用户名: 密码: 验证码:
南水北调梯级泵站调节方式与系统优化运行研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
本文得到全国优秀博士学位论文作者专项基金(编号:2007B41)和江苏省水利科技重点项目(编号:2008048)的资助。
     南水北调东线工程为大型复杂梯级泵站系统。由于装机容量大,运行时间长,工程的优化运行对降低调水成本至关重要。目前,泵站优化运行研究考虑的因素和优化的范围不够全面,优化效果还有提高的空间。我国大部分泵站未实现优化运行,运行费用高,能源浪费严重。本文通过分析大型泵站系统的组成与能量损失,研究大型泵站工况调节方式的定量优化选择方法,对考虑多因素的南水北调东线单座泵站系统、并联泵站系统以及首段梯级泵站系统分别进行优化计算,确定最优运行方案,节省运行费用。主要研究工作和创造性成果有:
     (1)提出了泵站系统的概念,泵站系统由输变电设施、泵站以及输水设施组成。分析了梯级泵站系统各部分能量损失,对典型泵站系统的能量损失与系统效率进行了计算,首次揭示了泵站系统效率特性。结果表明,泵站系统效率符合随泵装置扬程的升高先升高后下降的规律。泵装置扬程一定情况下,随着开机台数的增加,宝应站和江都四站系统效率先升高后下降,江都二站和大套三站系统效率持续升高,所有机组全部开启时系统效率达到最高。
     (2)在大型泵站工况调节方式技术分析的基础上,综合考虑泵站运行扬程变化、运行时间、设备投资和运行费用等因素,首次提出了水泵机组工况调节方式定量优化选择方法。对6种典型泵型采用不同工况调节方式优化运行进行分析计算。结果表明,当泵站平均扬程位于高效区内且扬程变幅较小时,在保证正常起动的前提下,泵站最优工况调节方式为半调节。当泵站平均扬程偏离高效区较多或扬程变幅较大时,泵站需要采用变角或变频变速调节运行工况。由于变频装置本身耗费功率、设备费用高等原因,其适用的范围很小。泵站年运行扬程时间密度分布情况对工况调节方式的选择稍有影响。随着设备费用的降低,泵站系统变工况优化运行的效果愈加显著。
     (3)应用本文提出的工况调节方式定量优化选择方法,对已建的南水北调蔺家坝站、淮阴三站泵装置的工况调节方式进行了选择。结果表明,两座泵站的最优工况调节方式均为变频变速调节,这是由于这两座泵站的扬程相对变幅较大。针对待建的金湖站,筛选出3种可行泵型,进行应用不同工况调节方式优化运行计算分析,结果表明,金湖站采用变角调节较为合适。
     (4)分别采用遗传算法(GA)、基本粒子群算法(PSO)、模拟退火粒子群算法(SA-PSO)对南水北调江都站系统进行运行优化计算。结果表明,泵站实施变角优化运行,运行费用较在常规设计角度的运行费用节省0.99%-4.22%。三种算法中,SA-PSO算法更适合于泵站运行优化问题求解。
     (5)在源头江都四站日抽水量一定的情况下,考虑泵装置扬程随时间连续变化、分时电价和变角调节频度等因素,以系统日运行费用最少为目标,求解确定系统最优运行方案,首次研究优化运行的变角调节频度对运行费用的影响。结果表明,变角调节频度越高,每天划分的时段数越多,则优化效果越好,泵站系统运行费用越低,并趋向一恒定值。考虑到频繁调节对调节机构可靠性的影响,泵站每天变角以6-8次为宜。与不变角相比,优化运行一天变角8次可节省运行费用5.76%-17.63%。考虑分时电价泵站系统变角优化运行方案较不考虑分时电价的泵站系统设计角度运行方案节省运行费用5.64%-12.13%。
     (6)在源头邻近并联泵站——江都一至四站系统日抽水量一定的情况下,考虑泵装置扬程随时间连续变化、分时电价和变角调节,以系统日运行费用最少为目标,求解确定系统最优运行方案。该优化运行方案与不考虑分时电价的泵站系统设计角度优化运行方案相比,节省运行费用5.79%~18.64%。
     (7)首次研究了从长江三江营引水经江都站至淮安站下的包括输水河道和输变电设施在内的单线输水的泵站系统运行优化。在调水目的地淮安站下水位及流量一定的情况下,与在设计角度下运行相比,三江营最大潮差、平均潮差、最小潮差三种典型日分别实施变角优化运行,泵站系统运行费用分别减少0.62%-2.26%、0.33%-3.26%和0.22%-0.83%。
     (8)研究了从长江三江营引水经江都站、宝应站两条线路至淮安站下的双线输水的泵站系统优化运行。首次建立模型,分别采用逐次逼近法和两层直接迭代法求解两条线路的流量最优分配比及其系统优化运行方案。结果表明,最优流量分配方案系统输入功率较设计流量分配方案节省0.2%-2%。
     (9)首次研究了南水北调东线长江至洪泽湖段首段3级复杂梯级泵站系统运行优化,建立优化模型,通过四层迭代计算,求解在长江三江营水源水位2.19 m,洪泽湖水位13.5 m,入湖流量分别为450 m3/s、300 m3/s的情况下,首段梯级泵站系统的优化运行方案(包括梯级之间的最优扬程分配、并联输水线路最优流量分配、各泵站抽水流量、开机台数及运行工况)。结果表明:入湖流量分别为450 m3/s、300 m3/s时,系统最优运行方案输入功率较原设计方案可分别节省6.83%和2.27%。
Eastern Route of South-to-North Water Transfer Project is a large and complex step pumping station system. Because of large installed capacity and long operation time, optimal operation of the project is significant to reducing the cost of diverting water. At present, the factors and the optimal range have not been considered comprehensively in pumping station optimal operation, and the optimizing effect could be advanced. Optimal operation has not realized in most of the pumping stations. The operation cost is high and the energy is extravagant seriously. The constitutions of large pumping station system and energy losses were analyzed in the paper. Quantitative optimal selection methods of operation duty adjusting modes were researched for large pumping stations. Single pumping station system, parallel pumping station system and step pumping station system of the Eastern Route in South-to-North Water Transfer Project were calculated respectively based on multi-factors. Optimum operation schemes were obtained, and the operation cost was saved. The main works and the achievements are as follows:
