考虑分布式能源的电力系统优化运营模型研究
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摘要
随着风电和光伏发电等间歇式分布式能源在电网中比重的加大,其出力的随机波动性给电网安全运行带来了很大风险,需要从电网优化调度以及网络优化、规划等多方面研究以缓解分布式能源发电对电网安全可靠运行带来的巨大挑战。考虑分布式能源的电力系统优化运营问题是一个大规模、多目标、多约束、非线性的优化问题,其控制变量具有离散性与连续性相混合的特点,因此,该优化运营问题的建模与求解算法就成了十分重要的研究课题。
根据上述分析以及负荷预测对于调度运营的重要性,本文对短期负荷预测模型、考虑分布式能源的电力系统优化运营问题展开研究,包括日前闭环经济调度问题,考虑风电接入的网络潮流优化问题和考虑分布式能源的网络规划问题,具体研究内容包括以下几个方面：
(1)短期负荷预测是日前经济调度的重要依据,提出了一种基于GARCH误差修正模型的LS-SVM短期负荷预测模型,利用LS-SVM模型对日前负荷进行预测,采用GARCH误差修正模型对预测误差进行修正从而提高预测的精度。
(2)建立了一种基于闭环控制的日前经济调度模型,线性化处理考虑机组组合问题的经济调度模型以及各种约束,同时考虑机组的启停成本,电网运行的安全约束,包括支路输电容量约束以及安全约束。模型求解采用基于预防、校正的交替求解方法,对机组组合模型和基于安全约束的经济调度模型进行迭代交替求解。
(3)建立了一种考虑风电并网的多目标电力系统供电网络优化运营模型,综合考虑发电成本最小和电压稳定裕度最大两个优化目标。问题求解采用了自适应调整的粒子群算法对模型进行优化求解。
(4)建立了一种基于变权预测校正内点法的分布式网络规划模型,对不同类型的可再生分布式发电机组进行优化配置,以网络损耗最小为优化目标,同时考虑了所有分布式发电机组可能的运行方式。为了提高求解效率,模型采用了直角坐标潮流方程和约束条件。
对上述问题的建模与求解不仅可以实现电力系统运行安全性、经济性、环保性等要求,还可以降低发电、输电成本,协调电厂与电网、电网与用户之间的冲突,因此,对考虑分布式能源的电力系统优化运营问题进行研究具有重要的理论价值和现实意义。
With the increasing of intermittent wind power and photovoltaic power in distributed grid, stochastic volatility of power generation has brought risk to the operation of power grids. Therefore, we need alleviate the great challenges of distributed energy generation on the grid safe and reliable operation by optimizing the scheduling, dispatching, planning and other aspects from the grid. Operation optimization models of power system considering distributed energy is a large-scale, multi-objective, multi-constraint and nonlinear optimization problem, and control variables have the characteristics of mixed discrete and continuous phase. Therefore, optimization models of power system operation and their solution algorithm considering the distributed energy system have become an important research topic.
According to analysis mentioned above and the importance of load forecasting to scheduling operations, short-term load forecasting model and optimization models of power system operation are analyzed in this paper, including closed-loop economic dispatch problem, network optimization problems considering wind power access and network planning problem considering distributed energy. Specific research topics are listed in the following:
(1) Short-term load forecasting is an important basis for day-ahead economic dispatch, LS-SVM short-term load forecasting model based on GARCH error correction is proposed in this paper, using LS-SVM model to predict load data. GARCH model is applied to forecast error correction to improve the accuracy of prediction.
(2) The day-ahead economic dispatch model based on closed-loop control is presented, linearizing a variety of constraints and taking into account the unit cost of start and stop, security constraints of power grid operation, including the power flow constraints, voltage security constraints as well as N-1security constraints. Prevention-correction method is employed for solving the unit commitment model and security-constrained economic dispatch model alternately.
(3) A multi-objective power flow optimization model is established considering the wind power and system voltage stability margin simultaneously, including the minimum cost of power generation and maximum voltage stability margin. The problem was solved using the adaptive particle swarm optimization optimization algorithm.
(4) Distributed network planning model based on varied-weight predictor-corrector interior point method is put forward to optimize the allocation of different types of renewable distributed generator. Minimum network losses is used as the objective function, taking into account the operation possibility of distributed generator. In order to improve the efficiency of the problem, the model applies power flow equations and constraints in rectangular coordinates.
By modeling and solving the problem mentioned above, we can not only realize the basic requirements of power system on security, economics, environmental protection, but also can reduce costs of power generation and transmission, and coordinate the conflict between power plants and power grids. Therefore, research on operation optimization models of power system considering distributed energy has important theoretical value and practical significance.
根据上述分析以及负荷预测对于调度运营的重要性,本文对短期负荷预测模型、考虑分布式能源的电力系统优化运营问题展开研究,包括日前闭环经济调度问题,考虑风电接入的网络潮流优化问题和考虑分布式能源的网络规划问题,具体研究内容包括以下几个方面：
(1)短期负荷预测是日前经济调度的重要依据,提出了一种基于GARCH误差修正模型的LS-SVM短期负荷预测模型,利用LS-SVM模型对日前负荷进行预测,采用GARCH误差修正模型对预测误差进行修正从而提高预测的精度。
(2)建立了一种基于闭环控制的日前经济调度模型,线性化处理考虑机组组合问题的经济调度模型以及各种约束,同时考虑机组的启停成本,电网运行的安全约束,包括支路输电容量约束以及安全约束。模型求解采用基于预防、校正的交替求解方法,对机组组合模型和基于安全约束的经济调度模型进行迭代交替求解。
(3)建立了一种考虑风电并网的多目标电力系统供电网络优化运营模型,综合考虑发电成本最小和电压稳定裕度最大两个优化目标。问题求解采用了自适应调整的粒子群算法对模型进行优化求解。
(4)建立了一种基于变权预测校正内点法的分布式网络规划模型,对不同类型的可再生分布式发电机组进行优化配置,以网络损耗最小为优化目标,同时考虑了所有分布式发电机组可能的运行方式。为了提高求解效率,模型采用了直角坐标潮流方程和约束条件。
对上述问题的建模与求解不仅可以实现电力系统运行安全性、经济性、环保性等要求,还可以降低发电、输电成本,协调电厂与电网、电网与用户之间的冲突,因此,对考虑分布式能源的电力系统优化运营问题进行研究具有重要的理论价值和现实意义。
With the increasing of intermittent wind power and photovoltaic power in distributed grid, stochastic volatility of power generation has brought risk to the operation of power grids. Therefore, we need alleviate the great challenges of distributed energy generation on the grid safe and reliable operation by optimizing the scheduling, dispatching, planning and other aspects from the grid. Operation optimization models of power system considering distributed energy is a large-scale, multi-objective, multi-constraint and nonlinear optimization problem, and control variables have the characteristics of mixed discrete and continuous phase. Therefore, optimization models of power system operation and their solution algorithm considering the distributed energy system have become an important research topic.
According to analysis mentioned above and the importance of load forecasting to scheduling operations, short-term load forecasting model and optimization models of power system operation are analyzed in this paper, including closed-loop economic dispatch problem, network optimization problems considering wind power access and network planning problem considering distributed energy. Specific research topics are listed in the following:
(1) Short-term load forecasting is an important basis for day-ahead economic dispatch, LS-SVM short-term load forecasting model based on GARCH error correction is proposed in this paper, using LS-SVM model to predict load data. GARCH model is applied to forecast error correction to improve the accuracy of prediction.
(2) The day-ahead economic dispatch model based on closed-loop control is presented, linearizing a variety of constraints and taking into account the unit cost of start and stop, security constraints of power grid operation, including the power flow constraints, voltage security constraints as well as N-1security constraints. Prevention-correction method is employed for solving the unit commitment model and security-constrained economic dispatch model alternately.
(3) A multi-objective power flow optimization model is established considering the wind power and system voltage stability margin simultaneously, including the minimum cost of power generation and maximum voltage stability margin. The problem was solved using the adaptive particle swarm optimization optimization algorithm.
(4) Distributed network planning model based on varied-weight predictor-corrector interior point method is put forward to optimize the allocation of different types of renewable distributed generator. Minimum network losses is used as the objective function, taking into account the operation possibility of distributed generator. In order to improve the efficiency of the problem, the model applies power flow equations and constraints in rectangular coordinates.
By modeling and solving the problem mentioned above, we can not only realize the basic requirements of power system on security, economics, environmental protection, but also can reduce costs of power generation and transmission, and coordinate the conflict between power plants and power grids. Therefore, research on operation optimization models of power system considering distributed energy has important theoretical value and practical significance.
引文
[1]F. N. Lee. A fuel-constrained unit commitment method[J]. IEEE Trans. Power Syst., 1989,4(3):1208-1218
[2]H. Ma and S. M. Shahidehpour. Decomposition approach to unit commitment with reactive constraints[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1997, 144(2):113-117
[3]K. D. Lee, J. T. Day, B. L. Cooper, and E. W. Gibbons. A global optimization method for scheduling thermal generation, hydro generation, and economy purchase[J]. IEEE Trans. Power App. Syst.,1983,102(7):1983-1986
[4]A. I. Cohen and V. R. Sherkat. Optimization-based methods for operations[C] Proc. IEEE,1987,77:1574-1590
[5]K. Warwick, A. Ekwue, and R. Aggarwal. Artificial intelligence techniques in power systems[C] Inst. Elect. Eng. Power Eng. Series,1997
[6]L. F. B. Baptistella and J. C. Geromel. A decomposition approach to problem of unit commitment schedule for hydro thermal systems[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1980,127(6):250-258
[7]C. Li, R. B. Johnson, and A. F. Svaboda. A new unit commitment method[J]. IEEE Trans. Power Syst.,1997,12(1):113-119
[8]R. Baldick. The generalized unit commitment problem[J]. IEEE Trans. Power Syst., 1995,10(1):465-475
[9]R. Billinton, M. Fotuhi-Firuzabad, and S. Aboreshaid. Unit commitment health analysis for interconnected systems[J]. IEEE Trans. Power Syst.,1997, 12(3):1194-1201
[10]C. Li, E. Hsu, A. J. Svoboda, C. Tseng, and R. B. Johnson. Hydro unit commitment in hydro thermal optimization[J]. IEEE Trans. Power Syst.,1997,12(2):764-769
[11]C. Li, E. Hsu, R. B. Johnson. A robust unit commitment algorithm for hydro-thermal optimization[J]. IEEE Trans. Power Syst.,1998,13(3):1051-1056
