双馈风力发电机积分滑模励磁控制与混合粒子群优化设计
|
摘要
双馈发电机转子交流励磁,因励磁电流频率、幅值和相位可控,具有功率调节灵活、调速性能优良及励磁容量小等优点,成为目前变速恒频风力发电技术应用和发展的主要机型之一。有效的励磁控制策略是实现双馈风力发电系统优越运行性能的关键,而双馈发电机良好的电磁特性及工作特性是实现励磁系统有效控制的前提。因此,双馈风力发电机励磁控制与优化设计研究对于风电技术进步和风电产业发展具有重要意义。
本文围绕双馈风力发电机励磁控制易受系统不确性影响的问题,建立了双馈风力发电机空载及发电运行状态下励磁控制模型,证明了滑模控制策略对包括运行状态切换在内的系统不确定因素具有匹配性,提出了一种基于指数趋近率的双馈风力发电机积分滑模励磁控制策略,并对理想情况、电机参数摄动、电网电压扰动及状态切换情况下双馈风力发电系统空载运行励磁控制进行仿真研究。结果表明,积分滑模励磁控制策略无需任何调整即可实现双馈风力发电机从空载运行到发电运行,且对电机参数摄动及电网电压扰动具有较强的鲁棒性。
同时,本文针对粒子群算法在处理双馈风力发电机优化设计等非线性多峰值优化问题时收敛速度慢、易陷入局部最优等问题,提出了混合粒子群优化算法,在惯性权重更新机制中引入了个体模糊调节策略,对同一代的不同粒子根据适应度值优劣模糊选择不同的惯性权重;在粒子位置更新机制中引入了自适应变异操作,根据种群多样性状况自适应确定变异概率和变异因子。Benchmark函数测试结果表明,混合粒子群优化算法动态平衡了全局搜索与局部搜索能力,实现了算法收敛性和种群多样性的同时兼顾,从而提高了收敛速度和寻优精度,不易陷入局部最优,对于非线性多峰值优化问题不失为一种有效地求解方法。
此外,本文研究了双馈风力发电机电磁设计特点,探讨了发电机与励磁变换器参数匹配问题,分析了非正弦励磁谐波影响,进而建立了电机优化设计模型。在此基础上,利用混合粒子群优化算法分别实现了双馈风力发电机有效材料成本、额定效率和效率曲线平坦性优化设计,提出了一种基于Pareto最优的双馈风力发电机混合粒子群多目标优化设计方法。优化结果表明,对于双馈风力发电机优化设计问题,混合粒子群优化算法表现出较强的适用性,收敛速度较快,寻优精度较高,有助于实现电机经济技术性能综合最佳化。
Doubly fed induction generator (DFIG) with the rotor excitation has been one of the main wind turbine types for the variable speed constant frequency wind power system. It has advantages of excellent speed adjustment, flexible power control ability as well as fractionally rated converter due to the independent control of the excitation current frequency, amplitude and phase angle. Effective excitation current control plays a key role for the DFIG-based wind power system to achieve advantaged operation performance. The researches on the DFIG excitation current control and optimization design are very important to the development of wind power technology and industry, as the DFIG operation characteristics are the prerequisite for the effective excitation control.
Focusing on the problem that the DFIG excitation current control tends to be disturbed by system uncertainties, mathematical models of the DFIG excitation current control in no-load stage and power generation stage are built. The sliding mode control strategy is proved to be matched with the uncertainties of the system, such as operating switch. A novel integral sliding mode controller with exponential reaching law for DFIG current control is proposed. Then, the excitation control for DFIG-based wind power system in no-load stage is studied by digital simulation. The simulation is conducted in the cases of ideal grid voltage, fluctuant grid voltage, perturbation of the generator parameters and operating stage switch. The results show that the system under integral sliding mode control accomplishes switches from no-load to generation stages without additional changes in controller, and it is relatively robust to grid voltage disturbance and generator parameter perturbations.
The particle swarm optimization (PSO) algorithm has some problems such as slow convergence and high probability of being trapped in local optima when it is applied to the DFIG optimization design and other nonlinear multimodal optimization problem. In this paper, a hybrid particle swarm optimization (HPSO) algorithm, in which a fitness-guided individual fuzzy inertia weight and a diversity-guided adaptive mutation are introduced, is proposed to solve the problems. Different inertia weights should be fuzzily assigned to different particles in the same generation, and the mutation probability and factor are adaptively calculated by the population diversity. The optimization results of benchmark function show that the proposed HPSO algorithm achieves an optimized trade off between the convergence and population diversity, with proper dynamic balance between global and local searching ability. In addition, it also makes improvements in terms of quick convergence, high precision and other commendable optimizing performances such as the absence of premature convergence. Those characteristics make the proposed HPSO algorithm applicable to the nonlinear optimization problems.
In addition, an HPSO algorithm integrated with Pareto optimality is proposed for multiobjective optimization design of the DFIG in this paper. The electromagnetic design features are studied, the parameters matching rules between the generator and its excitation converter are discussed, the effects of the harmonics caused by non-sinusoidal excitation currents are analyzed, and an optimization model of the DFIG design is built. Based on the model, the effective material cost, efficiency and flat efficiency curve are separately selected as the optimization goal for the DFIG optimization design by the HPSO algorithm. The optimization results of a DFIG design example show that the proposed HPSO algorithm behaves quick convergence and high precision as it is applied to the benchmark functions optimization. The work of this paper is useful to achieve the overall optimization of the economic and technical performances indices for DFIGs.
本文围绕双馈风力发电机励磁控制易受系统不确性影响的问题,建立了双馈风力发电机空载及发电运行状态下励磁控制模型,证明了滑模控制策略对包括运行状态切换在内的系统不确定因素具有匹配性,提出了一种基于指数趋近率的双馈风力发电机积分滑模励磁控制策略,并对理想情况、电机参数摄动、电网电压扰动及状态切换情况下双馈风力发电系统空载运行励磁控制进行仿真研究。结果表明,积分滑模励磁控制策略无需任何调整即可实现双馈风力发电机从空载运行到发电运行,且对电机参数摄动及电网电压扰动具有较强的鲁棒性。
同时,本文针对粒子群算法在处理双馈风力发电机优化设计等非线性多峰值优化问题时收敛速度慢、易陷入局部最优等问题,提出了混合粒子群优化算法,在惯性权重更新机制中引入了个体模糊调节策略,对同一代的不同粒子根据适应度值优劣模糊选择不同的惯性权重;在粒子位置更新机制中引入了自适应变异操作,根据种群多样性状况自适应确定变异概率和变异因子。Benchmark函数测试结果表明,混合粒子群优化算法动态平衡了全局搜索与局部搜索能力,实现了算法收敛性和种群多样性的同时兼顾,从而提高了收敛速度和寻优精度,不易陷入局部最优,对于非线性多峰值优化问题不失为一种有效地求解方法。
此外,本文研究了双馈风力发电机电磁设计特点,探讨了发电机与励磁变换器参数匹配问题,分析了非正弦励磁谐波影响,进而建立了电机优化设计模型。在此基础上,利用混合粒子群优化算法分别实现了双馈风力发电机有效材料成本、额定效率和效率曲线平坦性优化设计,提出了一种基于Pareto最优的双馈风力发电机混合粒子群多目标优化设计方法。优化结果表明,对于双馈风力发电机优化设计问题,混合粒子群优化算法表现出较强的适用性,收敛速度较快,寻优精度较高,有助于实现电机经济技术性能综合最佳化。
Doubly fed induction generator (DFIG) with the rotor excitation has been one of the main wind turbine types for the variable speed constant frequency wind power system. It has advantages of excellent speed adjustment, flexible power control ability as well as fractionally rated converter due to the independent control of the excitation current frequency, amplitude and phase angle. Effective excitation current control plays a key role for the DFIG-based wind power system to achieve advantaged operation performance. The researches on the DFIG excitation current control and optimization design are very important to the development of wind power technology and industry, as the DFIG operation characteristics are the prerequisite for the effective excitation control.