     (1) The concept of pumping station system was put forward. Pumping station system is constituted by power transmission and transformation engineering, pumping stations and water transmission engineering. Energy losses of each part of step pumping station system were analyzed. Also, energy losses and system efficient of typical pumping station systems were calculated. The characteristics of pumping station system efficiency were revealed for the first time. The results indicated that the efficiency of pumping station system is according with the law of increasing at first and then decreasing with the pump assembly head increasing. Under the circumstances of certain pump assembly head, with the number of running pump units increasing, system efficiency of Baoying pumping station and Jiangdu 4th pumping station is increased at first, and then decreased. System efficiency of Jiangdu 2nd pumping station and Datao 3rd pumping station is increased continuely, and the system efficiency reaches the maximum when all the units are running.
     (2) On the basis of technical analysis on adjusting modes for large pumping station, several factors such as head variety, operation time, equipment investments and operation cost were considered comprehensively. Quantitative optimal selection methods of adjusting modes for pump unit operation duty were put forward. Aiming at 6 typical pump types, optimal operation of different adjusting modes were calculated and analyzed. The results indicated that under the premise of normal starting, the optimal adjusting mode is half adjusting blade angles when pumping station average head is locating high efficiency area, and also the head variety range is small. When pumping station average head is more deviated from high efficiency area or the head variety range is large, adjusting pump blade angles or rotational speeds by frequency is necessary to adjust operation duties. Because the variable frequency device consumes power and the equipment cost is high, its practicable range is very small. Time density distribution of pumping station annual operation head has a few influences on selecting adjusting modes. The effect of pumping station optimal operation by adjusting operation duties is more obvious with the decrement of the equipment cost.
     (3) Aiming at pump assemblies of constructed Linjiaba pumping station and Huaiyin 3rd pumping station of South-to-North Water Transfer Project, adjusting modes were selected with the quantitative optimal selection methods, which was put forward in the paper. The results indicated that the best adjusting modes of the two pumping station are both adjusting rotational speed by frequency conversion. This is because the relative variable ranges of the two pumping station head are large. Aiming at waiting for construction Jinhu pumping station, three feasible pump types were selected, and optimal operation schemes of different adjusting modes were calculated and analyzed. The results indicated that the adjusting mode by adjusting pump blade angles is suitable for Jinhu pumping station.