[12]M. E. Khan and R. Billinton. Generating unit commitment in composite generation and transmission systems[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1993, 140(5):404-410
[13]D.L. Travers, R.J. Kaye. Dynamic dispatch by constructive dynamic programming[J]. IEEE Trans. Power Syst,1998,13(1):72-78
[14]X.S. Han, H.B. Gooi, D. Kirschen. Dynamic economic dispatch:feasible and optimal solutions[J]. IEEE Trans. Power Syst,2001,16(1):22-28
[15]D. Attaviriyanupap, H. Kita, E. Tanaka, J. Hasegawa. A hybrid EP and SQP for dynamic economic dispatch with nonsmooth incremental fuel cost function[J]. IEEE Trans. Power Syst.2002,17(2):411-416
[16]M. Basu. Particle swarm optimization based goal-attainment method for dynamic economic emission dispatch[J]. Elect. Power Components Syst,2006, 34(8):1015-1025
[17]M. Basu. Dynamic economic emission dispatch using evolutionary programming and fuzzy satisfied method[J]. Int. J. Emerging Elect. Power Syst,2007,8(4):1-15
[18]M. Basu. Dynamic economic emission dispatch using nondominted sorting genetic algprthim-II[J]. Elect. Power Energy Syst,2008,30(2):140-149
[19]P. Attaviriyanupap, H. Kita, E. Tanaka, J. Hasegawa. A fuzzy-optimization approach to dynamic economic dispatch considering uncertainties[J]. IEEE Trans. Power Syst, 2004,19(3):1299-1307
[20]W.M. Lin, S.J. Chen. Bid-based dynamic economic dispatch with an efficient interior point algorithm[J]. Elect. Power Energy Syst,2002,24(1):51-57
[21]Carpentier J. Optimal power Flows[J]. Int. J. Elec Power and Energy System,1979, 1(1):1-3
[22]袁贵川,王建全,韩帧祥.电力市场下的最优潮流[J].电网技术,2004,5(28,)：13-17
[23]Xie K, Song Y H, Stonham J. Decoposition Model and Interior Point Methods for Optimal Spot Pricing of Electricity in Deregulation Environments[J]. IEEE Trans on Power Systems,2000,5(1):39-45
[24]谢开,宋永华,于尔铿,刘广一.基于最优潮流的实时电价分解模型及其内点法实现[J].电力系统自动化,1999,23(2)：5-10
[25]李平,宋燕敏,曹荣章.电力市场中的阻塞调度[J].电力系统自动化,2001,25(13)：11-12
[26]薛志方,李光熹.基于最优潮流的实时电价及其遗传算法实现[J].电网技术,2001,25(06)：25-28
[27]周明华,徐敏.基于最优潮流的实时电价及其算法的研究[J].继电器,2006,34(21)：63-67
[28]李平.电力市场下基于最优潮流的节点电价算法研究[D].西南交通大学,2005
[29]潘敬东,谢开.节点边际电价的优化原理[J].电力系统自动化,2006,30(22)：38-42
[30]刘科研,盛万兴,李运华.基于分布式最优潮流算法的跨区输电阻塞管理研究[J].中国电机工程学报,2007,27(19)：56-61
[31]王兴,宋永华,卢强.多区域输电阻塞管理的拉格朗日松弛分解算法[J].电力系统自动化,2002,26(13)：8-14
[32]商小乐,李建华,刘锐,李夏.基于辅助问题原理及内点法的分区并行最优潮 流算法[J].西安交通大学学报,2006,40(4)：468-472
[33]王永刚,韩学山,王宪荣,柳焯.动态优化潮流[J].中国电机工程学报,1997,17(3)：195-198
[34]刘方,颜伟,徐国禹.动态最优潮流的预测/校正解耦内点法[J].电力系统自动化,2007,31(14)：38-42
[35]XIE K, SONG Y H. Dynamic optimal power flow by interior point methods[J]. IEE Proceedings:Generation, Transmission and Distribution.2001,148(1):76-84
[36]袁贵川,王建全.考虑了动态约束和稳定约束的最优潮流[J].电力系统及其自动化学报,2003,15(3)：1-6
[37]杨明,韩学山,梁军,张利.计及网络安全约束及用户停电损失的动态经济调度方法[J].电力系统自动化,2009,33(14)：27-31
[38]王孟夏,韩学山,杨朋朋,康凯.计及电热耦合的动态最优潮流模型与算法[J].电力系统自动化,2010,34(3)：28-32
[39]覃智君,阳育德,吴杰康.矢量化动态最优潮流计算的步长控制内点法实现[J].中国电机工程学报,2009,29(7)：52-58
[40]杨明,韩学山,梁军,张利.计及用户停电损失的动态经济调度方法[J].中国电机工程学报,2009,29(31)：103-108
[41]傅旭,王锡凡,杜正春.电力系统电压稳定性研究现状及其展望[J].电力自动化设备,2005,25(2)：1-9
[42]黄海伦,韦化,阳育德.电压稳定约束的最优潮流研究[J].电力自动化设备,2007,27(3)：26-29
[43]Gan D, Thomas R J, Zimmerman R D. Stability-constrained optimal power flow[J]. IEEE Trans on Power Systems,2000,15(2):535-540
[44]JAZAYERI P, SHOARINEJAD A, ROSEHART W. Voltage stability constrained optimal power flow[J]. Automation of Electric Power Systems,2005,29(16):48-55
[45]SUN Hua-dong, ZHOU Xiao-xin, LI Ruo-mei. Accuracy analysis of static voltage stability indices based on power flow model[C]. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,2005
[46]KIM S, SONG T Y, JEONG M H, et al. Development of Voltage Stability Constrained Optimal Power Flow(VSCOPF)[C]. Proceedings of IEEE PES Summer Meeting. Vancouver, Canada:IEEE,2001
[47]王勤,方鸽飞.考虑电压稳定性的电力系统多目标无功优化[J].电力系统自动化,1999,23(3)：31-34
[48]Pvuyan Jazayeri, Arash Shoarinejad, William Rosehart.电压稳定约束的最优潮流(英文)[J].电力系统自动化,2005,29(16)：48-55
[49]Menezes T V, da Silva L C P, Affonso C M, et al. MVAR Management on the Pre-dispatch Problem for Improving Voltage Stability Margin[J]. IEE Proceedings-Generation, Transmission and Distribution,2004,151(6):665-672
[50]刘明波,杨勇.计及静态电压稳定约束的无功优化规划[J].电力系统自动化,2005,29(5)：21-25
[51]胡彩娥,杨仁刚.考虑电压稳定的电力系统无功优化规划[J].继电器,2005,33(4)：22-25
[52]Lin X, David A K, Yu C W. Reactive Power Optimization with Voltage Stability Consideration in Power Market Systems[J]. IEE Proceedings-Generation, Transmission and Distribution,2003,150(3):305-310
[53]Venkatesh B, Sadasivam G, Khan M A. A New Optimal Reactive Power Scheduling Method for Loss Minimization and Voltage Stability Margin Maximization Using Successive Multi-objective Fuzzy LP Technique[J]. IEEE Transactions on Power Systems,2000,15(2):844-851
[54]李林川,李磊,黄海浪.市场环境下考虑暂态稳定约束的最优潮流计算[J].天津大学学报,2006,39(9)：1093-1098
[55]徐琳,卢继平,汪洋等.电力系统节点电压稳定指标的研究[J].电网技术,2010,34(3)：26-30
[56]何斌,张秀彬,赵兴勇.考虑故障条件下电压稳定约束的最优潮流[J].高电压技术,2009,35(2)：435-440
[57]韦化,阳育德,李啸骢.多预想故障暂态稳定约束最优潮流[J].中国电机工程学报,2004,24(10)：91-96
[58]孙景强,房大中,锺德成.暂态稳定约束下的最优潮流[J].中国电机工程学报,2005,25(12)：12-17
[59]杨新林,孙元章,王海风.考虑暂态稳定性约束的最优潮流[J].电力系统自动化,2003,27(14)：13-17
[60]李传栋,杨金刚,陈家荣.暂态稳定约束下的最优潮流[J].电力系统及其自动化学报,2009,21(6)：45-50
[61]刘明波,李妍红,陈家荣.基于轨迹灵敏度的暂态稳定约束最优潮流计算[J].电力系统及其自动化学报,2007,19(6)：24-29
[62]孙艳,杭乃善,李如琦.考虑频率质量约束的最优潮流模型[J].中国电机工程学报,2010,30(22)：77-84
[63]顾承红,艾芊.考虑电压稳定约束的最优潮流[J].电网技术,2006,30(16)：29-34
[64]程浩忠,张节潭,欧阳武,姚良忠.主动管理模式下分布式风电源规划[J].电力科学与技术学报,2010,19(24)：12-18
[65]刘科研,盛万兴,李运华.基于分布式最优潮流算法的跨区输电阻塞管理研究[J].中国电机工程学报,2007,19(27)：56-62
[66]Antonios G. Marinopoulosa, Minas C. Alexiadisb, Petros S. Dokopoulosb. Energy losses in a distribution line with distributed generation based on stochastic power flow[J]. Electric Power Systems Research,2011,81(10):1986-1994
[67]Seyed Abbas Taher, Mohammad Hasani, Ali Karimian. A novel method for optimal capacitor placement and sizing in distribution systems with nonlinear loads and DG using GA[J]. Commun Nonlinear Sci Numer Simulat,2011,16(2):851-862
[68]Y. Zhu, K. Tomsovic. Optimal distribution power flow for systems with distributed energy resources[J]. Electrical Power and Energy Systems,2007,29(3):260-267
[69]A. Augugliaro, L. Dusonchet, M.G Ippolito, Sanseverino. Multiobjective design of distributed reactive power production in a deregulated electric market[J]. Electrical Power and Energy Systems,2005,27(3):205-214
[70]Hobson E, Active and Reactive Power Security Control Using Successive Linear Programming[J]. IEEE Transactions on Power Apparatus and Systems,1982, 101(l):644-654
[71]Mamandur K R C, Chenoweth R D, Optimal Control Reactive Power For Improvement In Voltage Profiles And For Real Loss Minimization[J]. IEEE Transactions on Power Apparatus and Systems,1981,100(7):263-269
[72]D.W.Well. Method for Economic Secure Loading of a Power System[J]. Proceedings of IEEE,1968, (11):956-961
[73]K R. Vlamandeur, Optimal Control of Reactive Power Flow For Improvement In Voltage Profiles And Real Power Losses Minimization[J]. IEEE Transactions on Power Apparatus and Systems,1981,100(7):3185-3194
[74]刘明波,程劲晖.电力系统无功综合优化的线性规划内点法[J].电力系统及其自动化学报,1999,11(5)：88-92
[75]刘明波,陈学军.电力系统无功优化的改进内点算法[J].电力系统自动化,1998,22(5)：33-36
[76]Dag, H.; Semlyen, A. A new preconditioned conjugate gradient power flow[J]. IEEE Transactions on Power Systems,2003,18(4):1248-1255
[77]严正,陈雪青,相年德,吴榕,李群炬.优化潮流牛顿算法的研究及应用[J].清华大学学报(自然科学版),1989,29(1)：69-79
[78]张力平,何大愚,朱太秀.牛顿法最优潮流与最优无功补偿[J].中国电机工程学报,1987,7(1)：11-19
[79]王宪荣,包丽明,柳焯,等.快速解耦牛顿法最优潮流[J].中国电机工程学报,1994,14(4)：26-32
[80]Burchett R C, Happ H H, Vierath D R. Quadratically Convergent Optimal Power Flow [J]. IEEE Trans. On Power Apparatus and Systems,1984,103(4):3276-3276
[81]Y C, Debs A S, Marsten R E. A direct nonlinear predictor-correcter primal-dual interior point algorithm for optimal power flows[J]. IEEE Traps on Power Syetem, 1994,9(2):876-883
[82]王永刚,彭世康,靳现林.牛顿法最优潮流的改进[J].继电器,2003,31(3)：1-4
[83]林济铿,李鸿路,仝新宇.基于自适应免疫算法和预测-校正内点法的无功优化[J].天津大学学报,2008,41(2)：168-174
[84]蔡广林,张勇军,任震.基于非线性多中心校正内点法的最优潮流算法[J].电工技术学报,2007,22(12)：134-140
[85]李尹,张伯明,孙宏斌,吴文传.基于非线性内点法的安全约束最优潮流(一)理论分析[J].电力系统自动化,2007,31(19)：7-12
[86]李尹,张伯明,孙宏斌,吴文传.基于非线性内点法的安全约束最优潮流(二)算法实现[J].电力系统自动化,2007,31(20)：6-11
[87]WEI Hua, SASAKI H, KUBOKAWA J et al. An Interior Point Nonlinear Programming for Optimal Power Flow Problems with a Novel Data Structure[J]. IEEE Transactions on Power Systems,1998,13(3):870-877
[88]Patra S, Goswami S K. Optimum power flow solution using a non-interior point method[J]. International Journal of Electrical Power&Energy Systems,2007, 29(2):138-146
[89]覃智君.最优潮流的原对偶内点法矢量化实现[J].电力系统及其自动化学报,2009,21(5)：68-74
[90]XI A Y, CHAN K W, LI U M. Direct nonlinear primal-dual interior-point method for transient stability constrained optimal power flow[J]. IEE Proceedings:Generation, Transmission and Distribution,2005,152(1):11-16
[91]余娟,颜伟,徐国禹,等.基于预测-校正原对偶内点法的无功优化新模型[J].中国电机工程学报,2005,25(11)：146-151
[92]Jabr, R.A., Coonick, A.H., Cory, B.J. A primal-dual interior point method for optimal power flow dispatching[J]. IEEE Transactions on Power Systems,2002, 17(3):654-662
[93]Xia, Y., Chan, K.W., Liu, M. Direct nonlinear primal-dual interior-point method for transient stability constrained optimal power flow[J]. Generation, Transmission and Distribution, IEE Proceedings,2005,152(1):11-16
[94]Hsiao Y T, Liu C C, Chiang H D, et al. A New Approach for Optimal VAR Sources Planning in Large Scale Electric Power Systems [J]. IEEE Trans. on Power System, 1993,8(3):988-996.
[95]Roa-Swpulveda C A, Pavez-Lazo B J. A Solution to the Optimal Power Flow Using Simulated Annealing[J]. Electrical Power and Energy Systems,2003,25(1):47-57
[96]彭慧敏,赵著,谢维廉.基于遗传算法的最优潮流[J].贵州工业大学学报(自然科学版),2003,32(1)：45-48.
[97]文福拴,韩帧祥.基于Tabu搜索方法的输电系统最优规则[J].电网技术,1997,21(5)：2-7
[98]卓峻峰,赵冬梅.基于混沌搜索的多目标模糊优化潮流算法[J].电网技术,2003,27(2)：41-45
[99]孙勇智,韦巍.基于人工免疫算法的电力系统最优潮流计算[J].电力系统自动化,2002,26(12)：30-34
[100]Mori K, Tsukiyama M, Fukuda T. Application of an Immune Algorithm to Multi-optimization Problems.Electrical Engineering in Japan,1998,122(2):30-37.
[101]陈建华,李先允,邓东华等.粒子群优化算法在电力系统中的应用综述[J].继电器,2007,35(23)：77-84.