Focusing on the problem that the DFIG excitation current control tends to be disturbed by system uncertainties, mathematical models of the DFIG excitation current control in no-load stage and power generation stage are built. The sliding mode control strategy is proved to be matched with the uncertainties of the system, such as operating switch. A novel integral sliding mode controller with exponential reaching law for DFIG current control is proposed. Then, the excitation control for DFIG-based wind power system in no-load stage is studied by digital simulation. The simulation is conducted in the cases of ideal grid voltage, fluctuant grid voltage, perturbation of the generator parameters and operating stage switch. The results show that the system under integral sliding mode control accomplishes switches from no-load to generation stages without additional changes in controller, and it is relatively robust to grid voltage disturbance and generator parameter perturbations.
The particle swarm optimization (PSO) algorithm has some problems such as slow convergence and high probability of being trapped in local optima when it is applied to the DFIG optimization design and other nonlinear multimodal optimization problem. In this paper, a hybrid particle swarm optimization (HPSO) algorithm, in which a fitness-guided individual fuzzy inertia weight and a diversity-guided adaptive mutation are introduced, is proposed to solve the problems. Different inertia weights should be fuzzily assigned to different particles in the same generation, and the mutation probability and factor are adaptively calculated by the population diversity. The optimization results of benchmark function show that the proposed HPSO algorithm achieves an optimized trade off between the convergence and population diversity, with proper dynamic balance between global and local searching ability. In addition, it also makes improvements in terms of quick convergence, high precision and other commendable optimizing performances such as the absence of premature convergence. Those characteristics make the proposed HPSO algorithm applicable to the nonlinear optimization problems.
In addition, an HPSO algorithm integrated with Pareto optimality is proposed for multiobjective optimization design of the DFIG in this paper. The electromagnetic design features are studied, the parameters matching rules between the generator and its excitation converter are discussed, the effects of the harmonics caused by non-sinusoidal excitation currents are analyzed, and an optimization model of the DFIG design is built. Based on the model, the effective material cost, efficiency and flat efficiency curve are separately selected as the optimization goal for the DFIG optimization design by the HPSO algorithm. The optimization results of a DFIG design example show that the proposed HPSO algorithm behaves quick convergence and high precision as it is applied to the benchmark functions optimization. The work of this paper is useful to achieve the overall optimization of the economic and technical performances indices for DFIGs.
引文
[1]王承煦,张源.风力发电[M].北京:中国电力出版社,2003.
[2]李俊峰.风力12在中国[M].北京:化学工业出版社,2005.
[3] World Wind Energy Assiciation.World Wind Energy Report 2009[R].Turkey:Istanbul,2010.
[4]钟伟强.国内外风力发电简述[J].青海科技,2004,2:25-2.
[5]永强,李俊峰,许洪华.风力发电技术发展状况与趋势分析[J].中国科技产业,2006,5:69-71.
[6]中国可再生能源学会风能专业委员会.2009年中国风电装机容量统计[R].中国:北京,2010.
[7]中国可再生能源学会风能专业委员会.2009年中国风电产业发展研究报告[R].中国:北京,2010.
[8] Xia Changliang,Song Zhanfeng.Wind energy in China:current scenario and future perspectives[J].Renawable & Sustainable Energy Reviews,2009,13(8):1974-1996.
[9]高小法.国内风力发电的现状和前景[J].新能源及工艺,2002(4):19-22.
[10]龙泽强,肖劲松.风力发电研究和开发的现状与展望[J].世界科技研究与发展,2003(4):26-30.
[11] C Eisenhut,F Krug,C Schram,et al.Wind-turbine model for system simulations near cut-in wind speed[J] . IEEE Transactions on Energy Conversion,22(2):414-420.
[12]赵栋利,许洪华,赵斌,等.变速恒频风力双馈发电机并网电压控制研究[J].太阳能学报,2004,25(5):587-591.
[13]刘其辉,贺益康,卞松江.变速恒频风力发电机空载并网控制[J].中国电机工程学报,2004,24(3):6-11.
[14]刘其辉,贺益康,张建华.交流励磁变速恒频风力发电机并网控制策略[J].电力系统自动化,2006,30(3):51-55, 7.
[15]吴国祥,马祎炜,陈国呈,等.双馈变速恒频风力发电空载并网控制策略[J].电工技术学报,2007,22(7):169-175.
[16]付旺保,赵栋利,潘磊,等.基于自抗扰控制器的变速恒频风力发电并网控制[J].中国电机工程学报,2006,26(3):13-18.
[17]郎永强,徐殿国,Hadianmrei S R,等.交流励磁双馈电机分段并网控制策略[J].中国电机工程学报,2006,26(19):133-138.
[18]杨淑英,张兴,张崇巍,等.变速恒频双馈风力发电机投切控制策略[J].中国电机工程学报,2007,27(17):103-108.
[19] Chen S Z,Cheung N C,Wong K C,et al.Grid synchronization of doubly-fed induction generator using integral variable structure control[J] . IEEE Transactions on Energy Conversion,2009,24(4):875-883.
[20]吴国祥,陈国呈,蔚兰.变速恒频风力发电柔性并网及解列控制[J].华中科技大学学报:自然科学版,2009,37(3):94-97.
[21]曾志勇,王清灵,冯婧.变速恒频双馈风力发电负载并网控制[J].电力系统保护与控制,2009(15):33-37.
[22]李亚西,王志华,赵斌,等.大功率双馈发电机“孤岛”并网方式[J].太阳能学报,2006,27(1):1-6.
[23]李建林,赵栋利,李亚西,等.几种适合变速恒频风力发电机并网方式对比分析[J].电力建设,2006,27(5):8-10.
