Abstract
The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM), due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP) and Dempster–Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster–Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment.
Highlights
As a key piece of equipment in power systems, the power transformer comprises up to 60% of the total investment in substations and affects the safety and stability of power supply [1,2]
Based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers
A novel Multi-attribute decision-making (MADM) model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, is adopted to evaluate the health condition of transformers in this paper
Summary
As a key piece of equipment in power systems, the power transformer comprises up to 60% of the total investment in substations and affects the safety and stability of power supply [1,2]. Many techniques, such as neural network [7], support vector machine [8] and fuzzy logic [9], were applied to transformer fault diagnosis. These approaches usually focused on a single factor (e.g., DGA analysis, thermal modeling, winding fault analysis, etc.). Results indicated that these research works could evaluate the transformer fault condition effectively to a certain extent. These attempts were not sufficient to obtain an overall and precise health condition of the transformers [5,6]. It is difficult for power utilities to obtain accurate evaluation results due to varied information sources from transformers, which can be regarded as an MADM problem [5,6]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