     (4) Genetic algorithms (GA), particle swarm optimization (PSO) and simulated annealing-particle swarm optimization (SA-PSO) were applied to calculate optimal operation of Jiangdu pumping station system in South-to-North Water Transfer Project. The results indicated that the operation costs by adjusting pump blade angles are 0.99%-4.22%less than that of the conventional schemes under design blade angles. And among the three optimum schemes, SA-PSO is more suitable for solving large pumping station optimal operation.
     (5) Under the circumstances of pumping certain volume water per day, considering pump assembly head varying along with the time, time-varying electrical price and regulating frequency by adjusting pump blade angles, optimal operation schemes of source Jiangdu 4th pumping station system were determined aiming at the least system operation cost. The results showed that the higher the regulating frequency by adjusting pump blade angles, the more the number of time periods per day is, while the optimal effect is obvious, and pumping station operation cost is decreased, which tends to some const. Considering the influences of frequently regulating on the reliability of regulating mechanism, the proper times of adjusting pump blade angles is 6-8. Compared with not adjusting pump blade angles, the operation cost is saved about 5.76%-17.63%by adjusting blade angles 8 times per day. Operation cost of the optimum schemes by adjusting pump blade angles and considering time-varying electrical price is 5.64%-12.13%less than that of design blade angles without considering time-varying electrical price.
     (6) Under the circumstances of pumping certain volume water per day, considering pump assembly head varying along with the time, time-varying electrical price and adjusting operation duties by adjusting pump blade angles, and optimal operation schemes of adjacent parallel Jiangdu pumping station system were determined aiming at the least system operation cost. Compared with the schemes of operation on design blade angles without considering time-varying electrical price, the operation cost of the optimum schemes is saved by 5.79%-18.64%.
     (7) Optimal operation for single line water transfer system was researched for the first time, which is starting from Sanjiangying of Yangtze River to Huai'an pumping station, passing by Jiangdu pumping station, including water channel, transmission and substation facilities. Under the circumstance of certain water level and discharge of Huai'an pumping station, system operation cost by adjusting blade angles are separately 0.62%-2.26%, 0.33%~3.26%and 0.22%-0.83%less than that of design blade angles with the maximum, average and minimum Sanjiangying tidal range of three typical days.
     (8) Optimal operation for double line water transfer system was researched, which is starting from Sanjiangying of Yangtze River to Huai'an pumping station, passing by Jiangdu pumping station and Baoying pumping station. Optimal models were built for the first time, and optimal discharge ratio of the two lines and system optimal operation schemes were solved by gradually approaching algorithm and two layer direct iteration. The results indicated that system input power of optimal discharge ratio is about 0.2%-2%less than that of design discharge ratio.
     (9) Optimal operation of the first section step pumping station with 3 steps was researched for the first time, which is starting from Yangtze River to Hongze Lake of Eastern Route in South-to-North Water Transfer Project. Optimal models were built and calculated by four layer iteration. When the water levels of Sanjiangying of Yangtze River and Hongze Lake are 2.19 m and 13.5 m respectively, and inflow discharge of Hongze Lake is 450 m3/s and 300 m3/s, optimal operation schemes were determined (including optimal head distribution among steps, optimal discharge distribution between parallel water diversion line, and pumping discharge, the number of running pump units and operation duties of each pumping station). The results indicated that when inflow discharge of Hongze Lake is 450 m3/s and 300 m3/s, system input power of the optimal operation schemes is 6.83%and 2.27% less than that of original design schemes.
