智能电网条件下输电检修优化模式与实施方案研究
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摘要
目前,低碳经济发展模式已被各国广泛认同并逐步推行,以应对气候变化、实现可持续发展。我国一次能源消费中,煤炭比例长期保持在70%以上。在低碳经济发展模式下,面对高碳型的电源结构,电力行业已成为我国实现节能减排的关键。推进智能电网建设,是电力行业转变发展方式,逐步实现向低碳经济转型的必然趋势。在此过程中,电网中将引入大量先进电力电子技术、可再生能源、微网等智能化因素,以提高能源的利用效率、减少温室气体排放,这将在一定程度上给我国传统输电检修模式带来新的机遇与挑战。一方面,随着清洁能源分散接入,电网规模日趋庞大,电网结构日益复杂,电网施工安装、运行维护检修及其技术管理的工作量也呈阶梯式增长,此时,如何针对输电检修面临的新状况,采取有效的方式方法确定输电检修策略,缩小影响范围,对于确保电网的安全稳定具有重要的理论意义；另一方面,在线监测技术、智能电网状态检测技术等先进技术的引入,为电网安全风险评估、设备故障诊断和状态检修等提供了技术支持,此时,如何充分利用智能电网的技术优势,确定有效的输电检修实施方案,对于智能电网条件下的输电检修具有重要的实践意义。因此,研究智能电网条件下输电检修优化模式与实施方案具有重要的理论和实践意义。
本文针对智能电网建设对输电检修产生的影响,研究智能电网条件下输电检修的优化模式与实施方案。第一,从设备故障、故障检测及诊断、设备故障风险评估以及设备故障检修等方面,分析输电检修优化理论,为论文的深入研究奠定理论基础。第二,针对智能电网条件下输电检修信息连续性和实时性的特点,提出基于连续蚁群优化算法的输电检修优化模型。以输电检修费用最小化、可用输电容量最大化为优化目标,建立输电检修优化决策模型,提出一种利用改进高斯函数反映人工蚂蚁搜索过程中信息素浓度变化情况的连续蚁群优化算法求解模型。第三,针对智能电网引入的大量先进电子技术能够为量化分析输电系统的风险提供技术支撑这一技术优势,提出基于风险评估的输电检修优化模型。从故障后果角度评估输电系统的风险,以故障风险降低值为检修优化指标,建立基于风险的输电检修优化模型,利用拉格朗日松弛规划技术求解模型。最后,研究智能电网条件下输电检修管理的实施方案,包括智能电网技术突破研究、输电资产管理、输电检修计划管理、输电检修需求侧响应、输电检修技术保障以及输电检修组织保障等内容。
研究表明,第一,在智能电网条件下基于连续蚁群优化算法的输电检修模型研究中,发现与常规蚁群算法相比,利用连续蚁群优化算法求解输电检修优化决策问题,所产生的检修费用相对较低,获得的可用输电容量相对较大,说明连续蚁群算法由于充分考虑了信息素浓度变化的连续性,所求得的解集有效性更好,为制定输电检修策略提供了借鉴。第二,在智能电网条件下基于风险评估的输电检修模型研究中,发现以输电系统故障风险降低值最大化为目标来安排输电检修任务是合理且可行的,基于动态规划的松弛线性规划算法满足最优解性质且计算效率高,而且通过重新对资金和人员进行分配能够进一步增加风险降低值,为检修资源的优化分配提供了决策支持。最后,在智能电网条件下输电检修管理的实施方案研究中,提出了“以智能电网技术为核心,输电资产管理、计划管理、需求侧管理、技术保障和组织保障同步推进”的输电检修管理的实施方案,在介绍智能电网基础技术和状态检修关键技术的基础上,以全寿命周期管理为出发点,介绍了智能电网条件下输电检修资产管理的特点及流程；分析了输电检修的短期、中期以及长期计划；分析了智能电网条件下输电检修的需求侧管理；从技术学习、专业间的技术渗透、岗位“准入门槛”、技能培训、激励约束机制以及信息技术水平六个方面,分析了智能电网条件下输电检修的技术保障；从输电检修工作管理、输电检修工作实施以及输电检修工作评估三个方面,分析了智能电网条件下输电检修的组织保障。这些研究成果能够为我国在大力推行智能电网建设的背景下,寻求合适的输电检修优化模式提供一定的参考价值,并在一定程度上为保障电网安全经济运行和供电可靠性做出贡献。
Currently, low-carbon economic development mode has been widely adopted to address climate change and achieve sustainable development. The rate of coal in primary energy consumption remains70%in China. In the mode of low-carbon economy development, facing with high-carbon-based power structure, the power industry had become the key to achieve energy conservation in China. It is an inevitable trend to promote smart grid construction for the purpose of changing development patterns of power industry progressively into the mode of low-carbon economy. In this process, a variety of advanced technologies have been introduced to the power system to improve energy efficiency and reduce greenhouse gas emissions, which brings new challenges to our traditional transmission maintenance mode. On the one hand, along with the increasing amount of power grid assets and stepped growth of workload in power construction, installation, maintenance, operation maintenance and technical management, it is of significant importance to determine the effective transmission maintenance strategy for ensuring the stability and safety of the power grid; On the other hand, the introduction of large numbers of advanced technology has provided technical support for real-time monitoring and evaluation of device status, fault diagnosis, and disaster warning information. Therefore, it is of positive theoretical and practical significance to undertake the transmission maintenance scientifically and efficiently so as to realize the safe, reliable and cost-effective operation of power grid.
In this thesis, considering the impact of smart grid construction on the transmission maintenance, an optimization mode and embodiment of the transmission maintenance under the conditions of smart grid is studied. Firstly, considering the areas of equipment failure, fault detection and diagnosis, risk assessment of equipment failure, and equipment troubleshooting, the optimization theory of transmission maintenance is analyzed, which lays the foundation for further in-depth study. Secondly, the optimization model of transmission maintenance based on continuous ant colony optimization algorithm is studied under the conditions of the smart grid. On the purpose of minimizing transmission maintenance costs and maximizing available transmission capacity, an optimization decision-making model of transmission maintenance is established, and a solving method and process for continuous optimization is analyzed, with a numerical example given. Thirdly, the optimization model of transmission maintenance based on the risk assessment is studied under the conditions of the smart grid. The risk of the transmission system is assessed based on the failure consequences, and an optimization model of transmission maintenance based on the risk assessment is established using the overhaul optimization index of fault risk value. Besides, process optimization and solution algorithm of transmission maintenance based on the risk is proposed, and a numerical example was given. Finally, the embodiment of transmission maintenance management under the smart grid conditions is analyzed, including the contents of transmission asset management, transmission maintenance program management, transmission maintenance demand side response, transmission maintenance technical support and organization guarantee.
