| 基于人工鱼群算法的最优潮流计算 |
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| 引用本文： | 刘耀年,李迎红,张冰冰,李春亮.基于人工鱼群算法的最优潮流计算[J].电工电能新技术,2006,25(4):30-33,66. |
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| 作者姓名： | 刘耀年 李迎红 张冰冰 李春亮 |
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| 作者单位： | 东北电力大学电气工程学院,吉林省,吉林市,132012 |
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| 摘 要： | 提出了基于人工鱼群优化算法(AFSA)的最优潮流(OPF)计算方法;算法结合动态调整罚函数的方式,将最优潮流问题转化为一个无约束求极值问题,有效提高了算法的全局收敛能力和计算精度.应用此算法对标准IEEE30节点的电力系统进行最优潮流计算,并与粒子群算法和遗传算法进行了比较,仿真结果表明,该算法能够更好地获得全局最优解,具有实用意义.
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| 关 键 词： | 人工鱼群算法 最优潮流计算 动态调整罚函数法 |
| 文章编号： | 1003-3076（2006）04-0030-04 |
| 收稿时间： | 2006-06-23 |
| 修稿时间： | 2006-06-23 |
Artificial fish school algorithm for optimal power flow problems |
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| LIU Yao-nian,LI Ying-hong,ZHANG Bing-bing,LI Chun-liang.Artificial fish school algorithm for optimal power flow problems[J].Advanced Technology of Electrical Engineering and Energy,2006,25(4):30-33,66. |
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| Authors: | LIU Yao-nian LI Ying-hong ZHANG Bing-bing LI Chun-liang |
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| Affiliation: | School of Electrical Engineering, Northeast Dianli University, Jilin 132012, China |
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| Abstract: | A new algorithm is presented to solve OPF problem using AFSA technique in this paper. Incorporation of nonstationary assignment penalty function in solving OPF problem can significantly improve the convergence and accuracy of AFSA. The proposed AFSA method is demonstrated and compared with PSO approach and GA approach on the standard IEEE 30-bus system. The investigations reveal that the proposed method is efficient in solving OPF problem. |
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| Keywords: | artificial fish school algorithm(AFSA) non-stationary multi-stage assignment penalty function optimal power flow(OPF) |
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