[24]马幼捷,尹向前,赵国华,等.变速恒频双馈风电机组参数扰动对并网控制的影响[J].太阳能学报,2009,30(5):650-654.
[25] Iqbal M T,Coonick A H,Freris L L.Dynamic control options for variable speed wind turbines[J].Wind Engineering,1994,18(1):1-12.
[26] Bhowmik S,Spee R,Enslin J H.Performance optimization for doubly fed wind power generation systems[J].IEEE Transactions on Industry Applications,1999,35(4):949.
[27] Yuan G,Chai J,Li Y.Vector control and synchronization of doubly fed induction wind generator system[C].The 4th International Power Electronics and Motion Control Conference,2004:886-890.
[28] Hua G,Geng Y.A novel control strategy of MPPT taking dynamics of wind turbine into account[C].37th IEEE Power Electronics Specialists Conference,2006:1-6.
[29] Bossanyi E A.The design of closed loop controllers for wind turbines[J].Wind Energy,2000,3(3):149-163.
[30]刘其辉,贺益康,张建华.交流励磁变速恒频风力发电机的运行控制及建模仿真[J].中国电机工程学报,2006,26(5):43-50.
[31] Ekanayake J,Holdsworth L,Jenkins N.Control of doubly-fed induction wind generators[J].Power Engineering,2003,17(1):28-32.
[32] Prats M A M,Carrasco J M,Galvan E,et al.Improving transition between power optimization and power limitation of variable speed,variable pitch wind turbines using fuzzy control techniques[J].26th Annual Conference of the IEEE Industrial Electronics Society,2000:1497-1502.
[33] Cardenas-Dobson R,Asher G M.Power limitation in variable speed wind turbines using pitch control and a mechanical torque observer[J].Wind Engineering,1996,20(6):363-387.
[34] Zhang X,Xu D,Liu Y.Intelligent control for large-scale variable speed variable pitch wind turbines[J].Journal of Control Theory and Applications,2004,2(3):305-311.
[35] Wright A D.Modern control design for flexible wind turbines[R].National Renewable Energy Laboratory,2004.
[36]夏长亮,宋战锋.变速恒频风力发电系统变桨距自抗扰控制[J].中国电机工程学报,2007,27(14):91-95.
[37]宋战锋.低电压故障下双馈风力发电系统特性分析与运行控制[D].[博士学位论文],天津:天津大学,2009.
[38]林成武,王凤翔,姚兴佳.变速恒频双馈风力发电机励磁控制技术研究[J].中国电机工程学报,2003,23(11):122-125.
[39]辜承林,韦忠朝.对转子交流励磁电流实行矢量控制的变速恒频发电机(第一部分:控制模型与数字仿真)[J].中国电机工程学报,1996,16(2):119-124.
[40] Muller S,Deicke M,De Doncker R W.Doubly fed induction generator systems for wind turbines[J].IEEE Industry Applications Magazine,2002,8(3):26-33.
[41] Peresada S,Tilli A,Tonielli A.Indirect stator flux-oriented output feedback control of a doubly fed induction machine[J].IEEE Transactions on Control Systems Technology,2003,11(6):875-888.
[42]陈炜,陈成,宋占锋,夏长亮.双馈风力发电系统双PWM变换器PR控制[J].中国电机工程学报,2009,29(15):1-6.
[43] Pena R,Clare J C,Asher G M.Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation[J].IEE Proceedings of Electric Power Applications,1996,143(3):231-241.
[44] Hopfensperger B,Atkinson D J,Lakin R A.Stator-flux-oriented control of a doubly-fed induction machine with and without position encoder[J].IEE Proceedings of Electric Power Application,2000,147(4):241-250.
[45] Tapia A,Tapia G,Ostolaza J X,et al.Modeling and control of a wind turbine driven doubly fed induction generator[J] . IEEE Transactions on energy conversion,2003,18(2):194-204.
[46]夏长亮,宋战锋.双馈风力发电系统转子电流自抗扰控制[J].电工电能新技术,2007,26(3):11-14.
[47] Datta R,Ranganathan V T.Direct power control of grid-connected wound rotor induction machine without rotor position sensors[J].IEEE Transactions on Power Electronics,2001,16(3):390-399.
[48] Mohammed O A,Liu Z,Liu S,et al.Stator power factor adjustable direct torque control of doubly-fed induction machines[J].Proceedings of IEEE Electric Machines and Drives,2005:572-576.
[49] Xu L,Cartwright P.Direct active and reactive power control of DFIG for wind energy generation[J].IEEE Transaction on Energy Conversion,2006,21(3):750-758.
[50] Zhi D,Xu L.Direct power control of DFIG with constant switching frequency and improved transient performance[J] . IEEE Transaction on Energy Conversion,2007,22(1):110-118.
[51]郭晓明,贺益康,何奔腾.双馈异步风力发电机开关频率恒定的直接功率控制[J].电力系统自动化,2008,32(1):61-65.
[52]高为炳.变结构控制研究的发展与现状[J].控制与决策,1993,8(4):241-248.
[53]路强,沈传文,季晓隆,等.一种用于感应电机控制的新型滑模速度观测器研究[J].中国电机工程学报,2006,26(18):164-168.
[54]王敬生,王庆龙.感应电机无传感器滑模变结构控制[J].合肥工业大学学报(自然科学版),2010,33(5):661-664.
[55]童克文,张兴,张昱,等.基于新型趋近律的永磁同步电动机滑模变结构控制[J].中国电机工程学报,2008,28(21):102-106.
[56]方斯琛,周波.滑模控制的永磁同步电机伺服系统一体化设计[J].中国电机工程学报,2009(3):96-101.
[57]刘颖,周波,方斯琛.基于新型扰动观测器的永磁同步电机滑模控制[J].中国电机工程学报,2010(9):80-85.
[58]凌睿,柴毅.永磁直线同步电机多变量二阶滑模控制[J].中国电机工程学报,2009(36):60-66.
[59] De Battista H,Mantz R J.Dynamical variable structure controller for power regulation of wind energy conversion systems[J].IEEE Transactions on Energy Conversion,2004,19(4):756-763.
[60] Valenciaga F,Puleston P F.Variable structure control of a wind energy conversion system based on a brushless doubly fed reluctance generator[J].IEEE Transaction on Energy Conversion,2007,22(2):499-506.
[61]李渊,何凤有,谭国俊.双馈电机系统滑模变结构反演控制的研究[J].电机与控制学报,2009,13(S1):15-19.
[62]刘远涛,杨俊华,谢景凤,等.双馈风力发电机有功功率和无功功率的滑模解耦控制[J].电机与控制应用,2010,37(4):39-43.
[63]孔屹刚,王志新.大型风电机组模糊滑模鲁棒控制器设计与仿真[J].中国电机工程学报,2008,28(14):136-141.
[64]郑雪梅,李琳,徐殿国.双馈风力发电系统低电压过渡的高阶滑模控制仿真研究[J].中国电机工程学报,200929(S1):178-183.