Study results are abundant. Firstly, in the context of smart grid, compared with the conventional ant colony algorithm, the solution to transmission maintenance optimal decision-making problems using continuous ant colony optimization algorithm is relatively cost-saving and has more available transmission capacity, indicating that continuous ant colony algorithm can get better effectiveness of the obtained solution set due to taking full account of continuity of the pheromone concentration change. Secondly, under the background of smart grid, it is reasonable and feasible to arrange transmission maintenance tasks for the goal of maximization reduction of the risk value. The relaxation linear programming algorithm based on dynamic programming meets optimal solution and has high calculation efficiency, and the risk reduction value can be further increased through the re-allocation of funds and personnel, which also provides decision-making support for optimal allocation of resources overhaul. Finally, in the program implementation of transmission maintenance management under smart grid conditions, taking a full life cycle management as the starting point, the characteristics and processes of transmission maintenance asset management under smart grid conditions is introduced; the short-term, medium-term, long-term plan and demand-side management of transmission maintenance under the smart grid conditions is proposed; technical support of transmission maintenance under the smart grid conditions is analyzed from the aspects of technical learning, professional technology penetration, job access threshold, skills training, incentive and restraint mechanisms, and IT level; group protection of transmission maintenance under the smart grid conditions is analyzed from the aspects of management, implementation and evaluation of transmission maintenance. These findings can provide certain reference for seeking suitable optimization mode of transmission maintenance under the smart grid conditions in China, and contribute to the safe and economic operation of our power grid and the reliability of power supply.
本文针对智能电网建设对输电检修产生的影响,研究智能电网条件下输电检修的优化模式与实施方案。第一,从设备故障、故障检测及诊断、设备故障风险评估以及设备故障检修等方面,分析输电检修优化理论,为论文的深入研究奠定理论基础。第二,针对智能电网条件下输电检修信息连续性和实时性的特点,提出基于连续蚁群优化算法的输电检修优化模型。以输电检修费用最小化、可用输电容量最大化为优化目标,建立输电检修优化决策模型,提出一种利用改进高斯函数反映人工蚂蚁搜索过程中信息素浓度变化情况的连续蚁群优化算法求解模型。第三,针对智能电网引入的大量先进电子技术能够为量化分析输电系统的风险提供技术支撑这一技术优势,提出基于风险评估的输电检修优化模型。从故障后果角度评估输电系统的风险,以故障风险降低值为检修优化指标,建立基于风险的输电检修优化模型,利用拉格朗日松弛规划技术求解模型。最后,研究智能电网条件下输电检修管理的实施方案,包括智能电网技术突破研究、输电资产管理、输电检修计划管理、输电检修需求侧响应、输电检修技术保障以及输电检修组织保障等内容。
研究表明,第一,在智能电网条件下基于连续蚁群优化算法的输电检修模型研究中,发现与常规蚁群算法相比,利用连续蚁群优化算法求解输电检修优化决策问题,所产生的检修费用相对较低,获得的可用输电容量相对较大,说明连续蚁群算法由于充分考虑了信息素浓度变化的连续性,所求得的解集有效性更好,为制定输电检修策略提供了借鉴。第二,在智能电网条件下基于风险评估的输电检修模型研究中,发现以输电系统故障风险降低值最大化为目标来安排输电检修任务是合理且可行的,基于动态规划的松弛线性规划算法满足最优解性质且计算效率高,而且通过重新对资金和人员进行分配能够进一步增加风险降低值,为检修资源的优化分配提供了决策支持。最后,在智能电网条件下输电检修管理的实施方案研究中,提出了“以智能电网技术为核心,输电资产管理、计划管理、需求侧管理、技术保障和组织保障同步推进”的输电检修管理的实施方案,在介绍智能电网基础技术和状态检修关键技术的基础上,以全寿命周期管理为出发点,介绍了智能电网条件下输电检修资产管理的特点及流程；分析了输电检修的短期、中期以及长期计划；分析了智能电网条件下输电检修的需求侧管理；从技术学习、专业间的技术渗透、岗位“准入门槛”、技能培训、激励约束机制以及信息技术水平六个方面,分析了智能电网条件下输电检修的技术保障；从输电检修工作管理、输电检修工作实施以及输电检修工作评估三个方面,分析了智能电网条件下输电检修的组织保障。这些研究成果能够为我国在大力推行智能电网建设的背景下,寻求合适的输电检修优化模式提供一定的参考价值,并在一定程度上为保障电网安全经济运行和供电可靠性做出贡献。
Currently, low-carbon economic development mode has been widely adopted to address climate change and achieve sustainable development. The rate of coal in primary energy consumption remains70%in China. In the mode of low-carbon economy development, facing with high-carbon-based power structure, the power industry had become the key to achieve energy conservation in China. It is an inevitable trend to promote smart grid construction for the purpose of changing development patterns of power industry progressively into the mode of low-carbon economy. In this process, a variety of advanced technologies have been introduced to the power system to improve energy efficiency and reduce greenhouse gas emissions, which brings new challenges to our traditional transmission maintenance mode. On the one hand, along with the increasing amount of power grid assets and stepped growth of workload in power construction, installation, maintenance, operation maintenance and technical management, it is of significant importance to determine the effective transmission maintenance strategy for ensuring the stability and safety of the power grid; On the other hand, the introduction of large numbers of advanced technology has provided technical support for real-time monitoring and evaluation of device status, fault diagnosis, and disaster warning information. Therefore, it is of positive theoretical and practical significance to undertake the transmission maintenance scientifically and efficiently so as to realize the safe, reliable and cost-effective operation of power grid.
In this thesis, considering the impact of smart grid construction on the transmission maintenance, an optimization mode and embodiment of the transmission maintenance under the conditions of smart grid is studied. Firstly, considering the areas of equipment failure, fault detection and diagnosis, risk assessment of equipment failure, and equipment troubleshooting, the optimization theory of transmission maintenance is analyzed, which lays the foundation for further in-depth study. Secondly, the optimization model of transmission maintenance based on continuous ant colony optimization algorithm is studied under the conditions of the smart grid. On the purpose of minimizing transmission maintenance costs and maximizing available transmission capacity, an optimization decision-making model of transmission maintenance is established, and a solving method and process for continuous optimization is analyzed, with a numerical example given. Thirdly, the optimization model of transmission maintenance based on the risk assessment is studied under the conditions of the smart grid. The risk of the transmission system is assessed based on the failure consequences, and an optimization model of transmission maintenance based on the risk assessment is established using the overhaul optimization index of fault risk value. Besides, process optimization and solution algorithm of transmission maintenance based on the risk is proposed, and a numerical example was given. Finally, the embodiment of transmission maintenance management under the smart grid conditions is analyzed, including the contents of transmission asset management, transmission maintenance program management, transmission maintenance demand side response, transmission maintenance technical support and organization guarantee.
Study results are abundant. Firstly, in the context of smart grid, compared with the conventional ant colony algorithm, the solution to transmission maintenance optimal decision-making problems using continuous ant colony optimization algorithm is relatively cost-saving and has more available transmission capacity, indicating that continuous ant colony algorithm can get better effectiveness of the obtained solution set due to taking full account of continuity of the pheromone concentration change. Secondly, under the background of smart grid, it is reasonable and feasible to arrange transmission maintenance tasks for the goal of maximization reduction of the risk value. The relaxation linear programming algorithm based on dynamic programming meets optimal solution and has high calculation efficiency, and the risk reduction value can be further increased through the re-allocation of funds and personnel, which also provides decision-making support for optimal allocation of resources overhaul. Finally, in the program implementation of transmission maintenance management under smart grid conditions, taking a full life cycle management as the starting point, the characteristics and processes of transmission maintenance asset management under smart grid conditions is introduced; the short-term, medium-term, long-term plan and demand-side management of transmission maintenance under the smart grid conditions is proposed; technical support of transmission maintenance under the smart grid conditions is analyzed from the aspects of technical learning, professional technology penetration, job access threshold, skills training, incentive and restraint mechanisms, and IT level; group protection of transmission maintenance under the smart grid conditions is analyzed from the aspects of management, implementation and evaluation of transmission maintenance. These findings can provide certain reference for seeking suitable optimization mode of transmission maintenance under the smart grid conditions in China, and contribute to the safe and economic operation of our power grid and the reliability of power supply.
