaluation Method on the Performance of Power System Big Data

Author

Listed:
  • Hao Zhang

    (State Grid Jibei Electric Power Co., Ltd., Beijing 100054, China)

  • Ye Liang

    (Beijing Kedong Electric Power Control System Co., Ltd., Beijing 100192, China)

  • Hao Zhang

    (State Grid Jibei Electric Power Co., Ltd., Beijing 100054, China)

  • Jing Wang

    (Beijing Kedong Electric Power Control System Co., Ltd., Beijing 100192, China)

  • Yuanzhuo Li

    (State Grid Jibei Electric Power Co., Ltd., Beijing 100054, China)

  • Xiaorui Rong

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Hongda Gao

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

With the development of digital economy, the integration and secure sharing of energy big data have become pivotal in driving innovation across the energy production, distribution, and consumption sectors. For power enterprises, leveraging data to enhance operational efficiency and drive business development will play a crucial role in value added. Firstly, based on the value-added service framework system of grid enterprises, this paper explores the basic technologies for power data applications and designs a technical roadmap for value-added services. Secondly, the proposed methodology incorporates the analytic hierarchy process (AHP) and gray comprehensive evaluation method (GCE) to determine the weights of key factors affecting the value-added services. Empirical research is conducted to validate the feasibility of typical value-added services. Additionally, this paper proposes methods for evaluating the benefits of value-added services and identifies key technologies in data mining and management, customer value discovery, and data asset utilization, providing theoretical support and practical pathways for the digital transformation of power enterprises.

Suggested Citation

  • Hao Zhang & Ye Liang & Hao Zhang & Jing Wang & Yuanzhuo Li & Xiaorui Rong & Hongda Gao, 2025. "Data Value-Added Service Comprehensive Evaluation Method on the Performance of Power System Big Data," Energies, MDPI, vol. 18(3), pages 1-26, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:3:p:700-:d:1582858
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    References listed on IDEAS

    as
    1. Ron Adner & Rahul Kapoor, 2010. "Value creation in innovation ecosystems: how the structure of technological interdependence affects firm performance in new technology generations," Strategic Management Journal, Wiley Blackwell, vol. 31(3), pages 306-333, March.
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