An improved particle swarm optimization algorithm and its application on distribution generation accessing to distribution network

• Published in: IOP conference series. Earth and environmental science Vol. 342; no. 1; pp. 12011 - 12019
• Main Authors: Wei, Zheng, Yong, Zhi, Chen, Liang, Lei, Gao, Wenpei, Zhu
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.10.2019
• Subjects: Algorithms; Contraction; Convergence; Distributed generation; Optimization algorithms; Particle swarm optimization; Simulated annealing; Smart grid
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/342/1/012011

To seek the optimal way of distributed generation(DG) accessing to the distribution network(DN) is becoming a hot topic in the research of modern smart grid. Aims to the drawbacks of imbalance and the sluggish convergence speed of some traditional intelligent algorithms, such as, particle swarm optimization algorithm, when it is used to solve DG node optimal assignment, an improved particle swarm optimization algorithm with contraction factor based on the hybrid simulated annealing algorithm is proposed. Using the improved method, the minimum power loss can be guaranteed when the DGs are accessed to the DN. The influence of the DN on the grid voltage and the network loss of the distribution of the distributed generation are analyzed. The optimization model of the active power loss minimization is derived. The simulation results are used to verify that the improved algorithm is advantageous because of its a balanced global search ability as well as fast convergence speed to assign the different DG access nodes optimally.