引文
[1]曾鸣,吕春泉,邱柳青,等.风电并网时基于需求侧响应的输电规划模型[J].电网技术,2011,35(4)：129-134
[2]孙德栋.基于碳交易市场下的火电机组低碳电力成本效益分析[J].水电能源科学,2013,31(1)：207-210
[3]庞清乐,高厚磊,李天友.基于负荷均衡的智能配电网故障恢复[J].电网技术,2013,37(2)：342-348
[4]曹培,翁慧颖,俞斌.低碳经济下的智能需求侧管理系统[J].电网技术,2012,36(10)：11-16
[5]K. Suresh, N. Kumarappan. Hybrid improved binary particle swarm optimization approach for generation maintenance scheduling problem [J]. Swarm and Evolutionary Computation,2013,9(4):69-89
[6]M.A. Fotouhi Ghazvini, Hugo Morais, Zita Vale. Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems[J]. Applied Energy,2012,96(8):281-291
[7]Alex Albert, Matthew R. Hallowell. Safety risk management for electrical transmission and distribution line construction [J]. Safety Science,2013, 51(1):118-126
[8]李有亮,高山.风电并网后大电网充裕性评估研究现状与展望[J].华东电力,2011,39(3)：0436-0442
[9]李雅茹,徐浩铭.风险评估在电网检修中的应用探讨[J].水利与建筑工程学报,2010,1(8)：122-124,137
[10]Uduakobong E. Ekpenyong, Jiangfeng Zhang, Xiaohua Xia. An improved robust model for generator maintenance scheduling [J]. Electric Power Systems Research,2012,92(11):29-36
[11]Prasan Kumar Sahoo, Jang-Ping Sheu. Limited mobility coverage and connectivity maintenance protocols for wireless sensor networks [J]. Computer Networks,2011,55(13):2856-2872
[12]Junaid Ahmad, Aamir Saeed Malik, Likun Xia, et al. Vegetation encroachment monitoring for transmission lines right-of-ways:A survey[J]. Electric Power Systems Research,2013,95(2):339-352
[13]Gheorghe Grigoras, Cecilia Barbulescu. Human errors monitoring in electrical transmission networks based on a partitioning algorithm[J]. International Journal of Electrical Power & Energy Systems,2013,49(7):128-136
[14]Paula Renatha N. da Silva, Martin Max L.C. Negrao, Petronio Vieira Junior, et al. A new methodology of fault location for predictive maintenance of transmission lines [J]. International Journal of Electrical Power & Energy Systems,2012,42(1): 568-574
[15]T. Geetha, K. Shanti Swarup. Coordinated preventive maintenance scheduling of GENCO and TRANSCO in restructured power systems[J]. International Journal of Electrical Power & Energy Systems,2009,31(10):626-638
[16]Benoit Casoetto, Eglantine Flottes, Julien Ardeois, et al. How to commercialize reliable capacities on a complex transmission network? [J]. Journal of Natural Gas Science and Engineering,2011,3(5):657-663
[17]Nobukazu Takeda, Satoshi Kakudate, Yasuhiro Matsumoto, et al. R&D on major components of control system for ITER blanket maintenance equipment [J]. Fusion Engineering and Design,2010,85(7-9):1190-1195
[18]Cher Ming Tan, Nagarajan Raghavan. A framework to practical predictive maintenance modeling formulti-state systems[J]. Reliability Engineering and System Safety,2008,93:1138-1150
[19]M. Shahidehpour, M. Marwali. Maintenance scheduling in restructured power system[M]. Kluwer Academic Publishuers,2000
[20]Y. Yare, G.K. Venayagamoorthy. Optimal maintenance scheduling of generators using multiple swarms-MDPSO framework [J]. Engineering Applications of Artificial Intelligence,2010,23(6):895-910
[21]Ehsan Reihani, Ali Sarikhani, Moez Davodi, et al. Reliability based generator maintenance scheduling using hybrid evolutionary approach [J]. International Journal of Electrical Power & Energy Systems,2012, 42(1):434-439
[22]Abdolvahhab Fetanat, Gholamreza Shafipour. Generation maintenance scheduling in power systems using ant colony optimization for continuous domains based 0-1 integer programming[J]. Expert Systems with Applications,2011,38(8):9729-9735
[23]Jaime Campos. Development in the application of ICT in condition monitoring and maintenance [J]. Computers in Industry,2009,60(1):1-20
[24]Voumvoulakis E M, Hatziargyriou N D. Decision trees-aided self-organized maps for corrective dynamic security[J]. IEEE Trans on Power Systems,2008,23(2):622-630
[25]Y. Fu, M. Shahidehpour, Z. Li. Long-term security-constrained unit commitment: Hybrid subgradient and Danzig-Wolfe decomposition[J]. IEEE Trans. Power Syst., 2005,4(20):2094-2106
[26]Y. Fu, M. Shahidehpour, Z. Li. AC contingency dispatch based on security-constrained unit commitment[J]. IEEE Trans. Power Syst.,2007,2(21): 897-908
[27]Y. Fu, M. Shahidehpour, Z. Li. Security-constrained unit commitment with AC constraints[J]. IEEE Trans. Power Syst.,2005,3(20):1538-1550
[28]Yong Fu, Mohammad Shahidehpour, Zuyi Li. Security-Constrained Optimal Coordination of Generation and Transmission Maintenance Outage Scheduling[J]. IEEE Transactions on Power Systems,2007,3(22):1302-1313
[29]L. F. Wang, C. Singh. Adequacy assessment of power-generating systems including wind power integration based on ant colony system algorithm[A]. IEEE Proceedings of Power Tech Conference (Power Tech) [C]. Lausanne, Switzerland,2007
[30]T. Li, M. Shahidehpour. Price-based unit commitment:A case of Lagrangian relaxation versus mixed integer programming[J]. IEEE Trans. Power Syst.,2005, 4(20):2015-2025
[31]A. J. Conejo, R. Garcia-Bertrand, M. Diaz-Salazar. Generation maintenance scheduling in restructured power systems[J]. IEEE Trans. Power Syst.,2005,2(20): 984-992
[32]Grall A, Berenguer C, Dieulle L. A condition-based maintenance policy for stochastically deteriorating systems[J]. Reliab Eng System Saf,2002,76(2):167-180
[33]A. Kurzhanski, P. Varaiya. Ellipsoidal techniques for reach-ability analysis, parts Ⅰ& Ⅱ[J]. Optimization Methods and Software,2002,17:177-206,207-237
