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DONG Fugui, XI Ziyue, WANG Peijun, et al. Comprehensive evaluation and application of standard data sources for new power system based on enhanced multi-criteria decision-makingJ. Electric Power, 2026, 59(10): 1−12. DOI: 10.11930/j.issn.1004-9649.202601057
Citation: DONG Fugui, XI Ziyue, WANG Peijun, et al. Comprehensive evaluation and application of standard data sources for new power system based on enhanced multi-criteria decision-makingJ. Electric Power, 2026, 59(10): 1−12. DOI: 10.11930/j.issn.1004-9649.202601057

Comprehensive evaluation and application of standard data sources for new power system based on enhanced multi-criteria decision-making

  • Establishing a scientific and comprehensive technical standard system is the foundation for ensuring the safe and efficient operation. The systematic evaluation of standard data sources is directly related to the scientificity and applicability of standard formulation. To address the problems of diverse sources, significant quality disparities and the absence of unified screening criteria for standard data sources, this study proposes a comprehensive evaluation method for technical standard data sources of the new power system based on improved multi-criteria decision-making. Firstly, an evaluation indicator system for data sources is constructed from four dimensions: data quality, relevance, update and maintenance, and accessibility. Secondly, indicator weights are determined by integrating subjective judgments with objective data characteristics, and the multi-criteria decision-making method is adopted to perform comprehensive ranking and grade classification for various data sources. Finally, an empirical analysis is conducted, taking a municipal power company as a case study. The findings indicate that completeness and scenario-relevance obtain the highest indicator weights, reaching 13.43% and 12.32%, respectively. Four platforms including the National Full-text Open System for Standards are rated as excellent-grade data sources, which can serve as priority access objects for the construction of technical standard data sources of power enterprises in similar provincial-municipal regions. This study achieves quantitative ranking and hierarchical management of multi-tiered standard data sources, addresses the lack of a unified evaluation framework and quantitative basis for the optimal selection of standard data sources, and provides an actionable decision-making tool for the digital construction and dynamic optimization of the new power system standard system.
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