Comprehensive assessment of power quality user opinion meter based on fuzzy clustering and hierarchical analysis approach

Power quality in renewable energy generation-based power systems faces challenges like complicated generation mechanisms and evolution law, which turns power quality comprehensive evaluation into significant work. This paper proposes a power quality comprehensive evaluation method based on fuzzy clustering and the analytic hierarchy process (AHP), which takes opinions from the load into account. Firstly, a comprehensive power quality evaluation index system is established based on the power quality standard and load opinion evaluation index. In addition, the evaluation index levels are classified. Secondly, the fuzzy clustering analysis method is used to evaluate each power quality index and generate dynamic data sources clustering to determine the best threshold of a single index. Lastly, the power quality comprehensive evaluation model is developed considering power quality opinions from the load side and their evaluation index weights. The engineering data calculation example verifies the accuracy and feasibility of the proposed power quality comprehensive evaluation model.