[34]L. N. de Castro, F. J. Von Zuben. Learning and optimization using the clonal selection principle[J]. IEEE Transactions on Evolutionary Computation,2002,3(6): 239-251
[35]N. Samaan, C. Singh. Adequacy Assessment of Power System Generation Using A Modified Simple Genetic Algorithm[J]. IEEE Transactions on Power Systems,2002, 4(17):974-981
[36]Y. G. Hegazy, M. M. A. Salam, A. Y. Chikhani. Adequacy assessment of distributed generation system using Monte Carlo simulation[J]. IEEE Transactions on Power Systems,2003,1(18):345-354
[37]M. Tanrioven. Reliability and cost-benefits of adding alternate power sources to an independent micro-grid community[J]. Power Sources,2005,150:136-149
[38]张粒子,黄弦超,舒隽,等.配电网检修计划优化模型设计[J].电力系统自动化,2005,29(21)：50-52
[39]黄弦超,张粒子,舒隽,等.配电网检修计划优化模型[J].电力系统自动化,2007,31(1)：33-37
[40]刘娜,朴在林,赵斌.农村配电网检修计划优化方法的研究及系统设计[J].东北电力技术.2006,2：38-40
[41]W Li, J. Korczynski. A reliability-based approach to transmission maintenance planning an its application in BC hydro system[J]. Power Delivery, IEEE Transactions on,2004,1(19):303-308
[42]Brethaue G, Gamaleja T, Handschin E. Integrated maintenance scheduling system for electrical energy systems[J]. IEEE Trans.on Power Delivery,1998,13(2): 655-660
[43]徐匡迪.应对气候变化发展低碳经济[J].泰州科技,2010,1：5-10
[44]郭基伟,柳纲,唐国庆,等.电力设备检修策略的马尔可夫决策[J].电力系统及其自动化学报,2004,(4)：6-10
[45]魏少岩,徐飞,阂勇.输电线路检修计划模型[J].电力系统自动化,2006,30(17)：41-44
[46]冯永青,吴文传,张伯明,等.基于可信性理论的输电网短期线路检修计划[J].中国电机工程学报,2007,27(4)：.65-71
[47]舒隽,张粒子,黄弦超.市场环境下中长期发输电协调检修计划优化[J].电力系统自动化,2007,31(2)：27-31
[48]纪航,刘新平,杨庆华,等.基于模糊综合评价的超高压输电线路状态评估方法思考[J].华东电力,2009,37(7)：1104-1108
[49]闵绚.输电线路状态检修智能决策系统研究[D].武汉：武汉理工大学,2010
[50]潘乐真,鲁国起,张焰.基于风险综合评判的设备状态检修决策优化[J].电力系统自动化,2010,34(11)：28-32,66
[51]葛夕武,严正,贾燕冰.计及输电线路约束的华东电网备用容量可靠性评估[J].华东电力,2008,36(3)：39-43
[52]王磊,赵书强.基于云模型的输电系统可靠性评估[J].电网与清洁能源,2010,26(11)：19-23
[53]程世娟,卢伟,何平.蚁群算法在复杂系统可靠性优化中的应用[J].工程设计学报,2009,16(3)：178-18
[54]李杰明,陈作兵,容亮,等.电力设备状态检修的探讨[J].广西水利水电,2006, 49(4)：49-52
[55]黄殿勋,张文,郭萍.发输电系统可靠性评估的蒙特卡洛改进算法[J].电力系统保护与控制,2010,38(21)：179-183
[56]高志华,任震,黄雯莹,等.发电机组竞争检修机制[J].电力系统自动化,2005,29(7)：38-42
[57]程世娟,卢伟,何平.蚁群算法在复杂系统可靠性优化中的应用[J].工程设计学报,2009,16(3)：178-181
[58]黄雅罗,黄树红.发电设备状态检修[M].北京：中国电力出版社,2000
[59]贾希胜,程中华.以可靠性为中心的维修(RCM)发展动态[J].军械工程学院,2005,24(6)：38-43
[60]喇元,王红斌,陈忠东.基于状态评价及风险评估的输变电设备状态[J].广东电力,2010,10(23)：36-40
[61]J. M. Arroyo, A. J. Conejo. Modeling of start-up and shut-down power trajectories of thermal units[J]. IEEE Trans. Power Syst,2004,3(19):1562-1568
[62]T. Li, M. Shahidehpour. Price-based unit commitment:A case of Lagrangian relaxation versus mixed integer programming[J]. IEEE Trans. Power Syst.,2005, 4(20):2015-2025
[63]丁明,冯永青.发输电设备联合检修安排模型及算法研究[J].中国电机工程学报,2004,24(5)：18-23
[64]李婷,李成武,何剑锋.国际碳交易市场发展现状及我国碳交易市场展望[J].经济纵横,2010,1(7)：76-80
[65]冯长有,王锡凡,别朝红.基于系统可靠性评估的机组检修规划模[J].西安交通大学学报,2009,43(8)：80-84
[66]李曝,韩晓萍,赵勇.基于面向对象技术的配电网状态估计的实现[J].电力学报,2004,19(3)：202-204
[67]吴为麟,侯勇,方鸽飞.基于支路电流的配电网状态估计[J].电力系统及其自动化学报,2003,13(6)：13-19
[68]黄弦超.配电网检修计划优化问题的研究[D].北京：华北电力大学,2007
[69]卢东明.关于配电网自动化系统实施的建议[J].黑龙江电力,2006,28(2)：108-111
[70]蔡奕胜.基于可靠性和经济性的配电设备检修策略研究[D].广东：华南理工大学,2006
[71]M. Shahidehpou, Y. Fu. Benders decomposition-Applying Benders decomposition to power systems[J]. IEEE Power Energy Mag.,2005,2(3):20-21
[72]Rong-Ceng Leou. A Flexible unit maintenance scheduling considering uncertainties[J]. IEEE Trans. on Power Systems,2010,16(3):552-559
[73]冯长有,王锡凡,王建学,等.市场环境下发电商的机组检修新策略[J].中国电机工程学报,2008,28(13)：106-113
[74]黄民翔.基于可靠性的供电设备检修计划优化的研究[D].浙江：浙江大学,2006
[75]陈跃芳.短期电力负荷预测方法研究与系统设计[D].浙江：浙江大学,2006
[76]贺鸿棋,周前,王丽,等.配电网检修计划制定的实用方法研究[J].试验研究,2006,34(4)：37-41
[77]关敬东.智能电网与低碳经济的认识与思考[J].供电企业管理,2010,4：79-81
[78]田廓,鄢帆,薛松,等.建设中国特色坚强智能电网技术经济关键问题框架研究[J].华东电力,2010,38(1)：0001-0005
[79]易海波,杨勇.以可靠性为基础的优化检修管理[J].华中电力,2003,16(4)：1204-1209
[80]Olga Ristic, Vladica Mijailovi. Method for determining optimal power transformers exploitation strategy[J]. Electric Power Systems Research,2012,83(1):255-261
[81]Mayank Pandey, Ming J. Zuo, Ramin Moghaddass, et al. Selective maintenance for binary systems under imperfect repair [J]. Reliability Engineering & System Safety,2013,113(5):42-51
[82]王赛一,王成山.遗传禁忌混合算法及其在电网规划中的应用[J].电力系统自动化,2004,28(20)：43-47
[83]黄弦超,舒隽,张粒子,等.免疫禁忌混合智能优化算法在配电网检修优化中的应用[J].中国电机工程学报,2004,24(11)：34-39
[84]张旭明,张焰,汪宇霆,等.采用禁忌搜索算法的多时段变压器经济运行方式优化[J].电网技术,2010,34(7)：109-113
[85]M. Y. El-Sharkh, A. A. El-Keib. Maintenance Scheduling of Generation and Transmission Systems Using Fuzzy Evolutionary Programming[J]. IEEE Transactions on Power systems,2003,2(18):862-866
[86]M. Shahidehpour, W. F. Tinney, Y. Fu. Impact of security on power systems operation[J]. Proc. IEEE,2005,11(93):2013-2025
[87]Juan L. Velasquez-Contreras, Miguel A. Sanz-Bobi, Samuel Galceran Arellano. General asset management model in the context of an electric utility. Application to power transformers [J]. Electric Power Systems Research,2011, 81(11):2015-2037
[88]M. Wang, A. J. Vandermaar, K. D. Srivastava. Review of condition assessment of power transformers in service[J]. Electrical Insulation Magazine, IEEE,2002,6(18): 12-25
[89]Amin M. Toward self-healing energy infrastructure systems[J]. IEEE Computer Applications in Power,2001,14(1):20-28
[90]王韶,周鑫.应用层次聚类法和蚁群算法的配电网无功优化[J].电网技术,2011,35(8),161-167