[102]Abido M A. Optimal Power Flow Using Particle Swarm Optimization[J]. Electrical Power and Energy Systems,2002,24(7):563-571
[103]杨翠茹,韩富春,武天文,张宁.基于遗传算法的FACTS网络最优潮流计算[J].太原理工大学学报,2005,36(3)：320-323
[104]向铁元,周青山,李富鹏,等.小生境遗传算法在无功优化中的应用研究[J].中国电机程学报,2005,25(17)：103-108
[105]Bakirtzis Anastasios, G Gharehpetian, Optimal Reactive Power Flow by Enhanced Genetic Algorithm[J]. IEEE Transactions on Power Systems,2002, 17(2):229-236
[106]Wu Q.H, Cao Y.J, Wen J Y,Optimal Reactive Power Dispatch Using An Adaptive Genetic Algorithm [J]. Electrical Power & Energy Systems,1998,20(8): 563-569
[107]Ma J.T, Lai L.L, New Genetic Algorithm For Optimal Reactive Power Dispatch [J]. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications,1997,5(2):115-120
[108]张文.基于粒子群体优化算法的电力系统无功优化研究[D].济南：山东大学,2006
[109]席照才.基于粒子群体优化算法的输电网规划方法研究[D].保定：华北电力大学,2008
[110]赵波,郭创新,曹一家.基于粒子群优化算法和动态调整罚函数的最优潮流计算[J].电工技术学报,2004,19(5)：47-54
[111]崔鹏程,陈明榜,向铁元.基于粒子群优化算法与混合罚函数法的最优潮流计算[J].电网技术,2006,30：192-195
[112]史继莉,邱晓燕.基于免疫算法的电压稳定裕度计算[J].电力系统及其自动化学报,2007,19(1)：79-83
[113]钟红梅,任震,张勇军,李邦峰.免疫算法及其在电力系统无功优化中的应用[J].电网技术,2004,28(3)：16-19
[114]刘科研,盛万兴,李运华.基于改进免疫遗传算法的无功优化[J].电网技术2007,31(13)：11-16
[115]李秀卿,王水英,葛广林,等.改进免疫算法在电力系统有功优化中的应用[J].东北电力大学学报(自然科学版),2007,27(4)：55-60
[116]C H Liang, C Y Chung, K P Wong. Study of differenial evolution for optimal reactive power flow[J]. IET Gener Tranan Disrib,2007,1(2):253-260
[117]J M. Varadaraj an, K. S.Swarup. Differential evolutionary algorithm for optimal reactive power dispatch[J]. Int. J. Electr. Power Energ. Syst,2008,30(8):435-441
[118]张丰田,宋家弊,李鉴.基于混合差异进化算法分析静态电压的稳定裕度[J].电网技术,2007,31(9)：33-37
[119]Cai, H.R., Chung, C.Y., Wong, K.P. Application of Differential Evolution Algorithm for Transient Stability Constrained Optimal Power Flow[J].Power Systems, IEEE Transactions on,2008,23(2):719-728
[120]刘自发,闰景信,张建华.基于改进微分进化算法的电力系统无功优化[J].电网技术,2007,31(18)：68-73
[121]Varadarajan, M., Swarup, K.S. Solving multi-objective optimal power flow using differential evolution[J]. IET Generation, Transmission & Distribution,2008, 2(5):720-730
[122]Bhagwan Das, D., Patvardhan, C. Useful multi-objective hybrid evolutionary approach to optimal power flow Generation, Transmission and Distribution, IEE Proceedings,2003,150(3):275-282
[123]Fred G, James P k, Manuel L, Hybrids Genetic Algorithms And Tabu Search For Optimization[J]. Computers & Operations Research,1995,22(1):111-134
[124]Liu Yutian, Ma Li, Zhang Jianjun. Reactive Power Optimization By GA/SA/TS Combined Algorithms [J]. International Journal of Electrical Power and Energy Systems,2002,24(9):765-769
[125]Yan Wei, Lu Shuai, Yu David C. A Novel Optimal Reactive Power Dispatch Method Based On An Improved Hybrid Evolutionary Programming Technique[J]. IEEE Transactions on Power Systems,2004,19(2):913-918
[126]刘继春.电力调度优化理论及其应用[M].北京：中国电力出版社,2010
[127]杜松怀,文福拴,李杨,等.电力系统的市场化运营[M].北京：中国电力出版社,2005
[128]沈剑飞.中国电力行业市场改革研究[M].北京：新华出版社,2005
[129]钟海旺,康重庆,陈慧坤,等.广东电网节能发电调度潜力分析[J].电网技术,2008,32(23)：7-12
[130]陈珩.电力系统稳态分析[M].北京：中国电力出版社,2007
[131]赵晶晶.含分布式发电的配电网优化运行研究[D].重庆：重庆大学,2009
[132]王长贵,崔容强,周簧.新能源发电技术[M].北京：中国电力出版社,2003
[133]熊一权.燃料电池发电技术[J].中国电力,1998,31(9)：61-64
[134]牛东晓,曹叔华,赵磊等.电力负荷预测技术及其应用[M].北京:中国电力出版社,1999
[135]D. Papalekopulos and T. C. Hesterberg. A regression-based approach to short-term system load forecasting[J]. IEEE Trans. Power Syst.,1990, 5(4):1535-1547
[136]J. W. Taylor, L. M. de Menezes, and P. E. McSharry. A comparison of univariate methods for forecasting electricity demand up to a day ahead[J]. Int. J. Forecasting,2006,22(1):1-16
[137]J. H. Park, Y. M. Park, and K. Y. Lee. Composite modeling for adaptive short-term load forecasting[J]. IEEE Trans. Power Syst.,1991,6(2):450-457
[138]H. S. Hippert, C. E. Pedreira, and R. C. Souza, Neural networks for shortterm load forecasting:Areviewand evaluation[J]. IEEE Trans. Power Syst., 2001,16(1):44-55
[139]M. Figueiredo, R. Ballini, S. Soares,M. Andrade, and F. Gomide. Learning algorithms for a class of neurofuzzy network and application[J]. IEEE Trans. Syst., Man, Cyber. C,2004,34(3):293-301
[140]C. J. Lin, C. H. Chen, and C. T. Lin. A hybrid of cooperative particle swarm optimization and cultural algorithm for neural fuzzy networks and its prediction applications[J]. IEEE Trans. Syst., Man, Cyber. C,2009,39(1):55-68
[141]Y. Bodyanskiy, S. Popov, and T. Rybalchenko. Multilayer neuro-fuzzy network for short term electric load forecasting[J]. Lect. Notes Comput. Sci., 2008,50(10):339-348
[142]S. Sheng and C. Wang, Integrating radial basis function neural network with fuzzy control for load forecasting in power system[C]. Proc. IEEE Trans. Dist. Conf. Exhib. Asia and Pacific,2005
[143]P. Lauret, E. Fock, R. N. Randrianarivony, and J. F. M. Ramsamy, Bayesian neural network approach to short time load forecasting[J]. Energy Convers. Manage.,2008,49(5):1156-1166
[144]V. N. Vapnik, Statistical Learning Theory[M]. New York:Wiley,1998.
[145]B. Scholkopf, C. Burges, and V. Vapnik, Extracting support data for a given task[C]. Proc.1st Int. Conf. Knowl. Discovery Data Mining,1995
[146]B. Ribeiro, Support vector machines for quality monitoring in a plastic injection molding process[J]. IEEE Trans. Syst., Man, Cybern. C,2005, 35(3):401-410
[147]J. I. Park, S. H. Baek,M. K. Jeong, and S. J. Bae, Dual features functional support vector machines for fault detection of rechargeable batteries[J]. IEEE Trans. Syst., Man, Cybern. C,2009,39(4):480-485
[148]A. J. Smola and B. Scholkopf, A tutorial on support vector regression[M]. Royal Holloway College,1998.
[149]K.W. Lau and Q. H.Wu, Local prediction of non-linear time series using support vector regression[J]. Pattern Recognit.,2008,(41):1539-1547
[150]C. C. Chuang and J. T. Jeng, Selection of initial structures with support vector regression for fuzzy neural networks[J]. Int. J. Fuzzy Syst.,2004, 6(2):63-70
[151]X. Li, B. Hu, and R. Du, Predicting the parts weight in plastic injection molding using least squares support vector regression[J]. IEEE Trans. Syst., Man, Cybern. C,2008,38(6):827-833
[152]J. A. K. Suykens, J. D. Brabanter, L. Lukas, and J. Vandewalle, Weighted least squares support vector machines:Robustness and sparse approximation[J]. Neurocomputing,2002,48(1):85-105
[153]马晓光,孟伟.残差修正法在电力负荷预测中的应用[J].电网技术,2001,24(4)： 21-25
[154]周明,严正,倪以信,等.含误差预测校正的ARIMA电价预测新方法[J].中国电机工程学报,2004,24(12)：63-68
[155]Ren H. L. Predictor-based error correction method in short-term climate prediction. Progress in Natural Science,2008,18(1):129-135
[156]Chen, A.S., M.T. Leung. Regression neural network for error correction in foreign exchange forecasting and trading. Computers & Operations Research, 2004,31(7):1049-1068
[157]Wong, J., A. Chan,& Y.H. Chiang. Forecasting construction manpower demand:A vector error correction model. Building and Environment,2007, 42(8):3030-3041
[158]李刚.水火电系统短期节能发电调度研究与应用[D].大连：大连理工大学,2007
[159]Bollerslev T, Chou R, Kroner K. ARCH modeling in finance[J]. Journal of Econometrics,1992, (52):55-59
[160]Peter Buhlmann, Alexander J M. An algorithm for nonparametric GARCH modeling[J]. Computational Statistics & Data Analysis,2002,40(4):665-683
[161]Fred N. Lee. Short-term thermal unit commitment-a new method[J]. IEEE transactions on power systems,1988,3(2):421-428
[162]Fred N. Lee Qibei Feng. Multi-Area Unit Commitment[J]. IEEE Transactions on Power Systems,1992, (7)2:591-599
[163]Tomonobu Senjyu, Kai Shimabukuro, Katsumi Uezato, Toshihisa Funabashi. A Fast Technique for Unit Commitment Problem by Extended Priority List[J]. IEEE Transactions on Power Systems,2003, (18)2:882-888
[164]Yuan-Yih Hsu, Chung-Ching Su Chih-Chien Liang Chia-Jen Lin, Chiang-Tsung Huang. Dynamic Security Constrained Multi-Area Unit Commitment[J]. IEEEE Transactions on Power Systems,1991,18(2):1049-1055
[165]Su C C, Hsu Y Y.Fuzzy dynamic programming:an application to unit commitment[J]. IEEE Trans on Power Systems,1991,6(3):1231-1237
[166]Van den Bosh P P J, Honderd G. A solution of the unit commitment problem via decomposition and dynamic programming[J]. IEEE Trans on Power Apparatus and Systems,1985,104(7):1684-1690
[167]赵子臣,相年德,夏清,张伯明.应用启发式与逐步动态规划法进行机组最优组合[J].清华大学学报(自然科学版),1997,37(1)：57-60
[168]T. K. Siu, G. A. Nash, and Z. K. Shawwash. A practical hydro, dynamic unit commitment and loading model[J]. IEEE Trans. Power Syst.,2001,16(2):301-306
[169]F. Zhuang and F. D. Galiana. Towards a more rigorous and practical unit commitment by Lagrange relaxation[J]. IEEE Trans. Power Syst.,1988, 3(2):763-773
[170]C. Wang and S. M. Shahidehpour. Ramp-rate limits in unit commitment and economic dispatch incorporating rotor fatigue effect[J]. IEEE Trans. Power Syst., 1994,9(3):1539-1545
[171]C.Wang and S. M. Shahidehpour. Optimal generation scheduling with ramping costs[J]. IEEE Trans. Power Syst.,1995,10(1):60-67
[172]S.-Y. Lai and R. Baldick. Unit commitment with ramp multipliers[J]. IEEE Trans. Power Syst.,1999,14(1):58-64
[173]W. Ongsakul and N. Petcharaks. Unit commitment by enhanced adaptive Lagrangian relaxation[J]. IEEE Trans. Power Syst.,2004,19(1):620-628
[174]Chuan-Ping Cheng, Chih-Wen Liu, and Chun-Chang Liu. Unit Commitment by Lagrangian Relaxation and Genetic Algorithms[J]. IEEE Trans. Power Syst.,2000, 15(2):707-714
[175]Seki, T.; Yamashita, N.; Kawamoto, K. New Local Search Methods for Improving the Lagrangian-Relaxation-Based Unit Commitment Solution[J]. IEEE Trans on Power Systems,2010,25(1):272-283
[176]C. Christober Asir Rajan and M. R. Mohan. An Evolutionary Programming-Based Tabu Search Method for Solving the Unit Commitment Problem[J]. IEEE Trans on Power Systems,2004,19(1):577-584
[177]Simopoulos, D.N.; Kavatza, S.D.; Vournas, C.D. Reliability Constrained Unit Commitment Using Simulated Annealing[J]. IEEE Trans on Power Systems,2006, 21(4):1699-1706
[178]G. K. Purushothama and L. Jenkins. Simulated annealing with local search—A hybrid algorithm for unit commitment[J]. IEEE Trans. Power Syst.,2003, 18(1):273-278
[179]T. S. Dillon, K. W. Edwin, H. D. Kochs, and R. J. Tand. Integer programming approach to the problem of optimal unit commitment with probabilistic reserve determination[J]. IEEE Trans. Power App. Syst.,1978,97(6):2154-2166
