The Application Of The Clonal Selection Algorithm To Accelerate The Optimization Of Particle Swarm Optimization Of Distribution Network

Distribution network optimization is the important measure of distribution automation, and it is the core software of urban and suburban network reconstruction, which is invested greatly by the government now. With the rapid advance of economy, energy supply shortage is serious. By distribution network optimization, the potential of equipment can be fully utilized. And the economy and security of system can be improved greatly, which may bring out great benefit both in economy and in society. Distribution networks reconfiguration and capacitor switching are two important aspects of distribution network optimization.A novel artificial Clonal selection algorithm with particle swarm optimization is proposed to optimization distribution network. Somatic hypermutation and immune recruitment operators are used to maintain the diversity of the population and prevent the optimization from prematurity. The particle swarm optimization is proposed to renovation the individual's velocity and position, and the speed of convergent are improved. Further more modifies update rule of PSO to deal with different types of variables.Division reconfiguration and capacitor switching to two processes can't get a good effect. The research before used to use an iterative process that reconfigure the network first and then switch the capacitor. This dissertation will consider them as a complete entity through the different disposal of two types of variable.The results of 16, 33 and 69-bus system demonstrate the proposed algorithm has a highly computational efficiency, and shows the practicability of algorithm.