performance evaluation method
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2022 ◽  
Vol 40 (1) ◽  
pp. 35-53
Author(s):  
Yasushi Nitta ◽  
Shinichi Yuta ◽  
Satoshi Takewaka ◽  
Takashi Ohtsuki ◽  
Koji Kondou ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Cuiping Li ◽  
Zheshen Zhang ◽  
Junhui Li ◽  
Yunbao Ma ◽  
Jiajun Zou

Because of wind sources’ volatility and intermittent news, wind power has made a more and more heavy burden on the power system. This paper analyzes in detail the traditional control method, parallel control strategy and serial control strategy of the wind storage system, and combines the advantages of the two to propose an optimal control strategy. A comprehensive performance evaluation method for the primary frequency regulation of the ESS participating in the power grid is proposed based on the power system operation requirements. In the example, the frequency modulation performance of the optimal control strategy is verified by the evaluation method described in this paper in the Chinese frequency adjustment market.


Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2126
Author(s):  
Xixia Sun ◽  
Chao Cai ◽  
Su Pan ◽  
Nan Bao ◽  
Ning Liu

This paper proposes a university teachers’ teaching performance evaluation method based on type-II fuzzy sets (T2 FSs), which solves the problems of fuzziness, complexity and uncertainty in teaching performance evaluation. Firstly, the evaluation indicator system is constructed from the aspects of teaching attitude, teaching contents, teaching professionalism, teaching methods and teaching effects. Then, T2 FSs theory and the perceptual computing method are introduced to model subjective judgments and capture uncertainties, effectively handling higher levels of uncertainty in the evaluation process. Furthermore, the linguistic weighted average operator is applied as the computing with words engine to aggregate scores and weights of indicators, which effectively integrates the uncertain information in the input data into the final evaluation conclusion and guarantees the accuracy of the evaluation results. Finally, the effectiveness of the method of this study is evaluated by simulation experiments. The computational results demonstrate that it can capture more uncertain and complex information, and is more accurate and reliable than the type-I fuzzy sets method.


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