Evaluation Index System and Comprehensive Evaluation Model of Power Quality Governance Effect in Distribution Station Area

Liang, Shuai; Yang, Yang; Zhang, Yifan; Li, He

doi:10.1109/icpsasia55496.2022.9949854

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…Wang et al (2018) proposed an electricity-user evaluation method in smart electricity utilization by integrating the entropy method and AHP. Liang et al (2022) proposed a governance effect evaluation model of power quality in distribution station areas based on the fuzzy comprehensive evaluation method, which uses the comprehensive weighting method combined with the AHP and entropy weight coefficient method to determine the index weight. The above works are only applicable to the performance evaluation of a single station area because the calculation process is very complicated, and the confidence degree of the evaluation results is ignored.…”

Section: Introductionmentioning

confidence: 99%

Confidence relative off-targets distance-based multi-dimensional transparency evaluation of distribution station area

Ren,

Li,

et al. 2024

Front. Energy Res.

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With the large-scale integration of distributed renewable energy into low-voltage distribution station areas, rapidly growing services put forward new requirements on transparent monitoring. In order to accurately and objectively quantify the transparency of various distribution station areas and measure the impact of different dimensional indexes on the transparency evaluation of distribution station areas, this paper proposes a confidence relative off-target distance-based multi-dimensional transparency evaluation method. First, a multi-dimensional transparency evaluation index system with electrical and communication integration is constructed. Second, an improved gray target model combining both positive and negative target vectors is established to realize bi-directional quantitative analysis. Then, the relative off-target distance is calculated based on the endowment coefficient by leveraging both subjective and objective weights. Finally, the confidence of the relative off-target distance is calculated based on fuzzy entropy to improve the reliability of transparency evaluation. The simulation results show that this method can effectively distinguish the transparency gap between different distribution station areas, identify the single dimensional index with the greatest contribution or potential, and verify the effectiveness of the proposed method applied to the transparency evaluation of distribution station areas.

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Section: Introductionmentioning

confidence: 99%