[65] Utkin V,Shi J.Integral sliding mode in systems operating under uncertainty conditions[C].IEEE Conference on Decision and Control,35th,Kobe,Japan.1996:4591-4596.
[66] Wang J D,Lee T L,Juang Y T.New methods to design an integral variable structure controller[J].IEEE Transactions on Automatic Control,1996,41(1):140-143.
[67] Pena R,Sbarbaro D.Integral variable structure controllers for small wind energy systems[C].Proceedings of the 25th Annual Conference of the IEEE Industrial Electronics Society,1999,3(3):1067-1072.
[68]杨文强,蔡旭,姜建国.矢量控制系统的积分型滑模变结构电流控制[J].上海交通大学学报,2004,38(8):1265-1268.
[69]杨文强,蔡旭,姜建国.矢量控制系统的积分型滑模变结构速度控制[J].上海交通大学学报,2005,39(3):426-428.
[70]宁玉泉,钟长青.大型感应电动机的离散优化设计[J].中国电机工程学报,1997,17(2):129-133.
[71]陈世坤.电机设计[M].北京:机械工业出版社,2000.
[72]傅丰礼,唐孝镐.异步电动机设计手册[M].北京:机械工业出版社,2002.
[73]黄国治,傅丰礼.中小旋转电机设计手册[M].北京:中国电力出版社,2007.
[74]上海电器科学研究所.中小型三相异步电动机电磁计算程序,1971.
[75]杨向宇.电机的计算机辅助设计[M].北京:机械工业出版社,1996.
[76]詹先伟.双馈异步电动发电机的设计特点[J].国外大电机,2006(4):1-5.
[77]杨顺昌.并网运行的异步发电机设计中几个问题的探讨[J].电工技术学报,1991,(2):21-25.
[78]廖勇,杨顺昌.交流励磁发电机的电磁设计[J].重庆大学学报:自然科学版,1999,22(6):29-35.
[79]高亚州,史荫生,白惠珍.双馈异步发电机的工作原理及电磁设计[J].电机技术,2009,6:11-17.
[80]廖勇,姚骏,杨顺昌.交流励磁发电机励磁电源管压降引起的谐波及其消除方法的研究[J].中国电机工程学报,2004,24(4):151-156.
[81]余渝,杨顺昌.电压型逆变器供电的交流励磁电动机的谐波分析[J].核工业自动化,2001(1):24-30.
[82]余渝.考虑谐波后的交流励磁电动机的电磁设计[D].[硕士学位论文],重庆:重庆大学,2001.
[83]李辉,杨顺昌.考虑转子谐波电流影响后双馈电机电磁功率的分析与计算[J].中国电机工程学报,2003,23(7):123-128.
[84] Fan L,Yuvarajan S,Kavasseri R.Harmonic analysis of a DFIG for a wind energy conversion system[J].IEEE Transactions on Energy Conversion,2010,25(1):181-190.
[85]陈荣德.并网风力发电机的技术要求[J].风力发电,1995(1):27-29.
[86]计宗燮.并网风力异步发电机设计参数和节能的关系[J].机电工程,1998,15(2):55-56.
[87]杨强,黄守道,高剑.兆瓦级交流励磁双馈风力发电机的电磁设计研究[J].大电机技术,2007(4):23-28.
[88]张越雷,杨强,黄守道.变速恒频风电机组用双馈异步发电机的设计探讨[J].电气应用,2007,26(12):80-83.
[89]魏静微,谭勇,张宏宇.大型交流励磁双馈风力发电机的设计[J].电机与控制学报,2010,14(5):44-48.
[90] Chad Abbey,Geza Joos.A systematic approach to design and operation of a doubly fed induction generator[J].Electric Power Systems Research,2008,78:399-408.
[91]张胜男.浅谈1.5MW双馈风力发电机定,转子槽型的选择[J].防爆电机,2009,44(4):5-7.
[92]侯小全,周光厚,汪波.兆瓦级绕线式双馈异步发电机总体设计研究[J].东方电机,2005,33(1):57-60.
[93]李松田,贺建华.2.5MW双馈绕线型三相异步风力发电机的研制和开发[J].东方电机,2009,37(4):52-58.
[94]郭亮.新型同步电机的分析与优化研究[D].[博士学位论文],浙江:浙江大学,2006.
[95]史婷娜.低速大转矩永磁同步电机及其控制系统[D].[博士学位论文],天津:天津大学,2009.
[96]范镇南,韩力.电机优化设计技术发展情况[J].电机与控制应用,2006,33(8):3-7.
[97] R Bhuvaneswari,S Subramanian.Optimization of three phase induction motor design using simulated annealing algorithm[J].Electric Power Components and Systems,2005,32(9):947-956.
[98]白凤仙,邵玉槐,孙建中.利用智能型模拟退火算法进行开关磁阻电机磁极几何形状的优化[J].中国电机工程学报,2003,23(1):126-131.
[99] R Kannan,S Subramanian,R Bhuvaneswari.Multiobjective optimal design of three phase induction generator using simulated annealing technique[J].International Journal of Engineering Science and Technology,2010,2(5):1359-1369.
[100]方攸同,魏世泽.基于随机算法的三相异步电动机全局优化[J].中国电机工程学报,2000,20(5):18-21.
[101]乔静秋,陈旭东.基Tabu算法的轮毂式永磁电机优化研究[J].浙江大学学报:工学版,2002,36(6):713-717.
[102] Lhassane Idoumghar,Tsarafidy Raminosoa,Abdellatif Miraoui.New tabu search algorithm to design an electric motor[J] . IEEE Transactions on Magnetics,2009,45(3):1498-1501.
[103]王群京,鲍晓华,倪有源,等.基于支持向量机和遗传算法的爪极发电机建模及参数优化[J].电工技术学报,2006,21(4):57-61.
[104]吴德荣,李景川.遗传算法在电机系列优化设计中的应用研究[J].西安交通大学学报,1999,33(2):14-18.
[105] L Jolly,M A Jabbar,L Qinghua.Design optimization of permanent magnet motors using response surface methodology and genetic algorithm[J].IEEE Transactions on Magnetics,2005,41(10):3928 - 3930.
[106] James Kennedy,Russell Eberhart.Particle swarm optimization[C].IEE Proceedings of International Conference on Neural Networks,Piscataway,NJ:IEEE Service Center,1995:1942-1948.
[107]杨维,李歧强.粒子群优化算法综述[J].中国工程科学,2004,6(5):87-94.
[108]谢美娟,叶云岳.自适应变异粒子群优化算法在水轮发电机优化设计中的应用[J].大电机技术,2005,(5):9-12.
[109]夏永明,付子义,袁世鹰,等.粒子群优化算法在直线感应电机优化设计中的应用[J].中小型电机,2002,29(6):14-16.
