scholarly journals Charging Load Prediction and Distribution Network Reliability Evaluation Considering Electric Vehicles’ Spatial-Temporal Transfer Randomness

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Shan Cheng ◽  
Zhaobin Wei ◽  
Dongdong Shang ◽  
Zikai Zhao ◽  
Huiming Chen
Author(s):  
Guowei Li ◽  
Qinghui Zeng ◽  
Hao Liu ◽  
Junbo Wang ◽  
Rongbo Luo ◽  
...  

2014 ◽  
Vol 672-674 ◽  
pp. 1441-1446 ◽  
Author(s):  
Yu Qiang Ou ◽  
Le Feng Cheng ◽  
Jian Zhong Wen ◽  
Xuan Yu Qiu ◽  
Tao Yu

Research on reliability of distribution network has very important meaning and function to ensure the quality of power supply. This paper introduces some basic concepts of reliability in distribution network, including distribution network reliability definition, task and index. The classical reliability evaluation method was reviewed, and focused on specific distribution network, an example analysis was given, and specific reliability evaluation indexes were calculated. Finally, the future development of distribution network reliability evaluation was made a simple prospect.


2013 ◽  
Vol 448-453 ◽  
pp. 2503-2506
Author(s):  
Xin Zhang ◽  
Hong Liu ◽  
Li Mei Zhou

The access of distributed renewable energy enhances the uncertainty of the distribution network reliability, whereas the distribution network reliability evaluation using existing methods cannot fully reflect the stochastic volatility of islanding power supply and loads. For this reason the approach of active distribution network probabilistic reliability evaluation based on point estimation method was proposed. In the framework of Monte Carlo simulation, the islanding random variable was sampled and processed firstly; then the islanding probabilistic reliability was assessed with a nonlinear transformation method of independent random variables based on point estimate method; finally, system probabilistic reliability indexes can be obtained from the probabilistic superimposing of the results of repeating simulated failures. The simulation on the transformed multi-branch feeder model of the IEEE RBTS Bus6 verifies the validity and accuracy of this assessment approach.


2013 ◽  
Vol 341-342 ◽  
pp. 1380-1383
Author(s):  
Yan Yan Cui ◽  
Da Pu Zhao ◽  
Wei Liu ◽  
Yu Long

It is difficult to evaluate and analyze power supply reliability of large-scale medium voltage distribution network by detailed modeling method. The paper proposes a power supply reliability evaluation method of large-scale medium voltage distribution network, which is based on the network reliability characteristics model. Lines with similar structural characteristics are designated as one model. The reliability index of each mode can be represented by the typical lines. The assessment principle, process and the advantages of this method are elaborated. The medium voltage distribution network of Nanjing area is taken as an example to evaluate power supply reliability. And the results are compared with historical statistics. The result shows that the method can greatly reduce the workload and has high accuracy. It can be used to evaluate the reliability of large-scale medium voltage distribution network.


2021 ◽  
Vol 256 ◽  
pp. 01001
Author(s):  
Xiang Gao ◽  
Lingyan Wei ◽  
Bing Wang ◽  
Guiru Chen ◽  
Xiaoyue Wu

In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning.


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