[91]M. Khalaquzzaman, Hyun Gook Kang, Man Cheol Kim, et al. A model for estimation of reactor spurious shutdown rate considering maintenance human errors in reactor protection system of nuclear powerplants [J]. Nuclear Engineering and Design,2010,240(10):2963-2971
[92]Kamran S. Moghaddam, John S. Usher. Preventive maintenance and replacement scheduling for repairable and maintainable systems using dynamic programming[J]. Computers & Industrial Engineering,2011,60(4):654-665
[93]Gyunyoung Heo, Jinkyun Park. A framework for evaluating the effects of maintenance-related human errors in nuclear power plants [J]. Reliability Engineering & System Safety,2010,95(7):797-805
[94]Radim Bris, Petr Byczanski. Effective computing algorithm for maintenance optimization of highly reliable systems [J]. Reliability Engineering & System Safety,2013,109(1):77-85
[95]M. Khalaquzzaman, Hyun Gook Kang, Man Cheol Kim, et al. Quantification of unavailability caused by random failures and maintenance human errors in nuclear power plants [J]. Nuclear Engineering and Design,2010,240(6):1606-1613
[96]J.Lee, M. Ghaffari, S. Elmeligy. Self-maintenance and engineering immune systems: Towards smarter machines and manufacturing systems [J]. Annual Reviews in Control,2011,35(1):111-122
[97]W.R.Blischke, D.N.Prabhakar Murthy. Reliability, modeling, prediction and optimization[J]. John Wiley & Sons,2000,13(3):34-40
[98]Billinton R, Tang X. Selected considerations in utilizing Monte Carlo simulation in quantitative reliability evaluation of composite power systems[J]. Electric Power Systems Research,2004,69(20):205-211
[99]Voumvoulakis E M, Hatziargyriou N D. Decision trees-aided self-organized maps for corrective dynamic security[J]. IEEE Trans on Power Systems,2008,23(2):622-630
[100]M.Y. El-Sharkh, A.A. El-Keib. An evolutionary programming-based solution methodology for power generation and transmission maintenance scheduling[J]. Electric Power Systems Research,2003,65:35-40
[101]Socha K, Dorigo M. Ant colony optimization for continuous domains[J]. European Journal of Operational Research,2008,185:1155-1173
[102]赵文彬,李慧星,费正明,等.基于智能电网需求的输电线路状态监测系统建设[J].华东电力,2010,38(8)：1212-1216
[103]S. Safari, M.M. Ardehali, M.J. Sirizi. Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage[J]. Energy Conversion and Management,2013,65(1):41-49
[104]Anthony U.Adoghe, Claudius Ojo A.Awosope, Joseph C. Ekeh. Asset maintenance planning in electric power distribution network using statistical analysis of outage data [J]. International Journal of Electrical Power & Energy Systems,2013,47(5):424-435
[105]Curtis L. Tomasevicz, Sohrab Asgarpoor. Optimum maintenance policy using semi-Markov decision processes [J]. Electric Power Systems Research,2009, 79(9):1286-1291
[106]Samir Benbelkacem, Mahmoud Belhocine, Abdelkader Bellarbi, et al. Augmented reality for photovoltaic pumping systems maintenance tasks [J]. Renewable Energy,2013,55(7):428-437
[107]Marcos Paulo Alves de Sousa, Manoel Ribeiro Filho, Marcus Vinicius Alves Nunes, et al. Maintenance and operation of a hydroelectric unit of energy in a power system using virtual reality [J]. International Journal of Electrical Power & Energy Systems,2010,32(6):599-606
[108]M.A. Fotouhi Ghazvini, Hugo Morais, Zita Vale. Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems[J]. Applied Energy,2012,96(8):281-291
[109]Joel Igba, Kazem Alemzadeh, Ike Anyanwu-Ebo, et al. A Systems Approach Towards Reliability-Centred Maintenance (RCM) of Wind Turbines [J]. Procedia Computer Science,2013,16(3):814-823
[110]M. Wang, A. J. Vandermaar, K. D.. Srivastava Review of condition assessment of power transformers in service[J]. Electrical Insulation Magazine IEEE,2002,18(6): 12-25
[111]Amalia Sergaki, Kostas Kalaitzakis. A fuzzy knowledge based method for maintenance planning in a power system [J]. Reliability Engineering & System Safety,2002,77(1):19-30
[112]S. Carlos, A.Sanchez, S. Martorell, et al. Particle Swarm Optimization of safety components and systems of nuclear power plants under uncertain maintenance planning[J]. Advances in Engineering Software,2012,50(8):12-18
[113]赵珊珊,张东霞,印永华.智能电网的风险评估[J].电网技术,2009,33(19)：7-10
[114]郇嘉嘉.电网设备状态检修策略研究基[D].广东：华南理工大学,2012
[115]郭云鹏,黄民翔,许旭锋.输变电设备的检修策略[J].华东电力,2006,34(12)：1118-1122
[116]张怀宇,朱松林,张扬,等.输变电设备状态检修技术体系研究与实施[J].电网技术,2009,33(13)：70-73
[117]纪航,刘新平,杨庆华,等.基于模糊综合评价的超高压输电线路状态评估方法思考[J].华东电力,2009,37(7)：1122-1126
[118]Mehmet Tu" may, A.M.Vural, K.L.Lo. The effect of unified power flow controller location in power systems[J]. Electrical Power and Energy Systems,2004,26: 561-569
[119]于宏涛,高立群,李丽霞.基于蚁群算法输电线路检修计划的制定[J].计算机应用研究,2011,28(9)：3256-3259,3263
[120]B. Chebel-Morello, K. Medjaher, A.H. Arab, et al. E-maintenance for photovoltaic power generation system [J]. Energy Procedia,2012,18:640-643
[121]Mohammad Amin Latify, Hossein Seifi, Habib Rajabi Mashhadi. An integrated model for generation maintenance coordination in a restructured power system involving gas network constraints and uncertainties [J]. International Journal of Electrical Power & Energy Systems,2013,46(3):425-440
[122]曾鸣,邱柳青.基于改进二元蚁群算法的发输电系统充裕度评估[J].华东电力,2011,39(10)：1574-1578
[123]Abdolvahhab Fetanat, Gholamreza Shafipour. Generation maintenance scheduling in power systems using ant colony optimization for continuous domains based 0-1 integer programming[J]. Expert Systems with Applications,2011,38(8):9729-9735
