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《Journal of Northeast Dianli University(Natural Science Edition)》 2007-04
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Improved Immune Algorithm Applied to Active Power Optimization of Electric Power System

LI Xiu-qing~1 WANG Shui-ying~2 GE Guang-lin~2 GE Lan~2 WANG Kai-lin~1(1.Electric Power Engineering College of Northeast Dianli University,Jilin City,Jilin Province,China,132012;2.Heilongjiang Electric Power Design Institute,Heilongjinag,Province,150010;)  
Immune Algorithm is a new optimization algorithm imitating the immune system to solve the multi- modal function optimization problem.Comparing with the genetic algorithm,the proposed algorithm based on immune principle exists following salient features such as antigen recognition,memory mechanism,the boost or restriction of antibody generations,etc.In immune algorithm the objective function and the constraints are assimilated to the antigens and the solution of the problem is assimilated to the antibody.Through the calcula- tion of affinity the antibody is evaluated and the boost or restrain of its generation is determined,thus,the pos- sibility of the evolutionary process fails into local optima is decreased.Through the memory mechanism the a- bility of local search is improved;therefore,the calculation is speeded up.The IA is Used to the calculation of active power optimization in an actual 30-bus system and the calculation results by IA is compared with that by traditional genetic algorithm(GA).The comparison results show that the more optimal solution can be ob- tained by IA and the performance of IA is far better than that of GA.
【CateGory Index】: TM744
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