[110]郭亮,卢琴芬,叶云岳.基于粒子群算法的直线振动发电机优化设计[J].电机与控制学报,2008,12(4):442-446.
[111]刘爱民,林莘.断路器操动机构用直线感应电机的优化设计[J].电机与控制学报,2009,13(4):528-532, 540.
[112]包广清,江建中.一种新型横向磁通永磁电机的建模与参数优化[J].大电机技术,2008,(4):12-16.
[113]包广清,郑文鹏,江建中.一种改进粒子群算法在横向磁通永磁电机优化中的应用[J].电机与控制应用,2008,35(8):27-31,61.
[114] Raj C T,Strivastava S P,Agarwal P.Realization on PSO based induction motor design via SPEED/PC-IMD[C] . International Conference on Advanced Computer Control,Singapore:IEEE Press,2009:65-69.
[115] Shi Yuhui,Russell Eberhart.A modified particle swarm optimizer[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,1998:69-73.
[116] Liang J J,Qin A K,Suganthan Ponnuthurai,et al.Comprehensive learning particle swarm optimizer for global optimization of multimodal functions [J].IEEE Transactions on Evolutionary Computation,2006,10(3):281-295.
[117] Maurice Clerc.The swarm and the queen: towards a deterministic and adaptive particle swarm optimization[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,1999:1951-1957.
[118] Maurice Clerc,James Kennedy.The particle swarm - explosion,stability,and convergence in a multidimensional complex space[J].IEEE Transactions on Evolutionary Computation,2002,6(1):58-73.
[119] Russell Eberhart,Shi Yuhui.Comparing inertia weights and constriction factors in particle swarm optimization[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,2000:84-88.
[120] Asanga Ratnaweera,Saman K. Halgamuge,Harry C. Watson.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J].IEEE Transactions on Evolutionary Computation,2004,8(3):240-255.
[121] Anthony Carlisle,Gerry Dozier.An off-the-shelf PSO[C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2001:1-6.
[122] Shi Yuhui,Russell Eberhart.Fuzzy adaptive particle swarm optimization [C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2001:101-106.
[123]郭文忠,陈国龙.粒子群优化算法中惯性权值调整的一种新策略[J].计算机工程与科学,2007,29(1):70-72,75.
[124]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.
[125] A Ratnaweera,S K Halgamuge,H C Watson.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J].IEEE Transactions on Evolutionary Computation,2004,8(3):240-255.
[126] Natsuki Higashi,Hitoshi Iba.Particle swarm optimization with gaussian mutation[C].Proceedings of the swarm intelligence symposium,Piscataway,NJ:IEEE Service Center,2003:72-79.
[127] Andrew Stacey,Mirjana Jancic,Ian Grundy.Particle swarm optimization with mutation[C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2003:1425-1430.
[128] S H Ling,H H C Iu,K Y Chan,et al.Hybrid particle swarm optimization with wavelet mutation and its industrial applications[J].IEEE Transactions on Systems,man and cybernetics-part B: Cybernetics,2008,38(3):743-763.
[129] Ning Li,Yuan-Qing Qin,De-Bao Sun,et al.Particles swarm optimization with mutation operator[C].Proceedings of the third international conference on machine learning and cybemetics,2004:26-29.
[130] Gao Yuelin.A New Particle Swarm optimization algorithm with adaptive mutation operator[C].2009 Second International Conference on Information and Computing Science,2009:58-61.
[131] Li Changhe,Yang Shengxiang,Korejo Imtiaz.An adaptive mutation operator for particle swarm optimization[C],Proceedings of the 2008 UK Workshop on Computational Intelligence,2008:165-170.
[132] Li Jize,Song Ping,Li Kejie.A modified particle swarm optimization with adaptive selection operator and mutation operator[C] . 2008 International Conference on Computer Science and Software Engineering,2008:1199-1202.
[133] Jacques Riget,J S Vesterstrom.A diversity-guided particle swarm optimizer﹣the ARPSO[R].Denmark:Department of Computer Science,University of Aarhus,2002.
[134] Jie Jing,Zeng Jianchao,Han Chongzhao.Adaptive particle swarm optimization with feedback control of diversity[J] . Computational Intelligence and Bioinformatics,2006,4115:81-92.
[135]王自强,张龙,黄燕丹.飞行控制用无刷直流电动机的优化设计[J].北京航空航天大学学报,2004,30(7):588-592.
[136] I. Das,J.E. Dennis.A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multi-criteria optimization problems [J].Structural Optimization,1997,14:63-69.
[137] Zitzler E,Thiele L.Multi-objective evolutionary algorithms:a comparative case study and the strength pareto approach[J].IEEE Transactions on Evolutionary Computation,1999,3(4):257-271.
[138] Deb K,Pratap A,Agarwal S,et al.A fast and elitist multi-objective genetic algorithm: NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[139] Giampaolo Liuzzi,Stefano Lucidi,Francesco Parasiliti,et al.Multi-objective optimization techniques for the design of induction motors[J] . IEEE Transactions on Magnetics,2003,29(3):1261-1264.
[140]张小玲.粒子群算法在圆筒型直线感应电机优化设计中的应用[D].[硕士学位论文],沈阳:沈阳工业大学,2010.
[2]李俊峰.风力12在中国[M].北京:化学工业出版社,2005.
[3] World Wind Energy Assiciation.World Wind Energy Report 2009[R].Turkey:Istanbul,2010.
[4]钟伟强.国内外风力发电简述[J].青海科技,2004,2:25-2.
[5]永强,李俊峰,许洪华.风力发电技术发展状况与趋势分析[J].中国科技产业,2006,5:69-71.
[6]中国可再生能源学会风能专业委员会.2009年中国风电装机容量统计[R].中国:北京,2010.
[7]中国可再生能源学会风能专业委员会.2009年中国风电产业发展研究报告[R].中国:北京,2010.
[8] Xia Changliang,Song Zhanfeng.Wind energy in China:current scenario and future perspectives[J].Renawable & Sustainable Energy Reviews,2009,13(8):1974-1996.
[9]高小法.国内风力发电的现状和前景[J].新能源及工艺,2002(4):19-22.
[10]龙泽强,肖劲松.风力发电研究和开发的现状与展望[J].世界科技研究与发展,2003(4):26-30.
[11] C Eisenhut,F Krug,C Schram,et al.Wind-turbine model for system simulations near cut-in wind speed[J] . IEEE Transactions on Energy Conversion,22(2):414-420.
[12]赵栋利,许洪华,赵斌,等.变速恒频风力双馈发电机并网电压控制研究[J].太阳能学报,2004,25(5):587-591.
[13]刘其辉,贺益康,卞松江.变速恒频风力发电机空载并网控制[J].中国电机工程学报,2004,24(3):6-11.
[14]刘其辉,贺益康,张建华.交流励磁变速恒频风力发电机并网控制策略[J].电力系统自动化,2006,30(3):51-55, 7.
