mba論文配電網(wǎng)中基于人工魚群算法的分布式發(fā)電規(guī)劃pdf

1、河北工業(yè)大學(xué)碩士學(xué)位論文配電網(wǎng)中基于人工魚群算法的分布式發(fā)電規(guī)劃姓名：吳海燕申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：電氣工程指導(dǎo)教師：楊文榮2010-11配電網(wǎng)中基于人工魚群算法的分布式發(fā)電規(guī)劃iiPLANNING PLANNING PLANNING PLANNING OF OF OF OF DISTRIBUTION DISTRIBUTION DISTRIBUTION DISTRIBUTION NETWORK NETWORK NETWORK NETWO

2、RK WITH WITH WITH WITHDISTRIBUTION DISTRIBUTION DISTRIBUTION DISTRIBUTION GENERATION GENERATION GENERATION GENERATION BASED BASED BASED BASED ON ON ON ON ARTIFICIAL ARTIFICIAL ARTIFICIAL ARTIFICIAL FISH FISH FISH FISHSWA

3、RM SWARM SWARM SWARM ALGORITHM ALGORITHM ALGORITHM ALGORITHMABSTRACT ABSTRACT ABSTRACT ABSTRACTDistributed generation (DG) is an efficient, environmental friendly, new power generationtechnology, which has the advantage

4、of less investment, flexible operation and installation, andhigher power supply reliability. However, switching the large-scale DG to the distributionnetwork brings more uncertainties to the distribution network planning

5、 and power system loadforecasting. Meanwhile, switching the DG to the distribution network can also influence thepower quality, power system protection and reliability, which are closely related with their sitesand sizes

6、. Therefore, the study of the sizes and the sites of DG will have the great strategicimportance and practical value.In this paper, double artificial fish swarm algorithm (AFSA) is applied to networkoptimization of the di

7、stribution network with DG. The outer optimize DG’s sites and sizes.Considering the impact of switching DG to the distribution network on the flow, the outeroptimization results will be brought to the inner line optimiza

8、tion. At the end of AFSA, we obtainthe optimization solutions of the distribution lines and the installation sites and sizes of the DG.The dynamic branch matrix is generated in the process of the inner line optimization

9、in the paper.The breadth first search strategy is used to re-form the branch matrix for the flow calculation.This method can identify the distribution network topology automatically, and avoid of checkingthe distribution

10、 network radiation, with the advantage of practicability and improvedoptimization efficiency.Targeting at improving the low precision and slow convergence speed in the later stage,AFSA has been enhanced by the best indiv

11、idual strategy and dynamic adjustment vision strategy.Finally, AFSA is applied to a classic example to verify its effectiveness and feasibility inoptimizing the distribution network expansion planning with DG.KEY KEY KEY