[180]J. M. Arroyo and A. J. Conejo. Optimal response of a thermal unit to an electricity spot market[J]. IEEE Trans. Power Syst.,2000,15(3):1098-1104
[181]Antonio Frangioni, Claudio Gentile, and Fabrizio Lacalandra. Tighter Approximated MILP Formulations for Unit Commitment Problems[J]. IEEE Trans on Power Systems,2009,24(1):105-113
[182]徐琳.电力系统电压崩溃风险评估[D].重庆：重庆大学,2009
[183]R.E.Gomory. Outline of an Algorithm for Integer Solutions to Linear programs[J]. Bulletin of the American Mathematical Society,1958,64(5):275-278
[184]Miguel Carrion, and Jose M. Arroyo. A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem[J]. IEEE Transactions on Power Systems,2006,21(3):1371-1378
[185]Yong Fu, Mohammad Shahidehpour, Zuyi Li. AC Contingency Dispatch Based on Security-Constrained Unit Commitment[J]. IEEE Trans on Power Systems,2006, 21(2):897-908
[186]何禹清,彭建春,毛丽林,曹丽华.含多个风电机组的配电网无功优化[J].电力系统自动化,2010,34(19)：37-41
[187]王成山,孙玮,王兴刚.含大型风电场的电力系统最大输电能力计算[J].电力系统自动化,2007,31(2)：17-22
[188]李凤婷,晁勤,童菲,等.风电系统容量的优化配置探讨[J].电力自动化设备,2007,27(6)：36-38
[189]吴义纯,丁明,张立军.含风电场的电力系统潮流计算[J].中国电机工程学报,2005,25(4)：36-39
[190]叶荣,陈皓勇,王钢,等.多风电场并网时安全约束机组组合的混合整数规划解法[J].电力系统自动化,2010,34(5)：29-34
[191]邱威,张建华,刘念.含大型风电场的环境经济调度模型与解法[J].中 国电机工程学报,2011,31(19)：8-15
[192]Chen, C. L., Lee, T. Y. and Jan R. M. Optimal wind thermal coordination dispatch in isolated power systems with large integration of wind capacity[J]. Energy Conversion Management,2006,47(19):3456-3472
[193]Jabr, R. A. and Pal, B. C. Intermittent wind generation in optimal power flow dispatching[J]. IET Gener. Transm. Distrib,2009,3(1):66-74
[194]MIRANDA V., HANG P.S. Economic dispatch model with fuzzy wind constraints and attitudes of dispatchers[J]. IEEE Trans. Power Syst.,2005, 20(4):2143-2145
[195]WANG L., SINGH C. Balancing risk and cost in fuzzy economic dispatch including wind power penetration based on particle swarm optimization[J]. Electr. Power Syst. Res.,2008,78(8):1361-1368
[196]B. Venkatesh, A. Arunagiri, H.B. Gooi. Unified OPF method for maximizing voltage stability margin using successive fuzzy LP[J]. Electric Power Systems Research,2002,64(2):119-128
[197]S. Chakrabarti, B.Jeyasurya. Generation rescheduling using ANN-based computation of parameter sensitivities of the voltage stability margin[J]. Engineering Applications of Artificial Intelligence,2008,21 (8):1164-1169
[198]Xiong Pan, Guoyu Xu. Available transfer capability calculation considering voltage stability margin[J]. Engineering Applications of Artificial Intelligence, 2005,76(9):52-57
[199]Debbie Q. Zhou, U. D. Annakkage, Athula D. Rajapakse. Online Monitoring of Voltage Stability Margin Using an Artificial Neural Network[J]. IEEE Transactions on Power Systems,2010,25(3):1566-1574
[200]Carolina M. Affonso, Luiz C. P. da Silva, Flavio G. M. Lima, and Secundino Soares MW and MVar Management on Supply and Demand Side for Meeting Voltage Stability Margin Criteria[J]. IEEE Transactions on Power Systems,2004, 19(3):1538-1545
[201]Hwachang Song, Byongjun Lee, Sae-Hyuk Kwon, Venkataramana Ajjarapu. Reactive Reserve-Based Contingency Constrained Optimal Power Flow (RCCOPF) for Enhancement of Voltage Stability Margins[J]. IEEE Transactions on Power Systems,2003,18(4):1538-1546
[202]T.V. Menezes, L.C.P. da Silva, C.M. Affonso and V.F. da CostaMVAR management on the pre-dispatch problem for improving voltage stability margin[J]. IEE Proc.-Gener. Transm. Distrib.,2004,151(6):665-672
[203]B. Venkatesh, G. Sadasivam, M. Abdullah Khan. A New Optimal Reactive Power Scheduling Method for Loss Minimization and Voltage Stability Margin Maximization Using Successive Multi-Objective Fuzzy LP Technique[J]. IEEE Transactions on Power Systems,2000,15(2):844-851
[204]Luis A. L1. Zarate, Carlos A. Castro, Jose Luis Martinez Ramos, Esther Romero Ramos. Fast Computation of Voltage Stability Security Margins Using Nonlinear Programming Techniques[J]. IEEE Transactions on Power Systems, 2006,21(1):19-27
[205]H. Song, B. Lee and Y.-H. MoonReactive optimal power flow incorporating margin enhancement constraints with nonlinear interior point method[J]. IEE Proc.-Gener. Transm. Distrib.,2005,152(6):961-968
[206]Eknath Vittal, Mark O'Malley, Andrew Keane. A Steady-State Voltage Stability Analysis of Power Systems With High Penetrations of Wind[J]. IEEE Transactions on Power Systems,2010,25(1):433-442
[207]IEEE/CIGRE Joint Task Force On Stability Terms and Definitions and Classification of Power System stability[J]. IEEE Transactions on Power Systems,2004,19(3):1387-1401
[208]刘明波,谢敏,赵维兴.大电网最优潮流计算[M].北京：科学出版社,2010
[209]R. Tavakkoli-Moghaddam, M. Azarkish, A. Sadeghnejad-Barkousaraie. A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem[J]. Expert Systems with Applications,2011, 38(9):10812-10821
[210]Liu, B., Wang, L.,& Jin, Y. H. An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers[J]. Computers and Operations Research,2008,35(9):2791-2806
[211]Kao, Y.-T.,& Zahara, E. A hybrid genetic algorithm and particle swarm optimization for multimodal functions[J]. Applied Soft Computing,2007, 8(2):849-857
[212]Acharjee, P.,& Goswami, S. K. Expert algorithm based on adaptive particle swarm optimization for power flow analysis[J]. Expert Systems with Applications,2009,36(3):541-552
[213]Gao, L., Yang, L., Zhou, C.,& Hu, Y. Category forecast application of neural network algorithm trained by particle swarm optimization[J]. Computer Integrated Manufacturing Systems,2006,12(3):465-469
[214]Lin, C.-J., Wang, J.-G.,& Lee, C.-Y. Pattern recognition using neural-fuzzy networks based on improved particle swam optimization[J]. Expert Systems with Application,2009,36(3):5402-5541
[215]Alper, U. Improvement of energy demand forecasts using swarm intelligence:The case of Turkey with projections to 2025[J]. Energy Policy, 2008,36(6):1937-1944
[216]Yannis, M., Magdalene, M., Michael, D.,& Constantin, Z. Ant colony and particle swarm optimization for financial classification problems[J]. Expert Systems with Applications,2009,36(7):10604-10611
[217]N. Mo, Z.Y. Zou, K.W. Chan and T.Y.G. Pong Transient stability constrained optimal power flow using particle swarm optimisation[J]. IET Gener. Transm. Distrib.,2007, 1(3):476-483
[218]Pablo E. Onate Yumbla, Juan M. Ramirez, etc. Optimal Power Flow Subject to Security Constraints Solved With a Particle Swarm Optimizer[J]. IEEE Transactions on Power Systems,2008,23(1):33-40
[219]M. R. AlRashidi, and M. E. El-Hawary. Hybrid Particle Swarm Optimization Approach for Solving the Discrete OPF Problem Considering the Valve Loading Effects[J]. IEEE Transactions on Power Systems,2007, 22(4):2030-2038
[220]Ahmed A. A. Esmin, Germano Lambert-Torres, Antonio C. Zambroni de Souza. A Hybrid Particle Swarm Optimization Applied to Loss Power Minimization[J]. IEEE Transactions on Power Systems,2005,22(2):859-866
[221]Sudipta Dutta, S. P. Singh. Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization[J]. IEEE Transactions on Power Systems,2008,23(4):1560-1569
[222]Hirotaka Yoshida, Kenichi Kawata, Shinichi Takayama, Yosuke Nakanishi. A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment[J]. IEEE Transactions on Power Systems,2000,15(4):1232-1239
[223]T.O. Ting, K.P. Wong, C.Y. Chung. Hybrid constrained genetic algorithm/particle swarm optimisation load flow algorithm[J]. IET Gener. Transm. Distrib.,2008,2(6):800-812
[224]R.E.Brown, L. A.A.Freeman. Analyzing the reliability impact of distributed generation[C]. IEEE Power Engineering Society Summer Meeting,2001, 2:1013-1018
[225]王志群.基于微型燃气轮机的分布式发电系统的研究[D].北京：清华大学博士学位论文,2004
[226]J. O. Kim, S. K. Park, K. W. Park, and C. Singh. Dispersed generation planning using improved Hereford Ranch algorithm[J]. Elect. Power Syst. Res., 1998,47(1):47-55
[227]M. Gandomkar, M. Vakilini, and M. Ehsan. Optimal distributed generation allocation in distribution network using Hereford Ranch algorithm[C]. Int. Conf. Electrical Machines and Systems,2005
[228]T. Griffin, K. Tomsovic, D. Secrest, and A. Law. Placement of dispersed generations system for reduced losses[C].33rd Hawaii Int. Conf. System Science,2000
[229]K. Nara, Y. Hayashi, K. Ikeda, and T. Ashizawa. Application of Tabu search to optimum placement of distributed generations[C]. IEEE PES Winter Meeting, 2001
[230]J. A. Greatbanks, D. H. Popovic, M. Begovic, A. Pregelj, and T. C. Green. On optimization for security and reliability of power systems with distributed generation[C]. IEEE Bologna Power Tech Conf,2003
[231]P. N. Vovos, G. P. Harrison, A. R.Wallace, and J. W. Bialek. Optimal power flow as a tool for fault level-constrained network capacity analysis[J]. IEEE Trans. Power Syst.,2005,20(2):734-741
[232]V. H. M. Quezada, J. R. Abbad, and T. G. San Roman. Assessment of energy distribution losses for increasing penetration of distributed generation[J]. IEEE Trans. Power Syst.,2006,21(2):533-540
[233]W. E1-Khattam, K. Bhattacharya, Y. Hegazy, and M. M. A. Salama. Optimal investment planning for distributed generation in a competitive electricity market[J] IEEE Trans. Power Syst.,2004,19(3):1674-1684
[234]G. Celli, E. Ghiani, S. Mocci, and F. Pilo. A multiobjective evolutionary algorithm for the sizing and siting of distributed generation[J]. IEEE Trans. Power Syst.,2005,20(2):750-757
[235]C. Wang and M. H. Nahrir. Analytical approaches for optimal placement of distributed generation sources in power systems[J]. IEEE Trans. Power Syst., 2004,19(4):2068-2076
[236]G. Celli and F. Pilo. Optimal distributed generation allocation in MV network[C].22nd IEEE PES Int. Conf. Power Industry and Computer Applications,2001
[237]G. Celli and F. Pilo. MV network planning under uncertainty on distributed generation penetration[C]. IEEE PES Summer Meeting,2001
[238]G. Carpinelli, G. Celli, F. Pilo, and A. Russo. Distributed generation sitting and sizing under uncertainty[C]. IEEE Porto Power Tech Conf.,2001
[239]L. F. Ochoa, C. J. Dent, and G. P. Harrison. Maximisation of intermittent distributed generation in active networks[C]. CIRED Seminar 2008:SmartGrids for Distribution,2008