[15]吴国祥,马祎炜,陈国呈,等.双馈变速恒频风力发电空载并网控制策略[J].电工技术学报,2007,22(7):169-175.
[16]付旺保,赵栋利,潘磊,等.基于自抗扰控制器的变速恒频风力发电并网控制[J].中国电机工程学报,2006,26(3):13-18.
[17]郎永强,徐殿国,Hadianmrei S R,等.交流励磁双馈电机分段并网控制策略[J].中国电机工程学报,2006,26(19):133-138.
[18]杨淑英,张兴,张崇巍,等.变速恒频双馈风力发电机投切控制策略[J].中国电机工程学报,2007,27(17):103-108.
[19] Chen S Z,Cheung N C,Wong K C,et al.Grid synchronization of doubly-fed induction generator using integral variable structure control[J] . IEEE Transactions on Energy Conversion,2009,24(4):875-883.
[20]吴国祥,陈国呈,蔚兰.变速恒频风力发电柔性并网及解列控制[J].华中科技大学学报:自然科学版,2009,37(3):94-97.
[21]曾志勇,王清灵,冯婧.变速恒频双馈风力发电负载并网控制[J].电力系统保护与控制,2009(15):33-37.
[22]李亚西,王志华,赵斌,等.大功率双馈发电机“孤岛”并网方式[J].太阳能学报,2006,27(1):1-6.
[23]李建林,赵栋利,李亚西,等.几种适合变速恒频风力发电机并网方式对比分析[J].电力建设,2006,27(5):8-10.
[24]马幼捷,尹向前,赵国华,等.变速恒频双馈风电机组参数扰动对并网控制的影响[J].太阳能学报,2009,30(5):650-654.
[25] Iqbal M T,Coonick A H,Freris L L.Dynamic control options for variable speed wind turbines[J].Wind Engineering,1994,18(1):1-12.
[26] Bhowmik S,Spee R,Enslin J H.Performance optimization for doubly fed wind power generation systems[J].IEEE Transactions on Industry Applications,1999,35(4):949.
[27] Yuan G,Chai J,Li Y.Vector control and synchronization of doubly fed induction wind generator system[C].The 4th International Power Electronics and Motion Control Conference,2004:886-890.
[28] Hua G,Geng Y.A novel control strategy of MPPT taking dynamics of wind turbine into account[C].37th IEEE Power Electronics Specialists Conference,2006:1-6.
[29] Bossanyi E A.The design of closed loop controllers for wind turbines[J].Wind Energy,2000,3(3):149-163.
[30]刘其辉,贺益康,张建华.交流励磁变速恒频风力发电机的运行控制及建模仿真[J].中国电机工程学报,2006,26(5):43-50.
[31] Ekanayake J,Holdsworth L,Jenkins N.Control of doubly-fed induction wind generators[J].Power Engineering,2003,17(1):28-32.
[32] Prats M A M,Carrasco J M,Galvan E,et al.Improving transition between power optimization and power limitation of variable speed,variable pitch wind turbines using fuzzy control techniques[J].26th Annual Conference of the IEEE Industrial Electronics Society,2000:1497-1502.
[33] Cardenas-Dobson R,Asher G M.Power limitation in variable speed wind turbines using pitch control and a mechanical torque observer[J].Wind Engineering,1996,20(6):363-387.
[34] Zhang X,Xu D,Liu Y.Intelligent control for large-scale variable speed variable pitch wind turbines[J].Journal of Control Theory and Applications,2004,2(3):305-311.
[35] Wright A D.Modern control design for flexible wind turbines[R].National Renewable Energy Laboratory,2004.
[36]夏长亮,宋战锋.变速恒频风力发电系统变桨距自抗扰控制[J].中国电机工程学报,2007,27(14):91-95.
[37]宋战锋.低电压故障下双馈风力发电系统特性分析与运行控制[D].[博士学位论文],天津:天津大学,2009.
[38]林成武,王凤翔,姚兴佳.变速恒频双馈风力发电机励磁控制技术研究[J].中国电机工程学报,2003,23(11):122-125.
[39]辜承林,韦忠朝.对转子交流励磁电流实行矢量控制的变速恒频发电机(第一部分:控制模型与数字仿真)[J].中国电机工程学报,1996,16(2):119-124.
[40] Muller S,Deicke M,De Doncker R W.Doubly fed induction generator systems for wind turbines[J].IEEE Industry Applications Magazine,2002,8(3):26-33.
[41] Peresada S,Tilli A,Tonielli A.Indirect stator flux-oriented output feedback control of a doubly fed induction machine[J].IEEE Transactions on Control Systems Technology,2003,11(6):875-888.
[42]陈炜,陈成,宋占锋,夏长亮.双馈风力发电系统双PWM变换器PR控制[J].中国电机工程学报,2009,29(15):1-6.
[43] Pena R,Clare J C,Asher G M.Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation[J].IEE Proceedings of Electric Power Applications,1996,143(3):231-241.
[44] Hopfensperger B,Atkinson D J,Lakin R A.Stator-flux-oriented control of a doubly-fed induction machine with and without position encoder[J].IEE Proceedings of Electric Power Application,2000,147(4):241-250.
[45] Tapia A,Tapia G,Ostolaza J X,et al.Modeling and control of a wind turbine driven doubly fed induction generator[J] . IEEE Transactions on energy conversion,2003,18(2):194-204.
[46]夏长亮,宋战锋.双馈风力发电系统转子电流自抗扰控制[J].电工电能新技术,2007,26(3):11-14.
[47] Datta R,Ranganathan V T.Direct power control of grid-connected wound rotor induction machine without rotor position sensors[J].IEEE Transactions on Power Electronics,2001,16(3):390-399.
[48] Mohammed O A,Liu Z,Liu S,et al.Stator power factor adjustable direct torque control of doubly-fed induction machines[J].Proceedings of IEEE Electric Machines and Drives,2005:572-576.
[49] Xu L,Cartwright P.Direct active and reactive power control of DFIG for wind energy generation[J].IEEE Transaction on Energy Conversion,2006,21(3):750-758.
[50] Zhi D,Xu L.Direct power control of DFIG with constant switching frequency and improved transient performance[J] . IEEE Transaction on Energy Conversion,2007,22(1):110-118.
[51]郭晓明,贺益康,何奔腾.双馈异步风力发电机开关频率恒定的直接功率控制[J].电力系统自动化,2008,32(1):61-65.
[52]高为炳.变结构控制研究的发展与现状[J].控制与决策,1993,8(4):241-248.
[53]路强,沈传文,季晓隆,等.一种用于感应电机控制的新型滑模速度观测器研究[J].中国电机工程学报,2006,26(18):164-168.
[54]王敬生,王庆龙.感应电机无传感器滑模变结构控制[J].合肥工业大学学报(自然科学版),2010,33(5):661-664.
