Stability Enhancement of a Power System With a PMSG-Based and a DFIG-Based Offshore Wind Farm Using a SVC With an Adaptive-Network-Based Fuzzy Inference System

2013 ◽  
Vol 60 (7) ◽  
pp. 2799-2807 ◽  
Author(s):  
Li Wang ◽  
Dinh-Nhon Truong
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peilin Lv ◽  
Rong Zhen ◽  
Zheping Shao

Offshore wind power is an effective way to solve the energy crisis problem and achieve sustainable economic development. Aiming at the problems that the navigational risk of ships in the waters of offshore wind farms is difficult to quantify due to complex factors, this paper proposes a method of navigational risk assessment in the waters of offshore wind farms based on a fuzzy inference system. Firstly, through the analysis of the factors affecting the navigation system of wind farm waters, it is found that the navigational risk is affected by natural factors and navigational environment factors. Then, the visibility, the number of traffic flows, the number of encounter areas, and the distance between the sailing route and the wind farm are extracted to evaluate the risk of natural factors and the risk of the sailing environment in the navigation system of the wind farm waters, respectively. Considering the mutual influence of the factors, the fuzzy inference rules of navigational risk influence are established according to the expert experience, and a method of navigational risk assessment based on the fuzzy inference system in offshore wind farm waters is developed. In order to verify the effectiveness of the proposed method, a comprehensive evaluation of the navigational risk of wind farm waters in Changle offshore sea of Fujian Province is carried out, and the evaluation results are consistent with the actual situation. The proposed method has important theoretical significance for the navigational safety supervision of offshore wind farm waters.


2019 ◽  
Vol 139 (4) ◽  
pp. 259-268
Author(s):  
Effat Jahan ◽  
Md. Rifat Hazari ◽  
Mohammad Abdul Mannan ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
...  

2021 ◽  
pp. 004051752110205
Author(s):  
Xueqing Zhao ◽  
Ke Fan ◽  
Xin Shi ◽  
Kaixuan Liu

Virtual reality is a technology that allows users to completely interact with a computer-simulated environment, and put on new clothes to check the effect without taking off their clothes. In this paper, a virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System (ANFIS), VFE-ANFIS for short, is proposed. There are two stages of the VFE-ANFIS: training and evaluation. In the first stage, we trained some key pressure parameters by using the VFE-ANFIS; these key pressure parameters were collected from real try-on and virtual try-on of pants by users. In the second stage, we evaluated the fit by using the trained VFE-ANFIS, in which some key pressure parameters of pants from a new user were determined and we output the evaluation results, fit or unfit. In addition, considering the small number of input samples, we used the 10-fold cross-validation method to divide the data set into a training set and a testing set; the test accuracy of the VFE-ANFIS was 94.69% ± 2.4%, and the experimental results show that our proposed VFE-ANFIS could be applied to the virtual fit evaluation of pants.


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