CAJ | 학술논문

提出一种改进克隆选择算法解决无功优化问题。该算法采用分级的变异策略，对每一代种群中的抗体按亲和力进行分级，根据等级确定变异范围和变异率：较低等级中的抗体(较优秀抗体)采用小范围、小变异率进行变异，较高等级中的抗体(相对较差的抗体)采用大范围、大变异率进行变异，兼顾算法的局部和全局搜索能力；结合均匀设计原理构造初始种群，与随机分布相比，在同样规模下，具有更好的种群多样性，且以较大的概率在全局最优解附近存在抗体，避免陷入局部最优解，提高算法的收敛速度；对IEEE 30节点系统进行仿真，结果表明：该算法具有解的质量高、收敛性能好等优点。
제출일충개진극륭선택산법해결무공우화문제。해산법채용분급적변이책략，대매일대충군중적항체안친화력진행분급，근거등급학정변이범위화변이솔：교저등급중적항체(교우수항체)채용소범위、소변이솔진행변이，교고등급중적항체(상대교차적항체)채용대범위、대변이솔진행변이，겸고산법적국부화전국수색능력；결합균균설계원리구조초시충군，여수궤분포상비，재동양규모하，구유경호적충군다양성，차이교대적개솔재전국최우해부근존재항체，피면함입국부최우해，제고산법적수렴속도；대IEEE 30절점계통진행방진，결과표명：해산법구유해적질량고、수렴성능호등우점。
This paper presents an improved colonial selec-tion algorithm (ICSA) for reactive power optimization. The proposed method employs hierarchic mutation strategy, in which anti-bodies go into the appropriate levels according to the affinity. Superior antibodies in lower-level have smaller mutation range and mutation rate while inferior antibodies in topper-level have larger ones,which can improve the local and global search capabilities simultaneously. A uniform design method adopted to make initial population has more diversity population compared to that produced by random,and it is highly probable that antibodies distribute around the optimal solution. Therefore,it is favorable to avoid only local solutions to be solved and the computation speed can be effectively improved. ICSA applied for reactive power is evaluated on an IEEE-30 bus power system. It is shown that the proposed algorithm has better efficiency,accuracy and stability.