引文
[1]张修真,洛叙六,俞澄生[M].南水北调——中国可持续发展的支撑工程.北京:中国水利水电出版社,1999
    [2]陈守伦,芮钧,徐青等.泵站日优化运行调度研究[J].水电能源科学,2003,21(3):82~83
    [3]汪亚超.泵站多型号水泵机组运行的优化调度.中国农村水利水电,1997,20(4):18~20
    [4]贾仁甫,王红,金明宇等.调水工程中梯级泵站的优化调度研究[J].扬州大学学报(自然科学版),2006,9(2):69~73
    [5]马文正,丘传忻,贺贵明。泵站运行的优化调度[J].水利学报,1993(3):35~41
    [6]江苏省江都水利工程管理处.江都排灌站[M].北京:水利电力出版社,1979
    [7]刘跃波.淮安第二抽水站拦污栅堵塞现状分析[J].工程管理,2002,(6):26~27
    [8]郑源,钱均.泵站拦污栅阻水研究[J].水泵技术,2002,(6):38~41
    [9]S. I. Egorshin. Characteristics of Modeling Water Intakes and Trash Racks for Hydroelectric Stations[J]. Power Technology and Engineering,1978,12(4):373-379
    [10]A. V. Dmitrieva. Trashrack Head Losses at Hydroelectric Power Plants[J]. Power Technology and Engineering,1980,14(10):1060~1064
    [11]慈红卫,尚联合.拦污栅在泵站工程中的应用[J].水利科技与经济,2008,14(3):247~247
    [12]钟永.拦污栅清污对洪江水电站机组运行的影响[J].人民长江,2008,39(16):43~44
    [13]金菊良,杨晓华,金保明.计算天然河道水面曲线的新方法[J].水利学报,2000,(9):25~28
    [14]任苇,郝秀运.明渠水面线能量方程的牛顿迭代法求解[J].西北水资源与水工程,2002,13(4):60~61
    [15]黄佑生,顾令宇.一种新的水面线计算方法[J].水利水电科技进展,2003,23(3):31~33
    [16]邢贞相,付强,孙兵。实码加速遗传算法在天然河道水面线计算中的应用[J].灌溉排水学报,2003,22(5):60~63
    [17]刘宝琨,张宝权.河渠水面线计算方法的简化[J].黑龙江水专学报,2005,32(1):34~35
    [18]万五一,江春波,李玉柱.变步长法在天然河道水面线计算中的应用[J].哈尔滨工业大学学报,2007,39(4):647~649
    [19]顾元棪,王尚毅.具有岔道支流的明渠非恒定流计算[J].天津大学学报,1995,(1):11~17
    [20]Robert B, Jr P E, Tim A W. The DYNHYD 5 Model documentation and user manual. Environmental Research Laboratory Office of Research and Development[J]. U S Environmental Protection Agency, 1993:9-15
    [21]黄勇,拾兵,朱玉伟,等.天然河道非恒定流数学模型原理及应用[J].海洋科学,2004,28(7):4-7
    [22]张大伟,董增川,李少华.河网非恒定流计算的牛顿迭代解法[J].西北水力发电,2004,20(3):31~33
    [23]白玉川,万艳春,黄本胜。河网非恒定流数值模拟的研究进展[J].水利学报,2000,(12):43~47
    [24]李义天.河网非恒定流隐式方程组的汊点分组解法[J].水利学报,1997,(3):49~57
    [25]侯玉,卓建民,郑国权.河网非恒定流汉点分组解法[J].水科学进展,1999,(3):49~52
    [26]徐小明,何建京,汪德爟.求解大型河网非恒定流的非线性方法[J].水动力学研究与进展,2001,16(3): 18~24
    [27]曾凡棠,黄水祥.珠江三角洲潮汐河网水环境数学模型评述[J].海洋环境科学,2000,(11):47~50
    [28]Lang A R G, et al. Inequality of Eddy Transfer Coefficients for Vertical Transport of Sensible and Latent Heats during Adventive Inversion[J]. Boundary Lager Meteor.1983, (25):25~11
    [29]闵骞.利用彭曼公式预测水面蒸发量[J].水利水电科技进展,2001,21(1):37~39
    [30]Ryan P J, Harleman D R F, and Stolzenbach K D. Surface Heat Loss from Cooling Ponds[J]. Water Resources Research,1974,10 (6):930~938
    [31]Adams E E, Douglas J, Coslee, Karl R, and Helfrich. Evaporation from Heared Water Bodies[J]. Water Resources Research,1990,26 (3):425~435
    [32]洪嘉琏,傅国斌.一种新的水面蒸发计算方法[J].地理研究,1993,(2):51~59
    [33]闵骞.道尔顿公式的应用研究[J].水利水电科技进展,2005,25(1):17~20 36
    [34]闵骞.道尔顿公式风速函数的改进[J].水文,2005,25(1):37~41,61
    [35]濮培民.水面蒸发与散热系数公式研究(一)[J].湖泊科学,1994,6(1):1-12
    [36]濮培民.水面蒸发与散热系数公式研究(二)[J].湖泊科学,1994,6(3):201~210
    [37]陈惠泉、毛世民.超温水体水面蒸发与散热[J].水利学报,1989,20(10):27~36