[240]A. Keane and M. O'Malley. Optimal distributed generation plant mix with novel loss adjustment factors[C]. IEEE PES General Meeting,2006
[241]A. Keane and M. O'Malley. Optimal utilization of distribution networks for energy harvesting[J]. IEEE Trans. Power Syst.,2007,22(1):467-475
[242]Karmarkar, N. A new polynomial-time algorithm for linear programming[J]. Combinatorica,1984,4(4):373-395
[243]Gill, P.E., Murray, W., Saunders, M.A., et.al. On the projected newton barrier methods for linear programming and an equivalence to Karmarkar's projective method[J]. Math.Programming,1986,36(2):183-209
[244]Barnes, E. R. A vacidon on Uarmarka's algorithm for solving linear programming problems[J]. Marheniaficnl Pmgromming,1986,36(1):174-182
[245]Marslen, R. E. and Snllzmsn, M. J. Implementation of a dual affine interior point algorithm for linear programming[J]. ORSA journal on computing,1989, 1(4):287-297
[246]Saigal, R. Linear Progromming:A modern integrated analysis[M]. Kluwer Academic Publishers,1995
[247]Ponnambalam, K., Quintana, V. H. and Vannellia, A. A fast algorithm for power system optimization problems using an interior point method[J]. IEEE Trans. On Power Systems,1991,7(2):892-899
[248]Vargas, L S, Quintana, V. H. and Vannellia, A. A tutorial description of an interior point method and its application to security-constrained economic dispatch[C]. IEEE/PS Summer Meeting,1992
[249]Salahi, M. Peng, J. and Terlaky, T. On mehrotra-type predictior-corrector algorithms [J]. SIAM Journal on Optimization,2007,18(4):1377-1397
[250]Torres, G. L. and Quintana, V. H. On a nonlinear multiple-centrality corrections interior-point method for optimal power flow [J]. IEEE Trans. Power Systems,2001,16(2):222-228
[251]Megiddo, N. Pathways to the optimal set in linear programming[R]. IBM Almaden Research Center, San Jose, CA, Technical Report RJ 5295,1986
[252]Kojima, M. and Tuncel, L. Monotonicity of primal-dual interior-point algorithms for semidefinite programming problems[J]. Optimization Methods and Software,1998,10(2):275-296
[253]缪楠林,刘明波,赵维兴.电力系统动态无功优化并行算法及其实现[J].电工技术学报,2009,24(2)：150-157
[254]孙艳,杭乃善,李如琦.考虑频率质量约束的最优潮流模型[J].中国电机工程学报,2010,30(22)：77-84
[255]黄镇,杨京燕,覃智君,等.采用内点法的多目标低电压风险优化[J].电力系统及其自动化学报,2011,23(2)：92-97
[256]涂福荣,王晓茹.电力系统无功优化模糊建模研究[J].电力系统保护与控制,2010,38(13)：46-49
[257]周悦,程浩忠,熊宁,等.危险负荷增长方式下考虑静态电压稳定裕度的无功优化[J].水电能源科学,2010,28(3)：152-155
[258]Wu, Y. C., Debs, A. S., Marsten, R. E. A direct nonlinear predictor-corrector primal-dual interior point algorithm for optimal power flow[J]. IEEE Trans. on Power Systems.1994,9(2):876-883
[259]程军照,李澍森,程强.一种无功优化预测校正内点算法[J].电工技术学报,2010,25(2)：152-158
[260]徐进东,丁晓群,覃振成.基于非线性预报-校正内点法的电力系统无功优化研究[J].电网技术,2005,29(9)：36-39
[261]刘雪连,段振刚,王坚,尹诗杭.考虑电压安全裕度的多目标最优潮流模糊建模[J].电工技术学报,2011,35(12)：112-116
[262]J. Nocedal, S.J. Wright, Numerical Optimization[M]. New York: Springer-Verlag,1999
[263]Cartis C. Some disadvantages of a Mehrotra-type pri-mal-dual corrector interior point algorithm for linear programming[J]. Applied Numerical Mathematics,2009, 59(5):1110-1119
[264]Z. M. Salameh, B. S. Borowy, and A. R. A. Amin. Photovoltaic module-site matching based on the capacity factors[J]. IEEE Trans. Energy Convers.,1995, 10(2):326-332
[265]G. Boyle, Renewable Energy[M]. Oxford, U.K.:Oxford Univ. Press,2004
[266]J. Hetzer, C. Yu, and K. Bhattarai. An economic dispatch model incorporating wind power[J]. IEEE Trans. Energy Convers.,2008,23(2):603-611
[267]Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, R. Seethapathy. Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization[J]. IEEE Transactions on Power Systems,2010,25(1):360-370
[268]X.P. Zhang, S.G. Petoussis and K.R. Godfrey. Nonlinear interior-point optimal power flow method based on a current mismatch formulation[J]. IEE Proc.-Gener. Transm. Distrib.,2005,152(6):795-805
[2]H. Ma and S. M. Shahidehpour. Decomposition approach to unit commitment with reactive constraints[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1997, 144(2):113-117
[3]K. D. Lee, J. T. Day, B. L. Cooper, and E. W. Gibbons. A global optimization method for scheduling thermal generation, hydro generation, and economy purchase[J]. IEEE Trans. Power App. Syst.,1983,102(7):1983-1986
[4]A. I. Cohen and V. R. Sherkat. Optimization-based methods for operations[C] Proc. IEEE,1987,77:1574-1590
[5]K. Warwick, A. Ekwue, and R. Aggarwal. Artificial intelligence techniques in power systems[C] Inst. Elect. Eng. Power Eng. Series,1997
[6]L. F. B. Baptistella and J. C. Geromel. A decomposition approach to problem of unit commitment schedule for hydro thermal systems[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1980,127(6):250-258
[7]C. Li, R. B. Johnson, and A. F. Svaboda. A new unit commitment method[J]. IEEE Trans. Power Syst.,1997,12(1):113-119
[8]R. Baldick. The generalized unit commitment problem[J]. IEEE Trans. Power Syst., 1995,10(1):465-475
[9]R. Billinton, M. Fotuhi-Firuzabad, and S. Aboreshaid. Unit commitment health analysis for interconnected systems[J]. IEEE Trans. Power Syst.,1997, 12(3):1194-1201
[10]C. Li, E. Hsu, A. J. Svoboda, C. Tseng, and R. B. Johnson. Hydro unit commitment in hydro thermal optimization[J]. IEEE Trans. Power Syst.,1997,12(2):764-769
[11]C. Li, E. Hsu, R. B. Johnson. A robust unit commitment algorithm for hydro-thermal optimization[J]. IEEE Trans. Power Syst.,1998,13(3):1051-1056
[12]M. E. Khan and R. Billinton. Generating unit commitment in composite generation and transmission systems[J]. Proc. Inst. Elect. Eng., Gen. Transm. Dist.,1993, 140(5):404-410
[13]D.L. Travers, R.J. Kaye. Dynamic dispatch by constructive dynamic programming[J]. IEEE Trans. Power Syst,1998,13(1):72-78
[14]X.S. Han, H.B. Gooi, D. Kirschen. Dynamic economic dispatch:feasible and optimal solutions[J]. IEEE Trans. Power Syst,2001,16(1):22-28
[15]D. Attaviriyanupap, H. Kita, E. Tanaka, J. Hasegawa. A hybrid EP and SQP for dynamic economic dispatch with nonsmooth incremental fuel cost function[J]. IEEE Trans. Power Syst.2002,17(2):411-416
[16]M. Basu. Particle swarm optimization based goal-attainment method for dynamic economic emission dispatch[J]. Elect. Power Components Syst,2006, 34(8):1015-1025
[17]M. Basu. Dynamic economic emission dispatch using evolutionary programming and fuzzy satisfied method[J]. Int. J. Emerging Elect. Power Syst,2007,8(4):1-15
[18]M. Basu. Dynamic economic emission dispatch using nondominted sorting genetic algprthim-II[J]. Elect. Power Energy Syst,2008,30(2):140-149
[19]P. Attaviriyanupap, H. Kita, E. Tanaka, J. Hasegawa. A fuzzy-optimization approach to dynamic economic dispatch considering uncertainties[J]. IEEE Trans. Power Syst, 2004,19(3):1299-1307
[20]W.M. Lin, S.J. Chen. Bid-based dynamic economic dispatch with an efficient interior point algorithm[J]. Elect. Power Energy Syst,2002,24(1):51-57
[21]Carpentier J. Optimal power Flows[J]. Int. J. Elec Power and Energy System,1979, 1(1):1-3
[22]袁贵川,王建全,韩帧祥.电力市场下的最优潮流[J].电网技术,2004,5(28,)：13-17
[23]Xie K, Song Y H, Stonham J. Decoposition Model and Interior Point Methods for Optimal Spot Pricing of Electricity in Deregulation Environments[J]. IEEE Trans on Power Systems,2000,5(1):39-45
[24]谢开,宋永华,于尔铿,刘广一.基于最优潮流的实时电价分解模型及其内点法实现[J].电力系统自动化,1999,23(2)：5-10
[25]李平,宋燕敏,曹荣章.电力市场中的阻塞调度[J].电力系统自动化,2001,25(13)：11-12
[26]薛志方,李光熹.基于最优潮流的实时电价及其遗传算法实现[J].电网技术,2001,25(06)：25-28
[27]周明华,徐敏.基于最优潮流的实时电价及其算法的研究[J].继电器,2006,34(21)：63-67
[28]李平.电力市场下基于最优潮流的节点电价算法研究[D].西南交通大学,2005
[29]潘敬东,谢开.节点边际电价的优化原理[J].电力系统自动化,2006,30(22)：38-42
[30]刘科研,盛万兴,李运华.基于分布式最优潮流算法的跨区输电阻塞管理研究[J].中国电机工程学报,2007,27(19)：56-61
[31]王兴,宋永华,卢强.多区域输电阻塞管理的拉格朗日松弛分解算法[J].电力系统自动化,2002,26(13)：8-14
[32]商小乐,李建华,刘锐,李夏.基于辅助问题原理及内点法的分区并行最优潮 流算法[J].西安交通大学学报,2006,40(4)：468-472
[33]王永刚,韩学山,王宪荣,柳焯.动态优化潮流[J].中国电机工程学报,1997,17(3)：195-198
[34]刘方,颜伟,徐国禹.动态最优潮流的预测/校正解耦内点法[J].电力系统自动化,2007,31(14)：38-42
[35]XIE K, SONG Y H. Dynamic optimal power flow by interior point methods[J]. IEE Proceedings:Generation, Transmission and Distribution.2001,148(1):76-84
[36]袁贵川,王建全.考虑了动态约束和稳定约束的最优潮流[J].电力系统及其自动化学报,2003,15(3)：1-6
[37]杨明,韩学山,梁军,张利.计及网络安全约束及用户停电损失的动态经济调度方法[J].电力系统自动化,2009,33(14)：27-31
[38]王孟夏,韩学山,杨朋朋,康凯.计及电热耦合的动态最优潮流模型与算法[J].电力系统自动化,2010,34(3)：28-32
[39]覃智君,阳育德,吴杰康.矢量化动态最优潮流计算的步长控制内点法实现[J].中国电机工程学报,2009,29(7)：52-58
[40]杨明,韩学山,梁军,张利.计及用户停电损失的动态经济调度方法[J].中国电机工程学报,2009,29(31)：103-108
[41]傅旭,王锡凡,杜正春.电力系统电压稳定性研究现状及其展望[J].电力自动化设备,2005,25(2)：1-9
[42]黄海伦,韦化,阳育德.电压稳定约束的最优潮流研究[J].电力自动化设备,2007,27(3)：26-29
[43]Gan D, Thomas R J, Zimmerman R D. Stability-constrained optimal power flow[J]. IEEE Trans on Power Systems,2000,15(2):535-540
[44]JAZAYERI P, SHOARINEJAD A, ROSEHART W. Voltage stability constrained optimal power flow[J]. Automation of Electric Power Systems,2005,29(16):48-55
[45]SUN Hua-dong, ZHOU Xiao-xin, LI Ruo-mei. Accuracy analysis of static voltage stability indices based on power flow model[C]. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,2005
[46]KIM S, SONG T Y, JEONG M H, et al. Development of Voltage Stability Constrained Optimal Power Flow(VSCOPF)[C]. Proceedings of IEEE PES Summer Meeting. Vancouver, Canada:IEEE,2001
[47]王勤,方鸽飞.考虑电压稳定性的电力系统多目标无功优化[J].电力系统自动化,1999,23(3)：31-34
[48]Pvuyan Jazayeri, Arash Shoarinejad, William Rosehart.电压稳定约束的最优潮流(英文)[J].电力系统自动化,2005,29(16)：48-55
[49]Menezes T V, da Silva L C P, Affonso C M, et al. MVAR Management on the Pre-dispatch Problem for Improving Voltage Stability Margin[J]. IEE Proceedings-Generation, Transmission and Distribution,2004,151(6):665-672
[50]刘明波,杨勇.计及静态电压稳定约束的无功优化规划[J].电力系统自动化,2005,29(5)：21-25
[51]胡彩娥,杨仁刚.考虑电压稳定的电力系统无功优化规划[J].继电器,2005,33(4)：22-25
[52]Lin X, David A K, Yu C W. Reactive Power Optimization with Voltage Stability Consideration in Power Market Systems[J]. IEE Proceedings-Generation, Transmission and Distribution,2003,150(3):305-310
[53]Venkatesh B, Sadasivam G, Khan M A. A New Optimal Reactive Power Scheduling Method for Loss Minimization and Voltage Stability Margin Maximization Using Successive Multi-objective Fuzzy LP Technique[J]. IEEE Transactions on Power Systems,2000,15(2):844-851
[54]李林川,李磊,黄海浪.市场环境下考虑暂态稳定约束的最优潮流计算[J].天津大学学报,2006,39(9)：1093-1098