[55]童克文,张兴,张昱,等.基于新型趋近律的永磁同步电动机滑模变结构控制[J].中国电机工程学报,2008,28(21):102-106.
[56]方斯琛,周波.滑模控制的永磁同步电机伺服系统一体化设计[J].中国电机工程学报,2009(3):96-101.
[57]刘颖,周波,方斯琛.基于新型扰动观测器的永磁同步电机滑模控制[J].中国电机工程学报,2010(9):80-85.
[58]凌睿,柴毅.永磁直线同步电机多变量二阶滑模控制[J].中国电机工程学报,2009(36):60-66.
[59] De Battista H,Mantz R J.Dynamical variable structure controller for power regulation of wind energy conversion systems[J].IEEE Transactions on Energy Conversion,2004,19(4):756-763.
[60] Valenciaga F,Puleston P F.Variable structure control of a wind energy conversion system based on a brushless doubly fed reluctance generator[J].IEEE Transaction on Energy Conversion,2007,22(2):499-506.
[61]李渊,何凤有,谭国俊.双馈电机系统滑模变结构反演控制的研究[J].电机与控制学报,2009,13(S1):15-19.
[62]刘远涛,杨俊华,谢景凤,等.双馈风力发电机有功功率和无功功率的滑模解耦控制[J].电机与控制应用,2010,37(4):39-43.
[63]孔屹刚,王志新.大型风电机组模糊滑模鲁棒控制器设计与仿真[J].中国电机工程学报,2008,28(14):136-141.
[64]郑雪梅,李琳,徐殿国.双馈风力发电系统低电压过渡的高阶滑模控制仿真研究[J].中国电机工程学报,200929(S1):178-183.
[65] Utkin V,Shi J.Integral sliding mode in systems operating under uncertainty conditions[C].IEEE Conference on Decision and Control,35th,Kobe,Japan.1996:4591-4596.
[66] Wang J D,Lee T L,Juang Y T.New methods to design an integral variable structure controller[J].IEEE Transactions on Automatic Control,1996,41(1):140-143.
[67] Pena R,Sbarbaro D.Integral variable structure controllers for small wind energy systems[C].Proceedings of the 25th Annual Conference of the IEEE Industrial Electronics Society,1999,3(3):1067-1072.
[68]杨文强,蔡旭,姜建国.矢量控制系统的积分型滑模变结构电流控制[J].上海交通大学学报,2004,38(8):1265-1268.
[69]杨文强,蔡旭,姜建国.矢量控制系统的积分型滑模变结构速度控制[J].上海交通大学学报,2005,39(3):426-428.
[70]宁玉泉,钟长青.大型感应电动机的离散优化设计[J].中国电机工程学报,1997,17(2):129-133.
[71]陈世坤.电机设计[M].北京:机械工业出版社,2000.
[72]傅丰礼,唐孝镐.异步电动机设计手册[M].北京:机械工业出版社,2002.
[73]黄国治,傅丰礼.中小旋转电机设计手册[M].北京:中国电力出版社,2007.
[74]上海电器科学研究所.中小型三相异步电动机电磁计算程序,1971.
[75]杨向宇.电机的计算机辅助设计[M].北京:机械工业出版社,1996.
[76]詹先伟.双馈异步电动发电机的设计特点[J].国外大电机,2006(4):1-5.
[77]杨顺昌.并网运行的异步发电机设计中几个问题的探讨[J].电工技术学报,1991,(2):21-25.
[78]廖勇,杨顺昌.交流励磁发电机的电磁设计[J].重庆大学学报:自然科学版,1999,22(6):29-35.
[79]高亚州,史荫生,白惠珍.双馈异步发电机的工作原理及电磁设计[J].电机技术,2009,6:11-17.
[80]廖勇,姚骏,杨顺昌.交流励磁发电机励磁电源管压降引起的谐波及其消除方法的研究[J].中国电机工程学报,2004,24(4):151-156.
[81]余渝,杨顺昌.电压型逆变器供电的交流励磁电动机的谐波分析[J].核工业自动化,2001(1):24-30.
[82]余渝.考虑谐波后的交流励磁电动机的电磁设计[D].[硕士学位论文],重庆:重庆大学,2001.
[83]李辉,杨顺昌.考虑转子谐波电流影响后双馈电机电磁功率的分析与计算[J].中国电机工程学报,2003,23(7):123-128.
[84] Fan L,Yuvarajan S,Kavasseri R.Harmonic analysis of a DFIG for a wind energy conversion system[J].IEEE Transactions on Energy Conversion,2010,25(1):181-190.
[85]陈荣德.并网风力发电机的技术要求[J].风力发电,1995(1):27-29.
[86]计宗燮.并网风力异步发电机设计参数和节能的关系[J].机电工程,1998,15(2):55-56.
[87]杨强,黄守道,高剑.兆瓦级交流励磁双馈风力发电机的电磁设计研究[J].大电机技术,2007(4):23-28.
[88]张越雷,杨强,黄守道.变速恒频风电机组用双馈异步发电机的设计探讨[J].电气应用,2007,26(12):80-83.
[89]魏静微,谭勇,张宏宇.大型交流励磁双馈风力发电机的设计[J].电机与控制学报,2010,14(5):44-48.
[90] Chad Abbey,Geza Joos.A systematic approach to design and operation of a doubly fed induction generator[J].Electric Power Systems Research,2008,78:399-408.
[91]张胜男.浅谈1.5MW双馈风力发电机定,转子槽型的选择[J].防爆电机,2009,44(4):5-7.
[92]侯小全,周光厚,汪波.兆瓦级绕线式双馈异步发电机总体设计研究[J].东方电机,2005,33(1):57-60.
[93]李松田,贺建华.2.5MW双馈绕线型三相异步风力发电机的研制和开发[J].东方电机,2009,37(4):52-58.
[94]郭亮.新型同步电机的分析与优化研究[D].[博士学位论文],浙江:浙江大学,2006.
[95]史婷娜.低速大转矩永磁同步电机及其控制系统[D].[博士学位论文],天津:天津大学,2009.
[96]范镇南,韩力.电机优化设计技术发展情况[J].电机与控制应用,2006,33(8):3-7.
[97] R Bhuvaneswari,S Subramanian.Optimization of three phase induction motor design using simulated annealing algorithm[J].Electric Power Components and Systems,2005,32(9):947-956.
[98]白凤仙,邵玉槐,孙建中.利用智能型模拟退火算法进行开关磁阻电机磁极几何形状的优化[J].中国电机工程学报,2003,23(1):126-131.
[99] R Kannan,S Subramanian,R Bhuvaneswari.Multiobjective optimal design of three phase induction generator using simulated annealing technique[J].International Journal of Engineering Science and Technology,2010,2(5):1359-1369.
[100]方攸同,魏世泽.基于随机算法的三相异步电动机全局优化[J].中国电机工程学报,2000,20(5):18-21.