    [38]李万义。适用于全国范围的水面蒸发量计算模型的研究[J].水文,2000,20(4):13~17
    [39]克拉茨D B著,何丕承译.灌溉渠道衬砌[M].北京:水利电力出版社,1980
    [40]谢崇宝,Lance J M,崔远来,等.大中型灌区干渠输配水渗漏损失经验公式探讨[J].中国农村水利水电,2003,(2):20~22
    [41]于维丽,周黎明,张建泽.引黄济青输水河工程输水损失分析[J].人民黄河,2003,25(2):34~35
    [42]白美健,谢崇宝,许迪,等.灌区配水渠道流量损失计算方法的探讨[J].节水灌溉,2002(4):8-9
    [43]吴昌瑜,张伟.南水北调中线工程总干渠渗流与蒸发损失研究[J].长江科学院院报,2002,19(增刊):89~93
    [44]顾慰慈.土石(堤)坝的设计与计算[M].北京:中国建材工业出版社
    [45]杨红秀.汾河水库蒸发渗漏水量损失分析计算[J].山西水利科技,2005,(4):34~36
    [46]廉铁辉,张海生,黄国秀,等.于桥水库渗漏损失水量的估算[J].水利水电技术,2001,32(8):45~46
    [47]仇宝云.大中型水泵装置理论与关键技术研究[M].北京:中国水利水电出版社,2005
    [48]冯晓莉,仇宝云.大型泵站经济运行研究进展[J].流体机械,2006,34(4):32~37
    [49]仇宝云,黄海田.高港泵站1-3号机组变频调速效益分析[J].灌溉排水,2000,19(4):56~60
    [50]冯晓莉,仇宝云.南水北调工程江都抽水站变角经济运行研究[J].扬州大学学报(自然科学版),2006,9(2):65~68
    [51]仇宝云,冯晓莉,袁寿其.大型泵站变速-变角综合经济运行研究[J].农业机械学报,2005,36(10):58~61
    [52]Qiu Baoyun, Feng Xiaoli, Yuan Shouqi et al. Study on economical operation of large pump station by adjusting operation duty.8th Asian International Fluid Machinery Conference. October 12-15,2005: 856~870 · Yichang, China
    [53]仇宝云,冯晓莉,袁寿其,等.南水北调东线工程梯级泵站机组变工况方式选择[J].水力发电学报,2006,25(3):121~124,129
    [54]Qiu Baoyun, Jiang Wei, Cao Haihong et al. Comparison and selection of adjusting methods of large low head pump unit operation mode. The 9th Asian International Conference on Fluid Machinery. October 16-19,2007, Jeju, Korea
    [55]李强.基于遗传算法的梯级泵站优化运行研究[D].武汉大学硕士学位论文,2005
    [56]Long Xinping, Zhu Jinmu, Liu Meiqing et al. Optimization dispatch of Lianjiang pumping station[C]. 3rd International Conference on Water and Wastewater Pumping Stations,2005:163~171
    [57]Szychta L. System for Optimising Pump Station Control[J]. World Pumps, February,2004:45~48
    [58]Huo Jinsheng, Eckmann D H, Hoskins K P. Hydraulic Simulation and Variable Speed Pump Selection of a Dual-function Pumping Station:Pumping Treated Water to a Reclaimed Water System or Deep Injection Well System[J]. World Environmental and Water Resources Congress 2007: Restoring Our Natural Habitat, ASCE,1~7
    [59]Moreno M A, Carrion P A, Planells P, et al. Measurement and Improvement of the Energy Efficiency at Pumping Stations[J]. Biosystems Engineering,2007,98:479~486
    [60]Li Guohua, Baggett C C. Real-Time Operation Optimization of Variable-Speed Pumping Stations in Water Distribution Systems by Adaptive Discharge Pressure Control [J]. World Environmental and Water Resources Congress 2007, Restoring Our Natural Habitat:1~13
    [61]Moreno M A, Planells P, Corcoles J I,et al. Development of a New Methodology to Obtain the Characteristic Pump Curves that Minimize the Total Cost at Pumping Stations [J]. Biosystems Engineering,2009,102:95~10