[55]徐琳,卢继平,汪洋等.电力系统节点电压稳定指标的研究[J].电网技术,2010,34(3)：26-30
[56]何斌,张秀彬,赵兴勇.考虑故障条件下电压稳定约束的最优潮流[J].高电压技术,2009,35(2)：435-440
[57]韦化,阳育德,李啸骢.多预想故障暂态稳定约束最优潮流[J].中国电机工程学报,2004,24(10)：91-96
[58]孙景强,房大中,锺德成.暂态稳定约束下的最优潮流[J].中国电机工程学报,2005,25(12)：12-17
[59]杨新林,孙元章,王海风.考虑暂态稳定性约束的最优潮流[J].电力系统自动化,2003,27(14)：13-17
[60]李传栋,杨金刚,陈家荣.暂态稳定约束下的最优潮流[J].电力系统及其自动化学报,2009,21(6)：45-50
[61]刘明波,李妍红,陈家荣.基于轨迹灵敏度的暂态稳定约束最优潮流计算[J].电力系统及其自动化学报,2007,19(6)：24-29
[62]孙艳,杭乃善,李如琦.考虑频率质量约束的最优潮流模型[J].中国电机工程学报,2010,30(22)：77-84
[63]顾承红,艾芊.考虑电压稳定约束的最优潮流[J].电网技术,2006,30(16)：29-34
[64]程浩忠,张节潭,欧阳武,姚良忠.主动管理模式下分布式风电源规划[J].电力科学与技术学报,2010,19(24)：12-18
[65]刘科研,盛万兴,李运华.基于分布式最优潮流算法的跨区输电阻塞管理研究[J].中国电机工程学报,2007,19(27)：56-62
[66]Antonios G. Marinopoulosa, Minas C. Alexiadisb, Petros S. Dokopoulosb. Energy losses in a distribution line with distributed generation based on stochastic power flow[J]. Electric Power Systems Research,2011,81(10):1986-1994
[67]Seyed Abbas Taher, Mohammad Hasani, Ali Karimian. A novel method for optimal capacitor placement and sizing in distribution systems with nonlinear loads and DG using GA[J]. Commun Nonlinear Sci Numer Simulat,2011,16(2):851-862
[68]Y. Zhu, K. Tomsovic. Optimal distribution power flow for systems with distributed energy resources[J]. Electrical Power and Energy Systems,2007,29(3):260-267
[69]A. Augugliaro, L. Dusonchet, M.G Ippolito, Sanseverino. Multiobjective design of distributed reactive power production in a deregulated electric market[J]. Electrical Power and Energy Systems,2005,27(3):205-214
[70]Hobson E, Active and Reactive Power Security Control Using Successive Linear Programming[J]. IEEE Transactions on Power Apparatus and Systems,1982, 101(l):644-654
[71]Mamandur K R C, Chenoweth R D, Optimal Control Reactive Power For Improvement In Voltage Profiles And For Real Loss Minimization[J]. IEEE Transactions on Power Apparatus and Systems,1981,100(7):263-269
[72]D.W.Well. Method for Economic Secure Loading of a Power System[J]. Proceedings of IEEE,1968, (11):956-961
[73]K R. Vlamandeur, Optimal Control of Reactive Power Flow For Improvement In Voltage Profiles And Real Power Losses Minimization[J]. IEEE Transactions on Power Apparatus and Systems,1981,100(7):3185-3194
[74]刘明波,程劲晖.电力系统无功综合优化的线性规划内点法[J].电力系统及其自动化学报,1999,11(5)：88-92
[75]刘明波,陈学军.电力系统无功优化的改进内点算法[J].电力系统自动化,1998,22(5)：33-36
[76]Dag, H.; Semlyen, A. A new preconditioned conjugate gradient power flow[J]. IEEE Transactions on Power Systems,2003,18(4):1248-1255
[77]严正,陈雪青,相年德,吴榕,李群炬.优化潮流牛顿算法的研究及应用[J].清华大学学报(自然科学版),1989,29(1)：69-79
[78]张力平,何大愚,朱太秀.牛顿法最优潮流与最优无功补偿[J].中国电机工程学报,1987,7(1)：11-19
[79]王宪荣,包丽明,柳焯,等.快速解耦牛顿法最优潮流[J].中国电机工程学报,1994,14(4)：26-32
[80]Burchett R C, Happ H H, Vierath D R. Quadratically Convergent Optimal Power Flow [J]. IEEE Trans. On Power Apparatus and Systems,1984,103(4):3276-3276
[81]Y C, Debs A S, Marsten R E. A direct nonlinear predictor-correcter primal-dual interior point algorithm for optimal power flows[J]. IEEE Traps on Power Syetem, 1994,9(2):876-883
[82]王永刚,彭世康,靳现林.牛顿法最优潮流的改进[J].继电器,2003,31(3)：1-4
[83]林济铿,李鸿路,仝新宇.基于自适应免疫算法和预测-校正内点法的无功优化[J].天津大学学报,2008,41(2)：168-174
[84]蔡广林,张勇军,任震.基于非线性多中心校正内点法的最优潮流算法[J].电工技术学报,2007,22(12)：134-140
[85]李尹,张伯明,孙宏斌,吴文传.基于非线性内点法的安全约束最优潮流(一)理论分析[J].电力系统自动化,2007,31(19)：7-12
[86]李尹,张伯明,孙宏斌,吴文传.基于非线性内点法的安全约束最优潮流(二)算法实现[J].电力系统自动化,2007,31(20)：6-11
[87]WEI Hua, SASAKI H, KUBOKAWA J et al. An Interior Point Nonlinear Programming for Optimal Power Flow Problems with a Novel Data Structure[J]. IEEE Transactions on Power Systems,1998,13(3):870-877
[88]Patra S, Goswami S K. Optimum power flow solution using a non-interior point method[J]. International Journal of Electrical Power&Energy Systems,2007, 29(2):138-146
[89]覃智君.最优潮流的原对偶内点法矢量化实现[J].电力系统及其自动化学报,2009,21(5)：68-74
[90]XI A Y, CHAN K W, LI U M. Direct nonlinear primal-dual interior-point method for transient stability constrained optimal power flow[J]. IEE Proceedings:Generation, Transmission and Distribution,2005,152(1):11-16
[91]余娟,颜伟,徐国禹,等.基于预测-校正原对偶内点法的无功优化新模型[J].中国电机工程学报,2005,25(11)：146-151
[92]Jabr, R.A., Coonick, A.H., Cory, B.J. A primal-dual interior point method for optimal power flow dispatching[J]. IEEE Transactions on Power Systems,2002, 17(3):654-662
[93]Xia, Y., Chan, K.W., Liu, M. Direct nonlinear primal-dual interior-point method for transient stability constrained optimal power flow[J]. Generation, Transmission and Distribution, IEE Proceedings,2005,152(1):11-16
[94]Hsiao Y T, Liu C C, Chiang H D, et al. A New Approach for Optimal VAR Sources Planning in Large Scale Electric Power Systems [J]. IEEE Trans. on Power System, 1993,8(3):988-996.
[95]Roa-Swpulveda C A, Pavez-Lazo B J. A Solution to the Optimal Power Flow Using Simulated Annealing[J]. Electrical Power and Energy Systems,2003,25(1):47-57
[96]彭慧敏,赵著,谢维廉.基于遗传算法的最优潮流[J].贵州工业大学学报(自然科学版),2003,32(1)：45-48.
[97]文福拴,韩帧祥.基于Tabu搜索方法的输电系统最优规则[J].电网技术,1997,21(5)：2-7
[98]卓峻峰,赵冬梅.基于混沌搜索的多目标模糊优化潮流算法[J].电网技术,2003,27(2)：41-45
[99]孙勇智,韦巍.基于人工免疫算法的电力系统最优潮流计算[J].电力系统自动化,2002,26(12)：30-34
[100]Mori K, Tsukiyama M, Fukuda T. Application of an Immune Algorithm to Multi-optimization Problems.Electrical Engineering in Japan,1998,122(2):30-37.
[101]陈建华,李先允,邓东华等.粒子群优化算法在电力系统中的应用综述[J].继电器,2007,35(23)：77-84.
[102]Abido M A. Optimal Power Flow Using Particle Swarm Optimization[J]. Electrical Power and Energy Systems,2002,24(7):563-571
[103]杨翠茹,韩富春,武天文,张宁.基于遗传算法的FACTS网络最优潮流计算[J].太原理工大学学报,2005,36(3)：320-323
[104]向铁元,周青山,李富鹏,等.小生境遗传算法在无功优化中的应用研究[J].中国电机程学报,2005,25(17)：103-108
[105]Bakirtzis Anastasios, G Gharehpetian, Optimal Reactive Power Flow by Enhanced Genetic Algorithm[J]. IEEE Transactions on Power Systems,2002, 17(2):229-236
[106]Wu Q.H, Cao Y.J, Wen J Y,Optimal Reactive Power Dispatch Using An Adaptive Genetic Algorithm [J]. Electrical Power & Energy Systems,1998,20(8): 563-569
[107]Ma J.T, Lai L.L, New Genetic Algorithm For Optimal Reactive Power Dispatch [J]. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications,1997,5(2):115-120
[108]张文.基于粒子群体优化算法的电力系统无功优化研究[D].济南：山东大学,2006
[109]席照才.基于粒子群体优化算法的输电网规划方法研究[D].保定：华北电力大学,2008
[110]赵波,郭创新,曹一家.基于粒子群优化算法和动态调整罚函数的最优潮流计算[J].电工技术学报,2004,19(5)：47-54
[111]崔鹏程,陈明榜,向铁元.基于粒子群优化算法与混合罚函数法的最优潮流计算[J].电网技术,2006,30：192-195
[112]史继莉,邱晓燕.基于免疫算法的电压稳定裕度计算[J].电力系统及其自动化学报,2007,19(1)：79-83
[113]钟红梅,任震,张勇军,李邦峰.免疫算法及其在电力系统无功优化中的应用[J].电网技术,2004,28(3)：16-19
[114]刘科研,盛万兴,李运华.基于改进免疫遗传算法的无功优化[J].电网技术2007,31(13)：11-16
[115]李秀卿,王水英,葛广林,等.改进免疫算法在电力系统有功优化中的应用[J].东北电力大学学报(自然科学版),2007,27(4)：55-60
[116]C H Liang, C Y Chung, K P Wong. Study of differenial evolution for optimal reactive power flow[J]. IET Gener Tranan Disrib,2007,1(2):253-260
[117]J M. Varadaraj an, K. S.Swarup. Differential evolutionary algorithm for optimal reactive power dispatch[J]. Int. J. Electr. Power Energ. Syst,2008,30(8):435-441
[118]张丰田,宋家弊,李鉴.基于混合差异进化算法分析静态电压的稳定裕度[J].电网技术,2007,31(9)：33-37
[119]Cai, H.R., Chung, C.Y., Wong, K.P. Application of Differential Evolution Algorithm for Transient Stability Constrained Optimal Power Flow[J].Power Systems, IEEE Transactions on,2008,23(2):719-728
[120]刘自发,闰景信,张建华.基于改进微分进化算法的电力系统无功优化[J].电网技术,2007,31(18)：68-73
[121]Varadarajan, M., Swarup, K.S. Solving multi-objective optimal power flow using differential evolution[J]. IET Generation, Transmission & Distribution,2008, 2(5):720-730
[122]Bhagwan Das, D., Patvardhan, C. Useful multi-objective hybrid evolutionary approach to optimal power flow Generation, Transmission and Distribution, IEE Proceedings,2003,150(3):275-282
[123]Fred G, James P k, Manuel L, Hybrids Genetic Algorithms And Tabu Search For Optimization[J]. Computers & Operations Research,1995,22(1):111-134
[124]Liu Yutian, Ma Li, Zhang Jianjun. Reactive Power Optimization By GA/SA/TS Combined Algorithms [J]. International Journal of Electrical Power and Energy Systems,2002,24(9):765-769
[125]Yan Wei, Lu Shuai, Yu David C. A Novel Optimal Reactive Power Dispatch Method Based On An Improved Hybrid Evolutionary Programming Technique[J]. IEEE Transactions on Power Systems,2004,19(2):913-918
[126]刘继春.电力调度优化理论及其应用[M].北京：中国电力出版社,2010
[127]杜松怀,文福拴,李杨,等.电力系统的市场化运营[M].北京：中国电力出版社,2005
[128]沈剑飞.中国电力行业市场改革研究[M].北京：新华出版社,2005
[129]钟海旺,康重庆,陈慧坤,等.广东电网节能发电调度潜力分析[J].电网技术,2008,32(23)：7-12
[130]陈珩.电力系统稳态分析[M].北京：中国电力出版社,2007
[131]赵晶晶.含分布式发电的配电网优化运行研究[D].重庆：重庆大学,2009
[132]王长贵,崔容强,周簧.新能源发电技术[M].北京：中国电力出版社,2003
[133]熊一权.燃料电池发电技术[J].中国电力,1998,31(9)：61-64
[134]牛东晓,曹叔华,赵磊等.电力负荷预测技术及其应用[M].北京:中国电力出版社,1999
[135]D. Papalekopulos and T. C. Hesterberg. A regression-based approach to short-term system load forecasting[J]. IEEE Trans. Power Syst.,1990, 5(4):1535-1547
[136]J. W. Taylor, L. M. de Menezes, and P. E. McSharry. A comparison of univariate methods for forecasting electricity demand up to a day ahead[J]. Int. J. Forecasting,2006,22(1):1-16
[137]J. H. Park, Y. M. Park, and K. Y. Lee. Composite modeling for adaptive short-term load forecasting[J]. IEEE Trans. Power Syst.,1991,6(2):450-457
[138]H. S. Hippert, C. E. Pedreira, and R. C. Souza, Neural networks for shortterm load forecasting:Areviewand evaluation[J]. IEEE Trans. Power Syst., 2001,16(1):44-55
[139]M. Figueiredo, R. Ballini, S. Soares,M. Andrade, and F. Gomide. Learning algorithms for a class of neurofuzzy network and application[J]. IEEE Trans. Syst., Man, Cyber. C,2004,34(3):293-301
[140]C. J. Lin, C. H. Chen, and C. T. Lin. A hybrid of cooperative particle swarm optimization and cultural algorithm for neural fuzzy networks and its prediction applications[J]. IEEE Trans. Syst., Man, Cyber. C,2009,39(1):55-68
[141]Y. Bodyanskiy, S. Popov, and T. Rybalchenko. Multilayer neuro-fuzzy network for short term electric load forecasting[J]. Lect. Notes Comput. Sci., 2008,50(10):339-348
[142]S. Sheng and C. Wang, Integrating radial basis function neural network with fuzzy control for load forecasting in power system[C]. Proc. IEEE Trans. Dist. Conf. Exhib. Asia and Pacific,2005
[143]P. Lauret, E. Fock, R. N. Randrianarivony, and J. F. M. Ramsamy, Bayesian neural network approach to short time load forecasting[J]. Energy Convers. Manage.,2008,49(5):1156-1166
[144]V. N. Vapnik, Statistical Learning Theory[M]. New York:Wiley,1998.
