Bibliographic Details
| Title: |
Design of UPFC controller in large-scale power systems based on immune genetic algorithm. |
| Authors: |
Quanyuan Jiang1 jqy@zju.edu.cn, Zhenyu Zou1, Zhiyong Wang1, Yijia Cao1 |
| Source: |
Transactions of the Institute of Measurement & Control. 2006, Vol. 28 Issue 1, p15-25. 11p. 2 Diagrams, 1 Chart, 3 Graphs. |
| Subjects: |
Genetic programming, Computer simulation of immune system, Genetic algorithms, Combinatorial optimization, Mathematical optimization, Electric power system control |
| Abstract: |
This paper proposed a new optimization algorithm-immune genetic algorithm (IGA), which is based on immune genetic theory of creatures and can simulate the immune system and its behaviour in organisms. Compared with common genetic algorithms, the IGA adopts the following techniques to improve the global searching ability and convergence speed: immune memory, immune selection, concentration control, niching technique, chaos production and metabolism. Several typical test functions are used to verify the excellent performances of the proposed IGA. Finally, the IGA is applied to optimize the parameters of a unified power flow controller (UPFC) to improve the stability of the New England Test Power System (NETPS). Numerical simulation results demonstrate the validity of the optimized UPFC controller. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
