Power Flow Calculation of Distribution Network Considering Distributed Generation Switch-In

2011 ◽  
Vol 71-78 ◽  
pp. 2470-2474
Author(s):  
Zhen Li ◽  
Cai Hong Zhao ◽  
Cheng Fei Ma

Firstly, the present paper makes a brief introduction to types of the distributed power and the processing mode of PV node in the electricity grid; secondly, the forward and backward substitution method to calculate the power flow has been improved and used to analyze some examples; thirdly and most importantly, taking the multi-node distribution network which incorporates distributed generation (DG) as an example, the author analyzes the influences of DG on load flow distribution and network loss in different positions, capacities and power factors.

2012 ◽  
Vol 614-615 ◽  
pp. 862-865
Author(s):  
Qing Qi Zhao ◽  
Xue Chen ◽  
Yi Yang ◽  
Ji Guang Xue

With the injection of distributed generation (DG) into distribution network, complexity and uncertainty of power flow in distribution network follow. In order to calculate power flow more simply and accurately, considering the characteristics of distribution network with DG and the flexible applicability of RBF neural network, a special adaptive dynamic clustering RBFNN (DG-RBFNN) method, which clusters the input samples only according to the parameters associated with DG, has been used in this paper. Therefore, the results are more approximate to the real condition and the calculation process is simpler compared with conventional back/forward (B/F) method meanwhile the calculation scale is also relatively smaller compared with ordinary adaptive dynamic clustering RBFNN. Finally, according to a 21-bus 66 kV distribution network of Shenyang, Liaoning province simulation experiment, the availability of DG-RBFNN method is proved.


2013 ◽  
Vol 391 ◽  
pp. 295-300 ◽  
Author(s):  
Na Li ◽  
Yong Gang Li ◽  
Qing Jie Zhou

The introduction of distributed generation (DG) into distribution network will greatly impact on its operation and security inevitably, load flow calculation with distributed generations is the basic premise for the optimization planning and operation of distribution network, so the power flow in distribution network containing DG should be calculated .This paper analyzes several common DG in the former back flow calculation and mathematical model, with the first generation method fail to deal with PV node problem, improves back/forward substitution method based on node-layer, the branch search method is presented to form node impedance matrix to modify the PV node reactive injection. so that it can effectively deal with PV nodes, and the program written by matlab7.1, several schemes are designed for the different modes of DGS and are tested in IEEE33 node system and verifies the feasibility of the method, the reliability of the program.


Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 1094-1106 ◽  
Author(s):  
Zhen Li ◽  
Yao Zhang ◽  
Muhammad Aqeel Ashraf

Abstract Distribution network reconfiguration is a very complex and large-scale combinatorial optimization problem. In network reconfiguration, whether an effective solution can be obtained is a key issue. Aiming at the problems in network reconstruction by traditional algorithm, such as long time required, more times of power flow calculation and high network loss, a network optimization design algorithm based on improved ant colony algorithm for high voltage power distribution network is proposed. After analyzing the operating characteristics of the high voltage power distribution network, the network topology of the high voltage power distribution network is described by constructing a hierarchical variable-structure distribution network model. A mathematical model of distribution network reconstruction considering the opportunity constraint with the minimum network loss as the objective function is established. The power flow distribution is calculated by using the pre-push back-generation method combined with the hierarchical structure of the distribution network. The maximum and minimum ant colony algorithm is introduced to improve the pheromone updating method of the traditional ant colony algorithm, and the search range is expanded, so that the algorithm can jump out of the local optimization trap to realize the accurate solution of the power distribution network reconstruction model. The experimental results show that compared with the current network reconstruction algorithm, the proposed algorithm requires less time for convergence, less power flow calculation, and lower network loss.


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