[145]B. Scholkopf, C. Burges, and V. Vapnik, Extracting support data for a given task[C]. Proc.1st Int. Conf. Knowl. Discovery Data Mining,1995
[146]B. Ribeiro, Support vector machines for quality monitoring in a plastic injection molding process[J]. IEEE Trans. Syst., Man, Cybern. C,2005, 35(3):401-410
[147]J. I. Park, S. H. Baek,M. K. Jeong, and S. J. Bae, Dual features functional support vector machines for fault detection of rechargeable batteries[J]. IEEE Trans. Syst., Man, Cybern. C,2009,39(4):480-485
[148]A. J. Smola and B. Scholkopf, A tutorial on support vector regression[M]. Royal Holloway College,1998.
[149]K.W. Lau and Q. H.Wu, Local prediction of non-linear time series using support vector regression[J]. Pattern Recognit.,2008,(41):1539-1547
[150]C. C. Chuang and J. T. Jeng, Selection of initial structures with support vector regression for fuzzy neural networks[J]. Int. J. Fuzzy Syst.,2004, 6(2):63-70
[151]X. Li, B. Hu, and R. Du, Predicting the parts weight in plastic injection molding using least squares support vector regression[J]. IEEE Trans. Syst., Man, Cybern. C,2008,38(6):827-833
[152]J. A. K. Suykens, J. D. Brabanter, L. Lukas, and J. Vandewalle, Weighted least squares support vector machines:Robustness and sparse approximation[J]. Neurocomputing,2002,48(1):85-105
[153]马晓光,孟伟.残差修正法在电力负荷预测中的应用[J].电网技术,2001,24(4)： 21-25
[154]周明,严正,倪以信,等.含误差预测校正的ARIMA电价预测新方法[J].中国电机工程学报,2004,24(12)：63-68
[155]Ren H. L. Predictor-based error correction method in short-term climate prediction. Progress in Natural Science,2008,18(1):129-135
[156]Chen, A.S., M.T. Leung. Regression neural network for error correction in foreign exchange forecasting and trading. Computers & Operations Research, 2004,31(7):1049-1068
[157]Wong, J., A. Chan,& Y.H. Chiang. Forecasting construction manpower demand:A vector error correction model. Building and Environment,2007, 42(8):3030-3041
[158]李刚.水火电系统短期节能发电调度研究与应用[D].大连：大连理工大学,2007
[159]Bollerslev T, Chou R, Kroner K. ARCH modeling in finance[J]. Journal of Econometrics,1992, (52):55-59
[160]Peter Buhlmann, Alexander J M. An algorithm for nonparametric GARCH modeling[J]. Computational Statistics & Data Analysis,2002,40(4):665-683
[161]Fred N. Lee. Short-term thermal unit commitment-a new method[J]. IEEE transactions on power systems,1988,3(2):421-428
[162]Fred N. Lee Qibei Feng. Multi-Area Unit Commitment[J]. IEEE Transactions on Power Systems,1992, (7)2:591-599
[163]Tomonobu Senjyu, Kai Shimabukuro, Katsumi Uezato, Toshihisa Funabashi. A Fast Technique for Unit Commitment Problem by Extended Priority List[J]. IEEE Transactions on Power Systems,2003, (18)2:882-888
[164]Yuan-Yih Hsu, Chung-Ching Su Chih-Chien Liang Chia-Jen Lin, Chiang-Tsung Huang. Dynamic Security Constrained Multi-Area Unit Commitment[J]. IEEEE Transactions on Power Systems,1991,18(2):1049-1055
[165]Su C C, Hsu Y Y.Fuzzy dynamic programming:an application to unit commitment[J]. IEEE Trans on Power Systems,1991,6(3):1231-1237
[166]Van den Bosh P P J, Honderd G. A solution of the unit commitment problem via decomposition and dynamic programming[J]. IEEE Trans on Power Apparatus and Systems,1985,104(7):1684-1690
[167]赵子臣,相年德,夏清,张伯明.应用启发式与逐步动态规划法进行机组最优组合[J].清华大学学报(自然科学版),1997,37(1)：57-60
[168]T. K. Siu, G. A. Nash, and Z. K. Shawwash. A practical hydro, dynamic unit commitment and loading model[J]. IEEE Trans. Power Syst.,2001,16(2):301-306
[169]F. Zhuang and F. D. Galiana. Towards a more rigorous and practical unit commitment by Lagrange relaxation[J]. IEEE Trans. Power Syst.,1988, 3(2):763-773
[170]C. Wang and S. M. Shahidehpour. Ramp-rate limits in unit commitment and economic dispatch incorporating rotor fatigue effect[J]. IEEE Trans. Power Syst., 1994,9(3):1539-1545
[171]C.Wang and S. M. Shahidehpour. Optimal generation scheduling with ramping costs[J]. IEEE Trans. Power Syst.,1995,10(1):60-67
[172]S.-Y. Lai and R. Baldick. Unit commitment with ramp multipliers[J]. IEEE Trans. Power Syst.,1999,14(1):58-64
[173]W. Ongsakul and N. Petcharaks. Unit commitment by enhanced adaptive Lagrangian relaxation[J]. IEEE Trans. Power Syst.,2004,19(1):620-628
[174]Chuan-Ping Cheng, Chih-Wen Liu, and Chun-Chang Liu. Unit Commitment by Lagrangian Relaxation and Genetic Algorithms[J]. IEEE Trans. Power Syst.,2000, 15(2):707-714
[175]Seki, T.; Yamashita, N.; Kawamoto, K. New Local Search Methods for Improving the Lagrangian-Relaxation-Based Unit Commitment Solution[J]. IEEE Trans on Power Systems,2010,25(1):272-283
[176]C. Christober Asir Rajan and M. R. Mohan. An Evolutionary Programming-Based Tabu Search Method for Solving the Unit Commitment Problem[J]. IEEE Trans on Power Systems,2004,19(1):577-584
[177]Simopoulos, D.N.; Kavatza, S.D.; Vournas, C.D. Reliability Constrained Unit Commitment Using Simulated Annealing[J]. IEEE Trans on Power Systems,2006, 21(4):1699-1706
[178]G. K. Purushothama and L. Jenkins. Simulated annealing with local search—A hybrid algorithm for unit commitment[J]. IEEE Trans. Power Syst.,2003, 18(1):273-278
[179]T. S. Dillon, K. W. Edwin, H. D. Kochs, and R. J. Tand. Integer programming approach to the problem of optimal unit commitment with probabilistic reserve determination[J]. IEEE Trans. Power App. Syst.,1978,97(6):2154-2166
[180]J. M. Arroyo and A. J. Conejo. Optimal response of a thermal unit to an electricity spot market[J]. IEEE Trans. Power Syst.,2000,15(3):1098-1104
[181]Antonio Frangioni, Claudio Gentile, and Fabrizio Lacalandra. Tighter Approximated MILP Formulations for Unit Commitment Problems[J]. IEEE Trans on Power Systems,2009,24(1):105-113
[182]徐琳.电力系统电压崩溃风险评估[D].重庆：重庆大学,2009
[183]R.E.Gomory. Outline of an Algorithm for Integer Solutions to Linear programs[J]. Bulletin of the American Mathematical Society,1958,64(5):275-278
[184]Miguel Carrion, and Jose M. Arroyo. A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem[J]. IEEE Transactions on Power Systems,2006,21(3):1371-1378
[185]Yong Fu, Mohammad Shahidehpour, Zuyi Li. AC Contingency Dispatch Based on Security-Constrained Unit Commitment[J]. IEEE Trans on Power Systems,2006, 21(2):897-908
[186]何禹清,彭建春,毛丽林,曹丽华.含多个风电机组的配电网无功优化[J].电力系统自动化,2010,34(19)：37-41
[187]王成山,孙玮,王兴刚.含大型风电场的电力系统最大输电能力计算[J].电力系统自动化,2007,31(2)：17-22
[188]李凤婷,晁勤,童菲,等.风电系统容量的优化配置探讨[J].电力自动化设备,2007,27(6)：36-38
[189]吴义纯,丁明,张立军.含风电场的电力系统潮流计算[J].中国电机工程学报,2005,25(4)：36-39
[190]叶荣,陈皓勇,王钢,等.多风电场并网时安全约束机组组合的混合整数规划解法[J].电力系统自动化,2010,34(5)：29-34
[191]邱威,张建华,刘念.含大型风电场的环境经济调度模型与解法[J].中 国电机工程学报,2011,31(19)：8-15
[192]Chen, C. L., Lee, T. Y. and Jan R. M. Optimal wind thermal coordination dispatch in isolated power systems with large integration of wind capacity[J]. Energy Conversion Management,2006,47(19):3456-3472
[193]Jabr, R. A. and Pal, B. C. Intermittent wind generation in optimal power flow dispatching[J]. IET Gener. Transm. Distrib,2009,3(1):66-74
[194]MIRANDA V., HANG P.S. Economic dispatch model with fuzzy wind constraints and attitudes of dispatchers[J]. IEEE Trans. Power Syst.,2005, 20(4):2143-2145
[195]WANG L., SINGH C. Balancing risk and cost in fuzzy economic dispatch including wind power penetration based on particle swarm optimization[J]. Electr. Power Syst. Res.,2008,78(8):1361-1368
[196]B. Venkatesh, A. Arunagiri, H.B. Gooi. Unified OPF method for maximizing voltage stability margin using successive fuzzy LP[J]. Electric Power Systems Research,2002,64(2):119-128
[197]S. Chakrabarti, B.Jeyasurya. Generation rescheduling using ANN-based computation of parameter sensitivities of the voltage stability margin[J]. Engineering Applications of Artificial Intelligence,2008,21 (8):1164-1169
[198]Xiong Pan, Guoyu Xu. Available transfer capability calculation considering voltage stability margin[J]. Engineering Applications of Artificial Intelligence, 2005,76(9):52-57
[199]Debbie Q. Zhou, U. D. Annakkage, Athula D. Rajapakse. Online Monitoring of Voltage Stability Margin Using an Artificial Neural Network[J]. IEEE Transactions on Power Systems,2010,25(3):1566-1574
[200]Carolina M. Affonso, Luiz C. P. da Silva, Flavio G. M. Lima, and Secundino Soares MW and MVar Management on Supply and Demand Side for Meeting Voltage Stability Margin Criteria[J]. IEEE Transactions on Power Systems,2004, 19(3):1538-1545
[201]Hwachang Song, Byongjun Lee, Sae-Hyuk Kwon, Venkataramana Ajjarapu. Reactive Reserve-Based Contingency Constrained Optimal Power Flow (RCCOPF) for Enhancement of Voltage Stability Margins[J]. IEEE Transactions on Power Systems,2003,18(4):1538-1546
[202]T.V. Menezes, L.C.P. da Silva, C.M. Affonso and V.F. da CostaMVAR management on the pre-dispatch problem for improving voltage stability margin[J]. IEE Proc.-Gener. Transm. Distrib.,2004,151(6):665-672
[203]B. Venkatesh, G. Sadasivam, M. Abdullah Khan. A New Optimal Reactive Power Scheduling Method for Loss Minimization and Voltage Stability Margin Maximization Using Successive Multi-Objective Fuzzy LP Technique[J]. IEEE Transactions on Power Systems,2000,15(2):844-851
[204]Luis A. L1. Zarate, Carlos A. Castro, Jose Luis Martinez Ramos, Esther Romero Ramos. Fast Computation of Voltage Stability Security Margins Using Nonlinear Programming Techniques[J]. IEEE Transactions on Power Systems, 2006,21(1):19-27
[205]H. Song, B. Lee and Y.-H. MoonReactive optimal power flow incorporating margin enhancement constraints with nonlinear interior point method[J]. IEE Proc.-Gener. Transm. Distrib.,2005,152(6):961-968
[206]Eknath Vittal, Mark O'Malley, Andrew Keane. A Steady-State Voltage Stability Analysis of Power Systems With High Penetrations of Wind[J]. IEEE Transactions on Power Systems,2010,25(1):433-442
