Hierarchical and Divisional Optimal Dispatching Strategy for Active Distribution Network based on Hybrid Particle Swarm Optimization

Author(s):  
Zhao Jian ◽  
Zhou Ning ◽  
Wang Lei ◽  
Liu Hao ◽  
Sun Qian
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Caoyuan Ma ◽  
Chunxiao Li ◽  
Xuezi Zhang ◽  
Guoxin Li ◽  
Yonggang Han

This paper proposes a reconfiguration strategy of distribution network with distribution generation (DG) based on dual hybrid particle swarm optimization algorithm. By the network structure simplification and branches grouping, network loss was selected as objective function, an improved binary particle swarm optimization algorithm (IBPSO) was used in branch group search, and the proposed group binary particle swarm optimization search algorithm was used in searching within the group to improve search efficiency and avoid early maturing. The proposed algorithm was tested on the IEEE 33-bus distribution power system and compared with other existing literature methods. The influence on the power flow of distribution network by DG position and capacity was studied. Simulation results illustrate that the proposed algorithm can get the optimal configuration results and significantly reduce system energy losses with fast convergence rate. In order to control the smart grid, using a dual hybrid particle swarm optimization algorithm to reconstruct a model, the result of simulation verifies the validity of the model. At the same time, the distributed power grid after reconstruction after optimization can effectively reduce the network loss and improve power supply quality.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7145
Author(s):  
Minsheng Yang ◽  
Jianqi Li ◽  
Jianying Li ◽  
Xiaofang Yuan ◽  
Jiazhu Xu

DC distribution network faults seriously affect the reliability of system power supply. Therefore, this paper proposes a fault recovery reconfiguration strategy for DC distribution networks, based on hybrid particle swarm optimization. The original particle swarm algorithm is improved by simplifying the distribution network structure, introducing Lévy Flight, and designing an adaptive coding strategy. First, the distribution network structure is equivalently simplified to reduce the problem dimensionality. Further, the generated branch groups are ensured to satisfy the radial constraints based on the adaptive solution strategy. Subsequently, Lévy flight is introduced to achieve intra-group optimality search for each branch group. The method is simulated in several distribution systems and analyzed in comparison with the particle swarm algorithm, genetic algorithm, and cuckoo algorithm. Finally, the results validate the accuracy and efficiency of the proposed method.


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