    [62]Anagnostopoulos J S, Papantonis D E. Pumping Station Design for a Pumped-Storage Wind-Hydro Power Plant [J]. Energy Conversion and Management,2007,48:3009~3017
    [63]Anagnostopoulos J S, Papantonis D E. Optimization of Operational Planning for Wind/hydro Hybrid Water Supply Systems [J]. Renewable Energy,2009,34:928~936
    [64]刘超,耿卫明.泵站经济运行的数值解法[J].排灌机械,2004,22(3):14~17
    [65]刘正祥.动态规划、模拟技术在多级泵站优化调度中的应用[J].灌溉排水,2000,22(2):62~65
    [66]王宏江,陆桂华.遗传算法在尔王庄枢纽泵站优化调度中的应用[J].水利水电技术,2003,34(3):50~53
    [67]鄢碧鹏,刘超.混沌优化算法在泵站经济运行中的应用[J].灌溉排水学报,2004,(3):38~40
    [68]杨飞,于永海,徐辉.国内梯级泵站调水工程运行调度综述[J].水利水电科技进展,2006,26(4):84~86
    [69]龙新平,朱劲木,刘梅清等.基于性能曲面拟合的泵站优化调度分析[J].水利学报,2004,(11):27~31
    [70]朱劲木,龙新平,刘梅清等.东深供水工程梯级泵站的优化调度[J].水力发电学报,2005,24(3): 123~127
    [71]俞亭超,张土乔.供水系统直接优化调度遗传算法求解模型研究[J].浙江大学学报(工学版),2006,40(5):804~809
    [72]段焕丰,俞国平.改进混合遗传算法优化城市给水系统调度模型[J].同济大学学报(自然科学版),2006,34(3):377~381
    [73]熊晓明,刘光临.梯级泵站的实时优化调度研究[J].农业机械学报,2005,36(12):81-83
    [74]陈磊,张土乔,吕谋等.混沌遗传算法优化管网状态神经网络模型[J].浙江大学学报(工学版),2005,39(6):874~877
    [75]张土乔,许刚,吕谋等。用于供水系统直接优化调度的蚁群改进算法[J].计算机集成制造系统,2006,12(6):918~923
    [76]Hanson B, Wegand C, Orioff S. Performance of Electric Irrigation Pumping Plants using Variable Frequency Drivers [J]. Journal of Irrigation and Drainage Engineering,1996,122(3):179~182
    [77]Nitivattanon V, Sadowski E C, Quimpo R G. Optimization of Water Supply System Operation [J]. Journal of Water Resources Planning and Management,1996,122(5):374~384
    [78]Moradi-Jalal M, Marino M A, Afshar A. Optimal Design and Operation of Irrigation Pumping Stations[J]. Journal of Irrigation and Drainage Engineering,2003,129(3):149~154
    [79]Moradi-Jalal M, Rodin S I, Marino M A. Use of Genetic Algorithm in Optimization of Irrigation Pumping Stations [J]. Journal of Irrigation and Drainage Engineering,2004,130(5):357~365
    [80]Nace D, Demotier S, Carlier J, et al. Using Linear Programming Methods for Optimizing the Real-Time Pump Scheduling[J]. World Water Congress,2001
    [81]McCormick G, Powell R S. Optimal Pump Scheduling in Water Supply Systems with Maximum Demand Charges[J]. Journal of Water Resources Planning and Management, September/October, 2003:372~379
    [82]Lingireddy S, Wood D J. Improved operation of water distribution systems using variable-speed pumps[J]. Journal of Energy Engineering,1998,24(3),90~103
    [83]Xin Kunlun, Liu Suiqing, Tao Tao, et al. Application of Pseudo-Parallel Genetic Algorithm in Optimal Operation of Multisource Water Supply Network[C].8th Annual Water Distribution Systems Analysis Symposium, Cincinnati, Ohio, USA,2006,August:27~30
    [84]Pezeshk S, Helweg O J. Adaptive Search Optimization in Reducing Pump Operation Costs[J]. Journal of Water Resources Planning and Management,1996,January and February,57-63