[207]IEEE/CIGRE Joint Task Force On Stability Terms and Definitions and Classification of Power System stability[J]. IEEE Transactions on Power Systems,2004,19(3):1387-1401
[208]刘明波,谢敏,赵维兴.大电网最优潮流计算[M].北京：科学出版社,2010
[209]R. Tavakkoli-Moghaddam, M. Azarkish, A. Sadeghnejad-Barkousaraie. A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem[J]. Expert Systems with Applications,2011, 38(9):10812-10821
[210]Liu, B., Wang, L.,& Jin, Y. H. An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers[J]. Computers and Operations Research,2008,35(9):2791-2806
[211]Kao, Y.-T.,& Zahara, E. A hybrid genetic algorithm and particle swarm optimization for multimodal functions[J]. Applied Soft Computing,2007, 8(2):849-857
[212]Acharjee, P.,& Goswami, S. K. Expert algorithm based on adaptive particle swarm optimization for power flow analysis[J]. Expert Systems with Applications,2009,36(3):541-552
[213]Gao, L., Yang, L., Zhou, C.,& Hu, Y. Category forecast application of neural network algorithm trained by particle swarm optimization[J]. Computer Integrated Manufacturing Systems,2006,12(3):465-469
[214]Lin, C.-J., Wang, J.-G.,& Lee, C.-Y. Pattern recognition using neural-fuzzy networks based on improved particle swam optimization[J]. Expert Systems with Application,2009,36(3):5402-5541
[215]Alper, U. Improvement of energy demand forecasts using swarm intelligence:The case of Turkey with projections to 2025[J]. Energy Policy, 2008,36(6):1937-1944
[216]Yannis, M., Magdalene, M., Michael, D.,& Constantin, Z. Ant colony and particle swarm optimization for financial classification problems[J]. Expert Systems with Applications,2009,36(7):10604-10611
[217]N. Mo, Z.Y. Zou, K.W. Chan and T.Y.G. Pong Transient stability constrained optimal power flow using particle swarm optimisation[J]. IET Gener. Transm. Distrib.,2007, 1(3):476-483
[218]Pablo E. Onate Yumbla, Juan M. Ramirez, etc. Optimal Power Flow Subject to Security Constraints Solved With a Particle Swarm Optimizer[J]. IEEE Transactions on Power Systems,2008,23(1):33-40
[219]M. R. AlRashidi, and M. E. El-Hawary. Hybrid Particle Swarm Optimization Approach for Solving the Discrete OPF Problem Considering the Valve Loading Effects[J]. IEEE Transactions on Power Systems,2007, 22(4):2030-2038
[220]Ahmed A. A. Esmin, Germano Lambert-Torres, Antonio C. Zambroni de Souza. A Hybrid Particle Swarm Optimization Applied to Loss Power Minimization[J]. IEEE Transactions on Power Systems,2005,22(2):859-866
[221]Sudipta Dutta, S. P. Singh. Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization[J]. IEEE Transactions on Power Systems,2008,23(4):1560-1569
[222]Hirotaka Yoshida, Kenichi Kawata, Shinichi Takayama, Yosuke Nakanishi. A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment[J]. IEEE Transactions on Power Systems,2000,15(4):1232-1239
[223]T.O. Ting, K.P. Wong, C.Y. Chung. Hybrid constrained genetic algorithm/particle swarm optimisation load flow algorithm[J]. IET Gener. Transm. Distrib.,2008,2(6):800-812
[224]R.E.Brown, L. A.A.Freeman. Analyzing the reliability impact of distributed generation[C]. IEEE Power Engineering Society Summer Meeting,2001, 2:1013-1018
[225]王志群.基于微型燃气轮机的分布式发电系统的研究[D].北京：清华大学博士学位论文,2004
[226]J. O. Kim, S. K. Park, K. W. Park, and C. Singh. Dispersed generation planning using improved Hereford Ranch algorithm[J]. Elect. Power Syst. Res., 1998,47(1):47-55
[227]M. Gandomkar, M. Vakilini, and M. Ehsan. Optimal distributed generation allocation in distribution network using Hereford Ranch algorithm[C]. Int. Conf. Electrical Machines and Systems,2005
[228]T. Griffin, K. Tomsovic, D. Secrest, and A. Law. Placement of dispersed generations system for reduced losses[C].33rd Hawaii Int. Conf. System Science,2000
[229]K. Nara, Y. Hayashi, K. Ikeda, and T. Ashizawa. Application of Tabu search to optimum placement of distributed generations[C]. IEEE PES Winter Meeting, 2001
[230]J. A. Greatbanks, D. H. Popovic, M. Begovic, A. Pregelj, and T. C. Green. On optimization for security and reliability of power systems with distributed generation[C]. IEEE Bologna Power Tech Conf,2003
[231]P. N. Vovos, G. P. Harrison, A. R.Wallace, and J. W. Bialek. Optimal power flow as a tool for fault level-constrained network capacity analysis[J]. IEEE Trans. Power Syst.,2005,20(2):734-741
[232]V. H. M. Quezada, J. R. Abbad, and T. G. San Roman. Assessment of energy distribution losses for increasing penetration of distributed generation[J]. IEEE Trans. Power Syst.,2006,21(2):533-540
[233]W. E1-Khattam, K. Bhattacharya, Y. Hegazy, and M. M. A. Salama. Optimal investment planning for distributed generation in a competitive electricity market[J] IEEE Trans. Power Syst.,2004,19(3):1674-1684
[234]G. Celli, E. Ghiani, S. Mocci, and F. Pilo. A multiobjective evolutionary algorithm for the sizing and siting of distributed generation[J]. IEEE Trans. Power Syst.,2005,20(2):750-757
[235]C. Wang and M. H. Nahrir. Analytical approaches for optimal placement of distributed generation sources in power systems[J]. IEEE Trans. Power Syst., 2004,19(4):2068-2076
[236]G. Celli and F. Pilo. Optimal distributed generation allocation in MV network[C].22nd IEEE PES Int. Conf. Power Industry and Computer Applications,2001
[237]G. Celli and F. Pilo. MV network planning under uncertainty on distributed generation penetration[C]. IEEE PES Summer Meeting,2001
[238]G. Carpinelli, G. Celli, F. Pilo, and A. Russo. Distributed generation sitting and sizing under uncertainty[C]. IEEE Porto Power Tech Conf.,2001
[239]L. F. Ochoa, C. J. Dent, and G. P. Harrison. Maximisation of intermittent distributed generation in active networks[C]. CIRED Seminar 2008:SmartGrids for Distribution,2008
[240]A. Keane and M. O'Malley. Optimal distributed generation plant mix with novel loss adjustment factors[C]. IEEE PES General Meeting,2006
[241]A. Keane and M. O'Malley. Optimal utilization of distribution networks for energy harvesting[J]. IEEE Trans. Power Syst.,2007,22(1):467-475
[242]Karmarkar, N. A new polynomial-time algorithm for linear programming[J]. Combinatorica,1984,4(4):373-395
[243]Gill, P.E., Murray, W., Saunders, M.A., et.al. On the projected newton barrier methods for linear programming and an equivalence to Karmarkar's projective method[J]. Math.Programming,1986,36(2):183-209
[244]Barnes, E. R. A vacidon on Uarmarka's algorithm for solving linear programming problems[J]. Marheniaficnl Pmgromming,1986,36(1):174-182
[245]Marslen, R. E. and Snllzmsn, M. J. Implementation of a dual affine interior point algorithm for linear programming[J]. ORSA journal on computing,1989, 1(4):287-297
[246]Saigal, R. Linear Progromming:A modern integrated analysis[M]. Kluwer Academic Publishers,1995
[247]Ponnambalam, K., Quintana, V. H. and Vannellia, A. A fast algorithm for power system optimization problems using an interior point method[J]. IEEE Trans. On Power Systems,1991,7(2):892-899
[248]Vargas, L S, Quintana, V. H. and Vannellia, A. A tutorial description of an interior point method and its application to security-constrained economic dispatch[C]. IEEE/PS Summer Meeting,1992
[249]Salahi, M. Peng, J. and Terlaky, T. On mehrotra-type predictior-corrector algorithms [J]. SIAM Journal on Optimization,2007,18(4):1377-1397
[250]Torres, G. L. and Quintana, V. H. On a nonlinear multiple-centrality corrections interior-point method for optimal power flow [J]. IEEE Trans. Power Systems,2001,16(2):222-228
[251]Megiddo, N. Pathways to the optimal set in linear programming[R]. IBM Almaden Research Center, San Jose, CA, Technical Report RJ 5295,1986
[252]Kojima, M. and Tuncel, L. Monotonicity of primal-dual interior-point algorithms for semidefinite programming problems[J]. Optimization Methods and Software,1998,10(2):275-296
[253]缪楠林,刘明波,赵维兴.电力系统动态无功优化并行算法及其实现[J].电工技术学报,2009,24(2)：150-157
[254]孙艳,杭乃善,李如琦.考虑频率质量约束的最优潮流模型[J].中国电机工程学报,2010,30(22)：77-84
[255]黄镇,杨京燕,覃智君,等.采用内点法的多目标低电压风险优化[J].电力系统及其自动化学报,2011,23(2)：92-97
[256]涂福荣,王晓茹.电力系统无功优化模糊建模研究[J].电力系统保护与控制,2010,38(13)：46-49
[257]周悦,程浩忠,熊宁,等.危险负荷增长方式下考虑静态电压稳定裕度的无功优化[J].水电能源科学,2010,28(3)：152-155
[258]Wu, Y. C., Debs, A. S., Marsten, R. E. A direct nonlinear predictor-corrector primal-dual interior point algorithm for optimal power flow[J]. IEEE Trans. on Power Systems.1994,9(2):876-883
[259]程军照,李澍森,程强.一种无功优化预测校正内点算法[J].电工技术学报,2010,25(2)：152-158
[260]徐进东,丁晓群,覃振成.基于非线性预报-校正内点法的电力系统无功优化研究[J].电网技术,2005,29(9)：36-39
[261]刘雪连,段振刚,王坚,尹诗杭.考虑电压安全裕度的多目标最优潮流模糊建模[J].电工技术学报,2011,35(12)：112-116
[262]J. Nocedal, S.J. Wright, Numerical Optimization[M]. New York: Springer-Verlag,1999
[263]Cartis C. Some disadvantages of a Mehrotra-type pri-mal-dual corrector interior point algorithm for linear programming[J]. Applied Numerical Mathematics,2009, 59(5):1110-1119
[264]Z. M. Salameh, B. S. Borowy, and A. R. A. Amin. Photovoltaic module-site matching based on the capacity factors[J]. IEEE Trans. Energy Convers.,1995, 10(2):326-332
[265]G. Boyle, Renewable Energy[M]. Oxford, U.K.:Oxford Univ. Press,2004
[266]J. Hetzer, C. Yu, and K. Bhattarai. An economic dispatch model incorporating wind power[J]. IEEE Trans. Energy Convers.,2008,23(2):603-611
[267]Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, R. Seethapathy. Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization[J]. IEEE Transactions on Power Systems,2010,25(1):360-370
[268]X.P. Zhang, S.G. Petoussis and K.R. Godfrey. Nonlinear interior-point optimal power flow method based on a current mismatch formulation[J]. IEE Proc.-Gener. Transm. Distrib.,2005,152(6):795-805