2018•Unpublished venueRequires access

Fuzzy Comprehensive Evaluation of Power Quality Based on State Variable Weight and Normal Cloud Model

Cheng Lv, Lijun Tian, Zhiguo Wang

Open publisher page 5 citations

Abstract

Objective and accurate comprehensive evaluation on power quality is an important evidence for power pricing and power quality assessment. Considering the shortcomings existing in current methods, state variable weight and normal cloud model are used to improve the fuzzy comprehensive evaluation method of power quality. The state variable weight vector is applied to consider the influence of the actual condition of evaluation indicators on the indicator weights, and the normal cloud model is applied to construct the membership function. The asymmetric proximity criterion is used to obtain the quantitative and qualitative assessment results. Finally, the accuracy and effectiveness of the proposed method are verified by a practical example.

About this research paper

What this paper is about

Objective and accurate comprehensive evaluation on power quality is an important evidence for power pricing and power quality assessment. Considering the shortcomings existing in current methods, state variable weight and normal cloud model are used to improve the fuzzy comprehensive evaluation method of power quality. The state variable weight vector is applied to consider the influence of the actual condition of evaluation indicators on the indicator weights, and the normal cloud model is applied to construct the membership function. The asymmetric proximity criterion is used to obtain the quantitative and qualitative assessment results. Finally, the accuracy and effectiveness of the proposed method are verified by a practical example.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Objective and accurate comprehensive evaluation on power quality is an important evidence for power pricing and power quality assessment. Considering the shortcomings existing in current methods, state variable weight and normal cloud model are used to improve the fuzzy comprehensive evaluation method of power quality. The state variable weight vector is applied to consider the influence of the actual condition of evaluation indicators on the indicator weights, and the normal cloud model is applied to construct the membership function. The asymmetric proximity criterion is used to obtain the quantitative and qualitative assessment results. Finally, the accuracy and effectiveness of the proposed method are verified by a practical example.

Key concepts: Fuzzy logic, Cloud computing, Computer science, Variable (mathematics), Data mining, Construct (python library), Fuzzy set, Power (physics)

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