[124]杨廷方,周力行,李景禄,等.基于最优权值的组合模型诊断变压器故障[J].电网技术,2013,37(1)：190-194
[2]孙德栋.基于碳交易市场下的火电机组低碳电力成本效益分析[J].水电能源科学,2013,31(1)：207-210
[3]庞清乐,高厚磊,李天友.基于负荷均衡的智能配电网故障恢复[J].电网技术,2013,37(2)：342-348
[4]曹培,翁慧颖,俞斌.低碳经济下的智能需求侧管理系统[J].电网技术,2012,36(10)：11-16
[5]K. Suresh, N. Kumarappan. Hybrid improved binary particle swarm optimization approach for generation maintenance scheduling problem [J]. Swarm and Evolutionary Computation,2013,9(4):69-89
[6]M.A. Fotouhi Ghazvini, Hugo Morais, Zita Vale. Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems[J]. Applied Energy,2012,96(8):281-291
[7]Alex Albert, Matthew R. Hallowell. Safety risk management for electrical transmission and distribution line construction [J]. Safety Science,2013, 51(1):118-126
[8]李有亮,高山.风电并网后大电网充裕性评估研究现状与展望[J].华东电力,2011,39(3)：0436-0442
[9]李雅茹,徐浩铭.风险评估在电网检修中的应用探讨[J].水利与建筑工程学报,2010,1(8)：122-124,137
[10]Uduakobong E. Ekpenyong, Jiangfeng Zhang, Xiaohua Xia. An improved robust model for generator maintenance scheduling [J]. Electric Power Systems Research,2012,92(11):29-36
[11]Prasan Kumar Sahoo, Jang-Ping Sheu. Limited mobility coverage and connectivity maintenance protocols for wireless sensor networks [J]. Computer Networks,2011,55(13):2856-2872
[12]Junaid Ahmad, Aamir Saeed Malik, Likun Xia, et al. Vegetation encroachment monitoring for transmission lines right-of-ways:A survey[J]. Electric Power Systems Research,2013,95(2):339-352
[13]Gheorghe Grigoras, Cecilia Barbulescu. Human errors monitoring in electrical transmission networks based on a partitioning algorithm[J]. International Journal of Electrical Power & Energy Systems,2013,49(7):128-136
[14]Paula Renatha N. da Silva, Martin Max L.C. Negrao, Petronio Vieira Junior, et al. A new methodology of fault location for predictive maintenance of transmission lines [J]. International Journal of Electrical Power & Energy Systems,2012,42(1): 568-574
[15]T. Geetha, K. Shanti Swarup. Coordinated preventive maintenance scheduling of GENCO and TRANSCO in restructured power systems[J]. International Journal of Electrical Power & Energy Systems,2009,31(10):626-638
[16]Benoit Casoetto, Eglantine Flottes, Julien Ardeois, et al. How to commercialize reliable capacities on a complex transmission network? [J]. Journal of Natural Gas Science and Engineering,2011,3(5):657-663
[17]Nobukazu Takeda, Satoshi Kakudate, Yasuhiro Matsumoto, et al. R&D on major components of control system for ITER blanket maintenance equipment [J]. Fusion Engineering and Design,2010,85(7-9):1190-1195
[18]Cher Ming Tan, Nagarajan Raghavan. A framework to practical predictive maintenance modeling formulti-state systems[J]. Reliability Engineering and System Safety,2008,93:1138-1150
[19]M. Shahidehpour, M. Marwali. Maintenance scheduling in restructured power system[M]. Kluwer Academic Publishuers,2000
[20]Y. Yare, G.K. Venayagamoorthy. Optimal maintenance scheduling of generators using multiple swarms-MDPSO framework [J]. Engineering Applications of Artificial Intelligence,2010,23(6):895-910
[21]Ehsan Reihani, Ali Sarikhani, Moez Davodi, et al. Reliability based generator maintenance scheduling using hybrid evolutionary approach [J]. International Journal of Electrical Power & Energy Systems,2012, 42(1):434-439
[22]Abdolvahhab Fetanat, Gholamreza Shafipour. Generation maintenance scheduling in power systems using ant colony optimization for continuous domains based 0-1 integer programming[J]. Expert Systems with Applications,2011,38(8):9729-9735
[23]Jaime Campos. Development in the application of ICT in condition monitoring and maintenance [J]. Computers in Industry,2009,60(1):1-20
[24]Voumvoulakis E M, Hatziargyriou N D. Decision trees-aided self-organized maps for corrective dynamic security[J]. IEEE Trans on Power Systems,2008,23(2):622-630
[25]Y. Fu, M. Shahidehpour, Z. Li. Long-term security-constrained unit commitment: Hybrid subgradient and Danzig-Wolfe decomposition[J]. IEEE Trans. Power Syst., 2005,4(20):2094-2106
[26]Y. Fu, M. Shahidehpour, Z. Li. AC contingency dispatch based on security-constrained unit commitment[J]. IEEE Trans. Power Syst.,2007,2(21): 897-908
[27]Y. Fu, M. Shahidehpour, Z. Li. Security-constrained unit commitment with AC constraints[J]. IEEE Trans. Power Syst.,2005,3(20):1538-1550
[28]Yong Fu, Mohammad Shahidehpour, Zuyi Li. Security-Constrained Optimal Coordination of Generation and Transmission Maintenance Outage Scheduling[J]. IEEE Transactions on Power Systems,2007,3(22):1302-1313
[29]L. F. Wang, C. Singh. Adequacy assessment of power-generating systems including wind power integration based on ant colony system algorithm[A]. IEEE Proceedings of Power Tech Conference (Power Tech) [C]. Lausanne, Switzerland,2007
[30]T. Li, M. Shahidehpour. Price-based unit commitment:A case of Lagrangian relaxation versus mixed integer programming[J]. IEEE Trans. Power Syst.,2005, 4(20):2015-2025
[31]A. J. Conejo, R. Garcia-Bertrand, M. Diaz-Salazar. Generation maintenance scheduling in restructured power systems[J]. IEEE Trans. Power Syst.,2005,2(20): 984-992
[32]Grall A, Berenguer C, Dieulle L. A condition-based maintenance policy for stochastically deteriorating systems[J]. Reliab Eng System Saf,2002,76(2):167-180
[33]A. Kurzhanski, P. Varaiya. Ellipsoidal techniques for reach-ability analysis, parts Ⅰ& Ⅱ[J]. Optimization Methods and Software,2002,17:177-206,207-237
