A Research On Modifying Parthenon Genetic Algorithm-Based To Carry Out The Reconstruction Of Distributing Network

The network reconstruction of distributing net means the topological construction of network is realized by changing the switch's on-off state under normal or non-normal conditions. With the progress of network construction and reconstruction in urban and rural areas, the degree of distributing net in the city is becoming higher and higher and its mode of operation is becoming more and more flexible. Only relying on one's past experience is not sufficient to administer and reconstruct modern distributing net. So, the automation of distributing net has an important role to play here. In recent years, with the rapid development of communication means and computer technology, the automation level of electric power distribution has been greatly improved. The layout of traditional distributing system required that network be reconstructed once a year or once a quarter. However, on the one hand, due to the dynamic property of load, and on the other, in order to make full use of the functions of distributing net reconstruction, the real-time network reconstruction of electric power distribution is imperative under the situation. Research on real-time distributing net reconstruction has a potential significance.The purpose of this research intends to find a new arithmetic method of distributing net reconstruction---modified Parthenon Genetic Algorithm. The operator or system may use the results of this arithmetic method to turn on or turn off the switch to greatly improve its efficiency and quality, thus the time for removing failure and resuming power supply can be greatly shortened and reliability of power supply can be improved enormously.Therefore, this paper first studied the theories and method about distributing net reconstruction of some forerunners and then did some improvements on selecting arithmetic operators. By adopting some optimal saving strategies and combining two-two competition selecting method, a smaller genetic reconstruction ratio has been adopted at the primary stage of single-parent descendible which makes individuals able to search in its own small areas and convergence groups to achieve optimal answer. The smallest iterative algebra saved by optimal individuals is used as convergence rule to terminate criterion. This convergence rule has made full use of knowledge accumulation of PGA in the course of evolution, which is more reasonable than the biggest conventional single-parent iterative algebra criterion and its iterative time is longer and operation simpler. The arithmetic analysis shows that PGA is high in arithmetic efficiency, which proves this research method is effective and feasible and has definite practical value/practicality.