    [85]Pulido-Calvol, Roldan J, Lopez-Luque R, et al. Water Delivery System Planning considering Irrigation Simultaneity [J]. Journal of Irrigation and Drainage Engineering,2003,129(4):247-255
    [86]Wegley C, Eusuff M, Lansey K. Determining Pump Operations using Particle Swarm Optimization [J]. Water Resources,2004:1~5
    [87]Benjamin Baran, Christian von Lucken, Aldo Sotelo. Multi-objective pump scheduling optimization using evolutionary strategies [J]. Advances in Engineering Software,2005,36:39~47
    [88]Pulido-Calvol, Gutierrez-Estrada J C, Asensio-Fernandez R. Optimal Design of Pumping Stations of Inland Intensive Fishfarms [J]. Aquacultural Engineering,2006,35:283~291
    [89]Keedwell E, Khu S-T. A hybrid genetic algorithm for the design of water distribution networks[J]. Engineering Applications of Artificial Intelligence,2005,18:461~472
    [90]Roberts A J., Berrisford M J. Application of two ant colony optimisation algorithms to water distribution system optimization[J]. Mathematical and Computer Modelling,2006,44:451~468
    [91]Leibundgut E, Koyama M. Good Design Reduces Operational Costs in Water Transportation[J]. World Pumps, June 2007,32~35
    [92]Ostfeld A, Tubaltzev A. Ant Colony Optimization for Least-Cost Design and Operation of Pumping Water Distribution Systems [J]. Journal of Water Resources Planning and Management.2008, March/April:107~118
    [93]夏春燕.变压器经济运行分析与应用[J].变压器,2007,44(12):24~28
    [94]仇宝云,林海江,黄季艳等.大型立式轴流泵叶片进口流场及其对水泵影响研究[J].机械工程学报,2005,41(4):28-34
    [95]仇宝云,黄季艳,林海江等.立式轴流泵出水流道流场试验研究[J].机械工程学报,2005,41(11):115-120,126
    [96]王三民,沈允文,孙智民.基于动态损失功率的行星齿轮传动效率计算[J].机械传动,2001,25(2):4-5,8
    [97]张承慧,夏东伟,石庆升.计及变频器和电机损耗的全变速泵站效率优化控制[J].电工技术学报,2006,21(5):52~57
    [98]王斐.南水北调东线江苏境内工程调水效率计算研究[D].[硕士学位论文],扬州大学2009
    [99]顾慰慈.土石(堤)坝的设计与计算[M].中国建材工业出版社,2006
    [100]仇宝云,刘超.泵站水泵叶片调节方式概论[J].水泵技术,1997(4):29~33
    [101]魏军,卜舸,马志华.南水北调工程宝应泵站叶片调节方式的选择[J].排灌机械,2006,24(4):14~17
    [102]黄经国。用可调进口导叶调节特性的大型混流泵[J].流体机械,2000,28(4):37~40
    [103]陈坚,孔令夔,郑玉春等.前置导轮在轴流泵站技术改造中的应用[J].中国农村水利水电,1998(2):21~25
    [104]陈坚,刘德祥,丘传忻等.带前置导轮的轴流泵装置模型试验结果及分析[J].水利学报,2000(3):69~72
    [105]江苏省江都水利工程管理处.江都排灌站(第二版)[M].北京:水利电力出版社,1979
    [106]冯晓莉.南水北调东线一期工程源头泵站优化运行研究[D].[硕士学位论文],扬州大学,2006
    [107]孔令夔,陈坚,冯心宽.改善轴流泵汽蚀性能的试验研究[J].水泵技术,1997(5):8-13
    [108]蔡可健。变频调速异步电动机运行效率的研究[J].防爆电机,2005,40(6):10~12,29
    [109]曾建潮,介婧,崔志华.微粒群算法[M].北京:科学出版社,2004
    [110]刘群明.粒子群优化算法在梯级水电站水库优化调度中的应用研究[D].[硕士学位论文],河海大学,2007
    [111]郭志辉.粒子群优化算法的若干改进及应用[D].[硕士学位论文],兰州理工大学,2009
    [112]Trelea I. The Particle Swarm Optimization Algorithm[J]. Information Processing Letters, 2003,85(6):317~325
    [113]Eberhart R, Shi Y. Comparing Inertia Weigthts and Constriction Factors in Particle Swarm Optimization[J]. IEEE Service Center,2000:4~8