[34]L. N. de Castro, F. J. Von Zuben. Learning and optimization using the clonal selection principle[J]. IEEE Transactions on Evolutionary Computation,2002,3(6): 239-251
[35]N. Samaan, C. Singh. Adequacy Assessment of Power System Generation Using A Modified Simple Genetic Algorithm[J]. IEEE Transactions on Power Systems,2002, 4(17):974-981
[36]Y. G. Hegazy, M. M. A. Salam, A. Y. Chikhani. Adequacy assessment of distributed generation system using Monte Carlo simulation[J]. IEEE Transactions on Power Systems,2003,1(18):345-354
[37]M. Tanrioven. Reliability and cost-benefits of adding alternate power sources to an independent micro-grid community[J]. Power Sources,2005,150:136-149
[38]张粒子,黄弦超,舒隽,等.配电网检修计划优化模型设计[J].电力系统自动化,2005,29(21)：50-52
[39]黄弦超,张粒子,舒隽,等.配电网检修计划优化模型[J].电力系统自动化,2007,31(1)：33-37
[40]刘娜,朴在林,赵斌.农村配电网检修计划优化方法的研究及系统设计[J].东北电力技术.2006,2：38-40
[41]W Li, J. Korczynski. A reliability-based approach to transmission maintenance planning an its application in BC hydro system[J]. Power Delivery, IEEE Transactions on,2004,1(19):303-308
[42]Brethaue G, Gamaleja T, Handschin E. Integrated maintenance scheduling system for electrical energy systems[J]. IEEE Trans.on Power Delivery,1998,13(2): 655-660
[43]徐匡迪.应对气候变化发展低碳经济[J].泰州科技,2010,1：5-10
[44]郭基伟,柳纲,唐国庆,等.电力设备检修策略的马尔可夫决策[J].电力系统及其自动化学报,2004,(4)：6-10
[45]魏少岩,徐飞,阂勇.输电线路检修计划模型[J].电力系统自动化,2006,30(17)：41-44
[46]冯永青,吴文传,张伯明,等.基于可信性理论的输电网短期线路检修计划[J].中国电机工程学报,2007,27(4)：.65-71
[47]舒隽,张粒子,黄弦超.市场环境下中长期发输电协调检修计划优化[J].电力系统自动化,2007,31(2)：27-31
[48]纪航,刘新平,杨庆华,等.基于模糊综合评价的超高压输电线路状态评估方法思考[J].华东电力,2009,37(7)：1104-1108
[49]闵绚.输电线路状态检修智能决策系统研究[D].武汉：武汉理工大学,2010
[50]潘乐真,鲁国起,张焰.基于风险综合评判的设备状态检修决策优化[J].电力系统自动化,2010,34(11)：28-32,66
[51]葛夕武,严正,贾燕冰.计及输电线路约束的华东电网备用容量可靠性评估[J].华东电力,2008,36(3)：39-43
[52]王磊,赵书强.基于云模型的输电系统可靠性评估[J].电网与清洁能源,2010,26(11)：19-23
[53]程世娟,卢伟,何平.蚁群算法在复杂系统可靠性优化中的应用[J].工程设计学报,2009,16(3)：178-18
[54]李杰明,陈作兵,容亮,等.电力设备状态检修的探讨[J].广西水利水电,2006, 49(4)：49-52
[55]黄殿勋,张文,郭萍.发输电系统可靠性评估的蒙特卡洛改进算法[J].电力系统保护与控制,2010,38(21)：179-183
[56]高志华,任震,黄雯莹,等.发电机组竞争检修机制[J].电力系统自动化,2005,29(7)：38-42
[57]程世娟,卢伟,何平.蚁群算法在复杂系统可靠性优化中的应用[J].工程设计学报,2009,16(3)：178-181
[58]黄雅罗,黄树红.发电设备状态检修[M].北京：中国电力出版社,2000
[59]贾希胜,程中华.以可靠性为中心的维修(RCM)发展动态[J].军械工程学院,2005,24(6)：38-43
[60]喇元,王红斌,陈忠东.基于状态评价及风险评估的输变电设备状态[J].广东电力,2010,10(23)：36-40
[61]J. M. Arroyo, A. J. Conejo. Modeling of start-up and shut-down power trajectories of thermal units[J]. IEEE Trans. Power Syst,2004,3(19):1562-1568
[62]T. Li, M. Shahidehpour. Price-based unit commitment:A case of Lagrangian relaxation versus mixed integer programming[J]. IEEE Trans. Power Syst.,2005, 4(20):2015-2025
[63]丁明,冯永青.发输电设备联合检修安排模型及算法研究[J].中国电机工程学报,2004,24(5)：18-23
[64]李婷,李成武,何剑锋.国际碳交易市场发展现状及我国碳交易市场展望[J].经济纵横,2010,1(7)：76-80
[65]冯长有,王锡凡,别朝红.基于系统可靠性评估的机组检修规划模[J].西安交通大学学报,2009,43(8)：80-84
[66]李曝,韩晓萍,赵勇.基于面向对象技术的配电网状态估计的实现[J].电力学报,2004,19(3)：202-204
[67]吴为麟,侯勇,方鸽飞.基于支路电流的配电网状态估计[J].电力系统及其自动化学报,2003,13(6)：13-19
[68]黄弦超.配电网检修计划优化问题的研究[D].北京：华北电力大学,2007
[69]卢东明.关于配电网自动化系统实施的建议[J].黑龙江电力,2006,28(2)：108-111
[70]蔡奕胜.基于可靠性和经济性的配电设备检修策略研究[D].广东：华南理工大学,2006
[71]M. Shahidehpou, Y. Fu. Benders decomposition-Applying Benders decomposition to power systems[J]. IEEE Power Energy Mag.,2005,2(3):20-21
[72]Rong-Ceng Leou. A Flexible unit maintenance scheduling considering uncertainties[J]. IEEE Trans. on Power Systems,2010,16(3):552-559
[73]冯长有,王锡凡,王建学,等.市场环境下发电商的机组检修新策略[J].中国电机工程学报,2008,28(13)：106-113
[74]黄民翔.基于可靠性的供电设备检修计划优化的研究[D].浙江：浙江大学,2006
[75]陈跃芳.短期电力负荷预测方法研究与系统设计[D].浙江：浙江大学,2006
[76]贺鸿棋,周前,王丽,等.配电网检修计划制定的实用方法研究[J].试验研究,2006,34(4)：37-41
[77]关敬东.智能电网与低碳经济的认识与思考[J].供电企业管理,2010,4：79-81
[78]田廓,鄢帆,薛松,等.建设中国特色坚强智能电网技术经济关键问题框架研究[J].华东电力,2010,38(1)：0001-0005
[79]易海波,杨勇.以可靠性为基础的优化检修管理[J].华中电力,2003,16(4)：1204-1209
[80]Olga Ristic, Vladica Mijailovi. Method for determining optimal power transformers exploitation strategy[J]. Electric Power Systems Research,2012,83(1):255-261
[81]Mayank Pandey, Ming J. Zuo, Ramin Moghaddass, et al. Selective maintenance for binary systems under imperfect repair [J]. Reliability Engineering & System Safety,2013,113(5):42-51
[82]王赛一,王成山.遗传禁忌混合算法及其在电网规划中的应用[J].电力系统自动化,2004,28(20)：43-47
[83]黄弦超,舒隽,张粒子,等.免疫禁忌混合智能优化算法在配电网检修优化中的应用[J].中国电机工程学报,2004,24(11)：34-39
[84]张旭明,张焰,汪宇霆,等.采用禁忌搜索算法的多时段变压器经济运行方式优化[J].电网技术,2010,34(7)：109-113
[85]M. Y. El-Sharkh, A. A. El-Keib. Maintenance Scheduling of Generation and Transmission Systems Using Fuzzy Evolutionary Programming[J]. IEEE Transactions on Power systems,2003,2(18):862-866
[86]M. Shahidehpour, W. F. Tinney, Y. Fu. Impact of security on power systems operation[J]. Proc. IEEE,2005,11(93):2013-2025
[87]Juan L. Velasquez-Contreras, Miguel A. Sanz-Bobi, Samuel Galceran Arellano. General asset management model in the context of an electric utility. Application to power transformers [J]. Electric Power Systems Research,2011, 81(11):2015-2037
[88]M. Wang, A. J. Vandermaar, K. D. Srivastava. Review of condition assessment of power transformers in service[J]. Electrical Insulation Magazine, IEEE,2002,6(18): 12-25
[89]Amin M. Toward self-healing energy infrastructure systems[J]. IEEE Computer Applications in Power,2001,14(1):20-28
[90]王韶,周鑫.应用层次聚类法和蚁群算法的配电网无功优化[J].电网技术,2011,35(8),161-167
[91]M. Khalaquzzaman, Hyun Gook Kang, Man Cheol Kim, et al. A model for estimation of reactor spurious shutdown rate considering maintenance human errors in reactor protection system of nuclear powerplants [J]. Nuclear Engineering and Design,2010,240(10):2963-2971
