Research on Access Point and Capacity Selection Optimization of Distributed Photovoltaic Access to Distribution Network for Network Loss

Author(s):  
Qinghan Wang ◽  
Yun Teng
2019 ◽  
Vol 9 (12) ◽  
pp. 2401
Author(s):  
Zhongdong Yin ◽  
Jingjing Tu ◽  
Yonghai Xu

The large-scale access of distributed generation (DG) and the continuous increase in the demand of electric vehicle (EV) charging will result in fundamental changes in the planning and operating characteristics of the distribution network. Therefore, studying the capacity selection of the distributed generation, such as wind and photovoltaic (PV), and considering the charging characteristic of electric vehicles, is of great significance to the stability and economic operation of the distribution network. By using the network node voltage, the distributed generation output and the electric vehicles’ charging power as training data, we propose a capacity selection model based on the kernel extreme learning machine (KELM). The model accuracy is evaluated by using the root mean square error (RMSE). The stability of the network is evaluated by voltage stability evaluation index (Ivse). The IEEE33 node distributed system is used as simulation example, and gives results calculated by the kernel extreme learning machine that satisfy the minimum network loss and total investment cost. Finally, the results are compared with support vector machine (SVM), particle swarm optimization algorithm (PSO) and genetic algorithm (GA), to verify the feasibility and effectiveness of the proposed model and method.


2019 ◽  
Vol 9 (14) ◽  
pp. 2871
Author(s):  
Guopeng Zhao ◽  
Jiaxing Liu ◽  
Siyuan Liu ◽  
Xinwei Zhou ◽  
Jihong Li ◽  
...  

With the aim of improving the consumption capacity of distributed generation (DG) in the distribution network, the control strategy of the flexible multi-state switch (FMSS) for the maximum consumption of distributed generation is proposed. The principle that FMSS improves the consumption capacity of distributed generation is analyzed and verified by simulation. The estimating method for the maximum accessible capacity of distributed generation at the access point is proposed. For complex systems, the multi-objective function for maximizing the consumption of distributed generation was established, and the analytic hierarchy process and entropy weight method were combined to obtain the weight factor. Then, combined with system constraints, the results can be obtained by optimization algorithms. Finally, the control strategy of FMSS for maximum consumption of distributed generation was realized and verified in a simulation.


2014 ◽  
Vol 716-717 ◽  
pp. 1148-1155
Author(s):  
Dong Mei Zhao ◽  
Xin Wang

This paper is focused on technical features of large-capacity distributed power generation and takes the example 33 in distribution system as illustration. What is more, the paper analyzes how injection capacity and access locations of distributed generation can affect voltage and network losses. The analysis carries out the trend that indicators changing regarding to change in injection capacity and access locations. Take a typical distribution network of 10kV with distributed power for example, and analysis what affect will happen to the access point upstream, downstream and adjacent current protection that brings by the distributed generation. It is concluded that the main factor that restrains distributed power capacity in photovoltaic power generation is voltage fluctuation and the relay operation of distributed system.


2021 ◽  
Vol 2087 (1) ◽  
pp. 012074
Author(s):  
Bingsen Xia ◽  
Yuanchun Tang

Abstract the paper introduces IRS to assist offloading, and the propagation Environment can be intelligently changed by changing the reflection unit of the IRS, This article proposes an IRS-assisted MEC power distribution Internet of Things system, and studies the gain effect of IRS in the MEC system. In this system, the single antenna equipment can choose to unload a small part of its computing task to the edge computing node of the distribution Internet of things through the multi antenna access point with the help of IRS. In this paper, the delay minimization problem of the whole system is established, the DNQ reinforcement learning algorithm is used to solve the problem, which can effectively change the coverage of smart substations.


2004 ◽  
Vol 171 (4S) ◽  
pp. 502-502 ◽  
Author(s):  
Brian R. Matlaga ◽  
Steve J. Hodges ◽  
Ojas Shah ◽  
Dean G. Assimos

2009 ◽  
Vol 129 (6) ◽  
pp. 733-744 ◽  
Author(s):  
Shoji Kawasaki ◽  
Yasuhiro Hayashi ◽  
Junya Matsuki ◽  
Hirotaka Kikuya ◽  
Masahide Hojo

2012 ◽  
Vol 132 (10) ◽  
pp. 853-861 ◽  
Author(s):  
Takuya Ishitani ◽  
Ryoichi Hara ◽  
Hiroyuki Kita ◽  
Eiji Kogure ◽  
Yuki Mitsukuri ◽  
...  

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