    [114]Shi Y, Eberhart R C. Empirical Study of Particle Swarm Optimization[C]. Proceedings of the 1999 Congress on Evolutionary Computation,1999(3):1945~1950
    [115]张龙,王华奎.粒子群优化算法中惯性权重的研究[J].机械管理开发,2008,23(6):6~7
    [116]邹毅。一种改进线性惯权的粒子群算法[J].福建电脑,2009(8):17~19
    [117]夏晓华,刘波,栾志业等.基于APSO的非线性预测控制及在pH中和反应中的应用[J].化工自动化仪表,2006,33(1):24~27
    [118]姜松,张光.基于粒子群算法的火电厂负荷优化分配研究[J].现代电力,2006,23(1):52~56
    [119]任子晖,王坚.一种动态改变惯性权重的自适应粒子群算法[J].计算机科学,2009,36(2):227~229,256
    [120]刘建华,樊晓平,瞿志华.一种惯性权重动态调整的新型粒子群算法[J].计算机工程与应用,2007,43(7):68~70
    [121]李剑,王乘。一种改进的自适应微粒群优化算法.华中科技大学学报(自然科学版),2008,36(3):118~121
    [122]贾瑞玉,黄义堂,邢猛.一种动态改变权值的简化粒子群算法[J].计算机技术与发展,2009,19(2):137~139,144
    [123]戴彩霞.一种改进的自适应粒子群优化算法[J].广西轻工业,2009(5):60~61
    [124]黄强,陈晓楠,张洪波等.基于自适应随机惯性权的粒子群优化算法[J].西安理工大学学报,2008,24(1):27~31
    [125]陶俊波,吴彰敦,蔡德所.适应度排序改进惯性权重的粒子群算法[J].计算机工程与应用,2009,45(14):53~55,57
    [126]张顶学,廖锐全.一种基于种群速度的自适应粒子群算法[J].控制与决策,2009,24(8):1257~1260,1265
    [127]胡建秀,、曾建潮.具有随机惯性权重的PSO算法[J].计算机仿真,2006,23(8):164~167
    [128]J iang C W, Etorre B. A Hybrid Method of Chaotic Particle Swarm Optimization and Linear Interior for Reactive Power Optimization[J]. Mathematics and Computers in Simulation,2005, 68(1):57~65
    [129]Chen G M, Huang X B, Jia J Y, etal. Natural Exponential Inertia Weight Strategy in Particle Warm Optimization[C]. Proceeding of 6th Congress on Intelligent Control and Automation. Dalian:IEEE Press,2006:3672~3675
    [130]Clerc M, Kennedy J. The Particle Swarm:Explosion, Stability, and Convergence in a Multidimensional Complex Space[J]. IEEE Transactions on Evolutionary Computation,2002,6:58~73
    [131]潘峰,陈杰,甘明刚等.粒子群优化算法模型分析[J].自动化学报,2006,32(3):369~377
    [132]杜欢,赵波.邻域拓扑粒子群优化算法在电力系统无功优化中的应用[J].继电器,2006,34(14):20~23,31
    [133]刘宇,覃征,史哲文.简约粒子群优化算法[J].西安交通大学学报,2006,40(8):883~887
    [134]刘舜民,张喆.一种基于种群多样性的自适应粒子群算法[J].河南师范大学学报(自然科学版),2009,37(3):39~41
    [135]严阳,周育人.解非线性约束规划问题的分组粒子群算法[J].电脑与信息技术,2009,17(4):28~31
    [136]杨光友,陈定方,周国柱.粒子个体最优位置变异的粒子群优化算法[J].哈尔滨工程大学学报,2006,27(增刊):531~536
    [137]黄越,王东明,周锡青.求解函数优化问题的自适应粒子群算法[J].科技信息,2009(7):8-9
    [138]高鹰,谢胜利.基于模拟退火的粒子群优化算法[J].计算机工程与应用,2004,(1):47~50
    [139]高尚,杨静宇,吴小俊等.基于模拟退火算法思想的粒子群优化算法[J].计算机应用与软件,2005,22(1):103~104,80
    [140]王华秋,曹长修.基于模拟退火的并行粒子群优化研究[J].控制与决策,2005,20(5):500~504
    [141]刘军民,高岳林.混沌粒子群优化算法[J].计算机应用,2008,28(2):322~325
    [142]侯力,王振雷,钱锋.基于混沌序列的自适应粒子群优化算法[J].计算机工程,2008,34(18):210~211,214
    [143]陈如清,俞金寿.混沌粒子群混合优化算法的研究与应用[J].系统仿真学报,2008,20(3):685~688
    [144]单梁,强浩,李军等.基于Tent映射的混沌优化算法[J].控制与决策,2005,20(2):179~182
    [145]康立山.非数值并行算法(第1册)——模拟退火算法[M].北京:科学出版社,1997
    [146]王凌,刘波.微粒群优化与调度算法[M].北京:清华大学出版社,2008
    [147]中水淮河工程有限责任公司,中水北方勘测设计研究院有限责任公司.南水北调东线第一期工程项目建议书[M],2004

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700