[92]Kamran S. Moghaddam, John S. Usher. Preventive maintenance and replacement scheduling for repairable and maintainable systems using dynamic programming[J]. Computers & Industrial Engineering,2011,60(4):654-665
[93]Gyunyoung Heo, Jinkyun Park. A framework for evaluating the effects of maintenance-related human errors in nuclear power plants [J]. Reliability Engineering & System Safety,2010,95(7):797-805
[94]Radim Bris, Petr Byczanski. Effective computing algorithm for maintenance optimization of highly reliable systems [J]. Reliability Engineering & System Safety,2013,109(1):77-85
[95]M. Khalaquzzaman, Hyun Gook Kang, Man Cheol Kim, et al. Quantification of unavailability caused by random failures and maintenance human errors in nuclear power plants [J]. Nuclear Engineering and Design,2010,240(6):1606-1613
[96]J.Lee, M. Ghaffari, S. Elmeligy. Self-maintenance and engineering immune systems: Towards smarter machines and manufacturing systems [J]. Annual Reviews in Control,2011,35(1):111-122
[97]W.R.Blischke, D.N.Prabhakar Murthy. Reliability, modeling, prediction and optimization[J]. John Wiley & Sons,2000,13(3):34-40
[98]Billinton R, Tang X. Selected considerations in utilizing Monte Carlo simulation in quantitative reliability evaluation of composite power systems[J]. Electric Power Systems Research,2004,69(20):205-211
[99]Voumvoulakis E M, Hatziargyriou N D. Decision trees-aided self-organized maps for corrective dynamic security[J]. IEEE Trans on Power Systems,2008,23(2):622-630
[100]M.Y. El-Sharkh, A.A. El-Keib. An evolutionary programming-based solution methodology for power generation and transmission maintenance scheduling[J]. Electric Power Systems Research,2003,65:35-40
[101]Socha K, Dorigo M. Ant colony optimization for continuous domains[J]. European Journal of Operational Research,2008,185:1155-1173
[102]赵文彬,李慧星,费正明,等.基于智能电网需求的输电线路状态监测系统建设[J].华东电力,2010,38(8)：1212-1216
[103]S. Safari, M.M. Ardehali, M.J. Sirizi. Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage[J]. Energy Conversion and Management,2013,65(1):41-49
[104]Anthony U.Adoghe, Claudius Ojo A.Awosope, Joseph C. Ekeh. Asset maintenance planning in electric power distribution network using statistical analysis of outage data [J]. International Journal of Electrical Power & Energy Systems,2013,47(5):424-435
[105]Curtis L. Tomasevicz, Sohrab Asgarpoor. Optimum maintenance policy using semi-Markov decision processes [J]. Electric Power Systems Research,2009, 79(9):1286-1291
[106]Samir Benbelkacem, Mahmoud Belhocine, Abdelkader Bellarbi, et al. Augmented reality for photovoltaic pumping systems maintenance tasks [J]. Renewable Energy,2013,55(7):428-437
[107]Marcos Paulo Alves de Sousa, Manoel Ribeiro Filho, Marcus Vinicius Alves Nunes, et al. Maintenance and operation of a hydroelectric unit of energy in a power system using virtual reality [J]. International Journal of Electrical Power & Energy Systems,2010,32(6):599-606
[108]M.A. Fotouhi Ghazvini, Hugo Morais, Zita Vale. Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems[J]. Applied Energy,2012,96(8):281-291
[109]Joel Igba, Kazem Alemzadeh, Ike Anyanwu-Ebo, et al. A Systems Approach Towards Reliability-Centred Maintenance (RCM) of Wind Turbines [J]. Procedia Computer Science,2013,16(3):814-823
[110]M. Wang, A. J. Vandermaar, K. D.. Srivastava Review of condition assessment of power transformers in service[J]. Electrical Insulation Magazine IEEE,2002,18(6): 12-25
[111]Amalia Sergaki, Kostas Kalaitzakis. A fuzzy knowledge based method for maintenance planning in a power system [J]. Reliability Engineering & System Safety,2002,77(1):19-30
[112]S. Carlos, A.Sanchez, S. Martorell, et al. Particle Swarm Optimization of safety components and systems of nuclear power plants under uncertain maintenance planning[J]. Advances in Engineering Software,2012,50(8):12-18
[113]赵珊珊,张东霞,印永华.智能电网的风险评估[J].电网技术,2009,33(19)：7-10
[114]郇嘉嘉.电网设备状态检修策略研究基[D].广东：华南理工大学,2012
[115]郭云鹏,黄民翔,许旭锋.输变电设备的检修策略[J].华东电力,2006,34(12)：1118-1122
[116]张怀宇,朱松林,张扬,等.输变电设备状态检修技术体系研究与实施[J].电网技术,2009,33(13)：70-73
[117]纪航,刘新平,杨庆华,等.基于模糊综合评价的超高压输电线路状态评估方法思考[J].华东电力,2009,37(7)：1122-1126
[118]Mehmet Tu" may, A.M.Vural, K.L.Lo. The effect of unified power flow controller location in power systems[J]. Electrical Power and Energy Systems,2004,26: 561-569
[119]于宏涛,高立群,李丽霞.基于蚁群算法输电线路检修计划的制定[J].计算机应用研究,2011,28(9)：3256-3259,3263
[120]B. Chebel-Morello, K. Medjaher, A.H. Arab, et al. E-maintenance for photovoltaic power generation system [J]. Energy Procedia,2012,18:640-643
[121]Mohammad Amin Latify, Hossein Seifi, Habib Rajabi Mashhadi. An integrated model for generation maintenance coordination in a restructured power system involving gas network constraints and uncertainties [J]. International Journal of Electrical Power & Energy Systems,2013,46(3):425-440
[122]曾鸣,邱柳青.基于改进二元蚁群算法的发输电系统充裕度评估[J].华东电力,2011,39(10)：1574-1578
[123]Abdolvahhab Fetanat, Gholamreza Shafipour. Generation maintenance scheduling in power systems using ant colony optimization for continuous domains based 0-1 integer programming[J]. Expert Systems with Applications,2011,38(8):9729-9735
[124]杨廷方,周力行,李景禄,等.基于最优权值的组合模型诊断变压器故障[J].电网技术,2013,37(1)：190-194