[101]乔静秋,陈旭东.基Tabu算法的轮毂式永磁电机优化研究[J].浙江大学学报:工学版,2002,36(6):713-717.
[102] Lhassane Idoumghar,Tsarafidy Raminosoa,Abdellatif Miraoui.New tabu search algorithm to design an electric motor[J] . IEEE Transactions on Magnetics,2009,45(3):1498-1501.
[103]王群京,鲍晓华,倪有源,等.基于支持向量机和遗传算法的爪极发电机建模及参数优化[J].电工技术学报,2006,21(4):57-61.
[104]吴德荣,李景川.遗传算法在电机系列优化设计中的应用研究[J].西安交通大学学报,1999,33(2):14-18.
[105] L Jolly,M A Jabbar,L Qinghua.Design optimization of permanent magnet motors using response surface methodology and genetic algorithm[J].IEEE Transactions on Magnetics,2005,41(10):3928 - 3930.
[106] James Kennedy,Russell Eberhart.Particle swarm optimization[C].IEE Proceedings of International Conference on Neural Networks,Piscataway,NJ:IEEE Service Center,1995:1942-1948.
[107]杨维,李歧强.粒子群优化算法综述[J].中国工程科学,2004,6(5):87-94.
[108]谢美娟,叶云岳.自适应变异粒子群优化算法在水轮发电机优化设计中的应用[J].大电机技术,2005,(5):9-12.
[109]夏永明,付子义,袁世鹰,等.粒子群优化算法在直线感应电机优化设计中的应用[J].中小型电机,2002,29(6):14-16.
[110]郭亮,卢琴芬,叶云岳.基于粒子群算法的直线振动发电机优化设计[J].电机与控制学报,2008,12(4):442-446.
[111]刘爱民,林莘.断路器操动机构用直线感应电机的优化设计[J].电机与控制学报,2009,13(4):528-532, 540.
[112]包广清,江建中.一种新型横向磁通永磁电机的建模与参数优化[J].大电机技术,2008,(4):12-16.
[113]包广清,郑文鹏,江建中.一种改进粒子群算法在横向磁通永磁电机优化中的应用[J].电机与控制应用,2008,35(8):27-31,61.
[114] Raj C T,Strivastava S P,Agarwal P.Realization on PSO based induction motor design via SPEED/PC-IMD[C] . International Conference on Advanced Computer Control,Singapore:IEEE Press,2009:65-69.
[115] Shi Yuhui,Russell Eberhart.A modified particle swarm optimizer[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,1998:69-73.
[116] Liang J J,Qin A K,Suganthan Ponnuthurai,et al.Comprehensive learning particle swarm optimizer for global optimization of multimodal functions [J].IEEE Transactions on Evolutionary Computation,2006,10(3):281-295.
[117] Maurice Clerc.The swarm and the queen: towards a deterministic and adaptive particle swarm optimization[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,1999:1951-1957.
[118] Maurice Clerc,James Kennedy.The particle swarm - explosion,stability,and convergence in a multidimensional complex space[J].IEEE Transactions on Evolutionary Computation,2002,6(1):58-73.
[119] Russell Eberhart,Shi Yuhui.Comparing inertia weights and constriction factors in particle swarm optimization[C].IEEE International Congress on Evolutionary Computation,Piscataway,NJ:IEEE Service Center,2000:84-88.
[120] Asanga Ratnaweera,Saman K. Halgamuge,Harry C. Watson.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J].IEEE Transactions on Evolutionary Computation,2004,8(3):240-255.
[121] Anthony Carlisle,Gerry Dozier.An off-the-shelf PSO[C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2001:1-6.
[122] Shi Yuhui,Russell Eberhart.Fuzzy adaptive particle swarm optimization [C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2001:101-106.
[123]郭文忠,陈国龙.粒子群优化算法中惯性权值调整的一种新策略[J].计算机工程与科学,2007,29(1):70-72,75.
[124]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.
[125] A Ratnaweera,S K Halgamuge,H C Watson.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J].IEEE Transactions on Evolutionary Computation,2004,8(3):240-255.
[126] Natsuki Higashi,Hitoshi Iba.Particle swarm optimization with gaussian mutation[C].Proceedings of the swarm intelligence symposium,Piscataway,NJ:IEEE Service Center,2003:72-79.
[127] Andrew Stacey,Mirjana Jancic,Ian Grundy.Particle swarm optimization with mutation[C].IEEE International Congress on Evolutionary Computation ,Piscataway,NJ:IEEE Service Center,2003:1425-1430.
[128] S H Ling,H H C Iu,K Y Chan,et al.Hybrid particle swarm optimization with wavelet mutation and its industrial applications[J].IEEE Transactions on Systems,man and cybernetics-part B: Cybernetics,2008,38(3):743-763.
[129] Ning Li,Yuan-Qing Qin,De-Bao Sun,et al.Particles swarm optimization with mutation operator[C].Proceedings of the third international conference on machine learning and cybemetics,2004:26-29.
[130] Gao Yuelin.A New Particle Swarm optimization algorithm with adaptive mutation operator[C].2009 Second International Conference on Information and Computing Science,2009:58-61.
[131] Li Changhe,Yang Shengxiang,Korejo Imtiaz.An adaptive mutation operator for particle swarm optimization[C],Proceedings of the 2008 UK Workshop on Computational Intelligence,2008:165-170.
[132] Li Jize,Song Ping,Li Kejie.A modified particle swarm optimization with adaptive selection operator and mutation operator[C] . 2008 International Conference on Computer Science and Software Engineering,2008:1199-1202.
[133] Jacques Riget,J S Vesterstrom.A diversity-guided particle swarm optimizer﹣the ARPSO[R].Denmark:Department of Computer Science,University of Aarhus,2002.
[134] Jie Jing,Zeng Jianchao,Han Chongzhao.Adaptive particle swarm optimization with feedback control of diversity[J] . Computational Intelligence and Bioinformatics,2006,4115:81-92.
[135]王自强,张龙,黄燕丹.飞行控制用无刷直流电动机的优化设计[J].北京航空航天大学学报,2004,30(7):588-592.
[136] I. Das,J.E. Dennis.A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multi-criteria optimization problems [J].Structural Optimization,1997,14:63-69.
[137] Zitzler E,Thiele L.Multi-objective evolutionary algorithms:a comparative case study and the strength pareto approach[J].IEEE Transactions on Evolutionary Computation,1999,3(4):257-271.
[138] Deb K,Pratap A,Agarwal S,et al.A fast and elitist multi-objective genetic algorithm: NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[139] Giampaolo Liuzzi,Stefano Lucidi,Francesco Parasiliti,et al.Multi-objective optimization techniques for the design of induction motors[J] . IEEE Transactions on Magnetics,2003,29(3):1261-1264.
[140]张小玲.粒子群算法在圆筒型直线感应电机优化设计中的应用[D].[硕士学位论文],沈阳:沈阳工业大学,2010.