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Strategic Study of CAE >> 2010, Volume 12, Issue 1

Application prospect of PSO in hydrology

1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;

2. China Three Gorges Corporation, Yichang Hubei 443002, China;

3. Economics and Management School of Wuhan University, Wuhan 430072, China

Funding project:国家科技支撑计划(2008BAB29B09);国家自然科学基金(50909073);武汉大学水资源与水电工程科学国家重点实验室开放研究基金(2007C017);中国博士后科学基金(20080440956) Received: 2008-07-15 Available online: 2010-01-14 13:33:46.000

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Abstract

The basic algorithm and its flow are introduced at first, then its application to scheduling operation of reservoir, economic operation of hydropower and parameter calibration in hydrology field is discussed, the suggestion for future study is pointed out that should strengthen the study of adaptive mechanism and convergence performance in PSO, compare and combine with other technology, broaden the region of application to hydrology which may supply a new method for solving much optimal problem in hydrology field.

References

[ 1 ] Amgad A,EL -Dib, Hosam K M,et al.Optimum VAR sizing and allocation using particle swarm optimization [ J ] .Electric Power Systems Research, 2007 ,77 :965 -972 link1

[ 2 ] 高飞,童恒庆.基于改进粒子群优化算法的混沌系统参数估计方法[J].物理学报,2006,55(2):577-582 link1

[ 3 ] 赵辉,刘鲁源,张更新.基于复合适应度微粒群算法的神经网络训练[J].控制与决策,2005,20(8):958-960 link1

[ 4 ] 杨波,赵遵廉,陈允平,等.基于小波变换的边际电价神经网络预测新模型[J].电力系统自动化,2007,31(12):40-44 link1

[ 5 ] Kennedy J, Eberhart R C.Particle swarm optimization [ A] .Proc IEEE int conf on Neural Networks[ C] .Perth,1995.1942 -1948

[ 6 ] Y H Shi, Eberhart.A modified swarm optimizer [ A] .Proc IEEE int conf on Evolutionary Computation[ C] .Anchorage, 1998.1951 -1957

[ 7 ] 胡国强,贺仁睦.基于协调粒子群算法的水电站水库优化调度[J].华北电力大学学报,2006,33(5):15-18 link1

[ 8 ] Jiang Chuanwen, Etorre Bompard.A hybrid method of chaotic par- ticle swarm optimization and linear interior for reactive power op- timisation[ J] .Mathematics and Computers in Simulation, 2005 , 68 :57 -65 link1

[ 9 ] 武新宇,程春田,廖胜利,等.两阶段粒子群算法在水电站群优化调度中的应用[J].电网技术,2006,30(20):25-28 link1

[10] 张双虎,黄强,吴洪寿,等.水电站水库优化调度的改进粒子群算法[J].水力发电学报,2007,26(1):1-5 link1

[11] 谢晓锋,张文俊,杨之廉.微粒群算法综述[J].控制与决策,2003,18(2):129-134 link1

[12] 李崇浩,纪昌明,缪益平.基于微粒群算法的梯级水电厂短期优化调度研究[J].水力发电学报,2006,25(2):94-98 link1

[13] 杨道辉,马光文,过夏明,等.粒子群算法在水电站优化调度中的应用[J].水力发电学报,2006,25(5):5-7 link1

[14] 马细霞,储冬冬.粒子群优化算法在水库调度中的应用分析[J].郑州大学学报(工学版),2006,27(4):121-124 link1

[15] 胡国强,贺仁睦.梯级水电站多目标模糊优化调度模型及其求解方法[J].电工技术学报,2007,22(1):154-158 link1

[16] 袁鹏,常江,朱兵,等.粒子群算法的惯性权重模型在水库防洪调度中的应用[J].四川大学学报(工程科学版),2006,38(5):54-57 link1

[17] 刘群明,陈守伦,刘德有.流域梯级水库防洪优化调度数学模型及PSODP解法[J].水电能源科学,2007,25(1):34-37 link1

[18] WOOD A J, Wollenberg B F.Power Generation, Operation and Control[ M] .New York:John Wiley & Sons,1984

[19] 汪新星,张明.基于改进微粒群算法的水火电力系统短期发电计划优化[J].电网技术,2004,28(12):16-19 link1

[20] 侯云鹤,鲁丽娟,熊信艮,等.广义蚁群与粒子群结合算法在电力系统经济负荷分配中的应用[J].电网技术,2004,28(21):34-38 link1

[21] 杨俊杰,周建中,吴玮,等.改进粒子群优化算法在负荷经济分配中的应用[J].电网技术,2005,29(2):1-4 link1

[22] 余炳辉,王金文,权先璋,等.求解水火电力系统短期发电计划的粒子群优化算法研究[J].水电能源科学,2005,23(6): link1

[23] 刘涌,侯志俭,蒋传文.求解机组组合问题的改进离散粒子群算法[J].电力系统自动化,2006,30(4):35-39 link1

[24] 李崇浩,纪昌明,李文武.微粒群算法在水电站厂内经济运行中的应用研究[J].水利水电技术,2006,37(1):88-91 link1

[25] 芮孝芳.流域水文模型研究中的若干问题[J].水科学进展,1997,8(1):94-98 link1

[26] 江燕,胡铁松,桂发亮,等.粒子群算法在新安江模型参数优选中的应用[J].武汉大学学报(工学版),2006,39(4):14-17 link1

[27] 江燕,刘昌明,胡铁松,等.新安江模型参数优选的改进粒子群算法[J].水利学报,2007,38(10):1200-1206 link1

[28] 王海政,仝允桓.可持续发展视角下的区域水资源优化配置模型[J].清华大学学报(自然科学版),2007,47(9):1531-1536 link1

[29] 赵晓军,田富强,胡和平.粒子群优化算法在水量调度方案优化中的应用[J].人民黄河,2005,27(11):26-27 link1

[30] 席秋义,谢小平,黄强,等.基于PSO的水库泄洪风险计算[J].系统工程理论与实践,2006,26(9):129-134 link1

[31] 杨道辉,马光文,刘起方,等.基于粒子群优化算法的BP网络模型在径流预测中的应用[J].水力发电学报,2006,25(2):65-68 link1

[32] 王亮,张宏伟,岳琳,等.PSO-BP模型在城市用水量短期预测中的应用[J].系统工程理论与实践,2007,27(9):165-170 link1

[33] 董前进,王先甲,艾学山,等.基于投影寻踪和粒子群优化算法的洪水分类研究[J].水文,2007,27(4):10-14 link1

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