基于贝叶斯网络与蚁群算法的输电线路巡检计划制定与路径规划研究
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摘要
输电线路网承载着我们国家当前的支柱能源,其能否安全稳定地运行不仅仅关系到国家的经济发展,而且与国家安全息息相关。但是由于输电线路网本身常年累月暴露于野外,很容易出现故障,所以电力公司普遍采用输电线路巡检作为保证电力系统安全的一项基础工作。现有的一些输电线路巡检方法由于管理上和技术上的缺陷而不能够及时准确地反映输电线路设备的运行状况,这对保证电力系统的稳定运行非常不利。所以研究和开发先进的智能巡检管理系统,及时发现问题,这将有利于提高电力系统运行的安全可靠性,减轻输电线路巡检工作人员的工作强度,提高巡检工作的效率,而且可以提高输电线路巡检的决策科学水平,对输电网络的发展具有重要的学术和现实意义。
本文以输电线路巡检现状为研究背景,研究基于贝叶斯网络与蚁群算法的输电线路巡检计划制定与路径规划。具体来说,主要完成了以下研究工作:
首先,总体介绍了输电线路巡检的现状,其中重点分析了输电线路故障的影响因素以及巡检机制的不足之处,为论文的研究工作奠定了重要的基础。
其次,针对当前输电线路巡检机制的不足之处,确定了输电线路巡检系统的总体架构,制定了输电线路巡检计划制定与路径规划的方案。
然后,研究了以贝叶斯网络及其推理机制为基础的输电线路杆塔运行风险分类算法,建立基于该算法的运行风险分类模型,并在matlab下进行了建模分析和评估。
最后,采用自适应蚁群算法解决输电线路巡检路径规划,同时把贝叶斯网络推理结果即输电线路杆塔运行风险的概率应用到路径规划算法中。仿真结果证明该巡检路径规划算法能够得到满足要求的路径。本文所研究的系统,采用了较为先进的规划理论和规划方法,可以与电力公司当前所使用的相关信息管理系统相结合,对于实现电力信息化,提高电力部门的生产效率和管理水平有一定的贡献。
The key energy of current nation was loaded on the power transmission lines network which is not only relate to the country’s economic development, but also vitally related with national security.?But the power transmission lines are exposed to the wild perennially, so it is easy to have failures. Electric power transmission lines patrol inspection is a basic work which effectively guaranteeing the safety of? the electric power system. The original power transmission lines patrol inspection can not accurately reflect the state of the electrical transmission line’running state duly and accurately, because of the limitation in current management and technically, it is very disadvantage for guaranteeing the power transmission lines system running steadily.?Therefore, to research and development of advanced intelligent patrol inspection management methods, promptly identify problems, which will help improve the power transmission lines operating in security and reliability, and it could reduce the intensity of planning the work of patrol inspection managers , but also improves the level of scientific decision-making. These are important value and practical significance for the development of transmission lines patrol inspection system.
This thesis is based on power transmission lines patrol inspection system, and the paper mainly researches on path-planning based on Bayesian inference and Self-adapted Ant Colony algorithm for simulated inspector’s path-planning, the major contents of the research presented in this thesis are as follows:
Firstly, this paper totally introduces the present condition of power transmission lines patrol inspection mechanism, and then particularly analyzes the impact factor of fault in power line, and the shortage of patrol inspection mechanism. These works made an important basis for the research on path-planning in the thesis.
Secondly, for the shortage of existing situation on power transmission lines patrol inspection, this thesis make an Feasibility Analysis about the usage of data mining in this system, and design a new framework about this system.
Then, algorithm of the power transmission line running state assessment based on Bayesian Network is discussed and its model is established. The result is analyzed by Matlab 6.5. Finally,?on the basis of global path-planning, this thesis adopting Self-adapted Ant Colony Algorithm to solve the local path-planning in order to take account of the power transmission line’s running state. And the simulation result shows that the algorithm is effective.
This system designed in this thesis, using advanced planning algorithm as a guide, combining with present information management systems of electric company, makes some contribution to the patrol inspection and the improvement of the electric management level.
本文以输电线路巡检现状为研究背景,研究基于贝叶斯网络与蚁群算法的输电线路巡检计划制定与路径规划。具体来说,主要完成了以下研究工作:
首先,总体介绍了输电线路巡检的现状,其中重点分析了输电线路故障的影响因素以及巡检机制的不足之处,为论文的研究工作奠定了重要的基础。
其次,针对当前输电线路巡检机制的不足之处,确定了输电线路巡检系统的总体架构,制定了输电线路巡检计划制定与路径规划的方案。
然后,研究了以贝叶斯网络及其推理机制为基础的输电线路杆塔运行风险分类算法,建立基于该算法的运行风险分类模型,并在matlab下进行了建模分析和评估。
最后,采用自适应蚁群算法解决输电线路巡检路径规划,同时把贝叶斯网络推理结果即输电线路杆塔运行风险的概率应用到路径规划算法中。仿真结果证明该巡检路径规划算法能够得到满足要求的路径。本文所研究的系统,采用了较为先进的规划理论和规划方法,可以与电力公司当前所使用的相关信息管理系统相结合,对于实现电力信息化,提高电力部门的生产效率和管理水平有一定的贡献。
The key energy of current nation was loaded on the power transmission lines network which is not only relate to the country’s economic development, but also vitally related with national security.?But the power transmission lines are exposed to the wild perennially, so it is easy to have failures. Electric power transmission lines patrol inspection is a basic work which effectively guaranteeing the safety of? the electric power system. The original power transmission lines patrol inspection can not accurately reflect the state of the electrical transmission line’running state duly and accurately, because of the limitation in current management and technically, it is very disadvantage for guaranteeing the power transmission lines system running steadily.?Therefore, to research and development of advanced intelligent patrol inspection management methods, promptly identify problems, which will help improve the power transmission lines operating in security and reliability, and it could reduce the intensity of planning the work of patrol inspection managers , but also improves the level of scientific decision-making. These are important value and practical significance for the development of transmission lines patrol inspection system.
This thesis is based on power transmission lines patrol inspection system, and the paper mainly researches on path-planning based on Bayesian inference and Self-adapted Ant Colony algorithm for simulated inspector’s path-planning, the major contents of the research presented in this thesis are as follows:
Firstly, this paper totally introduces the present condition of power transmission lines patrol inspection mechanism, and then particularly analyzes the impact factor of fault in power line, and the shortage of patrol inspection mechanism. These works made an important basis for the research on path-planning in the thesis.
Secondly, for the shortage of existing situation on power transmission lines patrol inspection, this thesis make an Feasibility Analysis about the usage of data mining in this system, and design a new framework about this system.
Then, algorithm of the power transmission line running state assessment based on Bayesian Network is discussed and its model is established. The result is analyzed by Matlab 6.5. Finally,?on the basis of global path-planning, this thesis adopting Self-adapted Ant Colony Algorithm to solve the local path-planning in order to take account of the power transmission line’s running state. And the simulation result shows that the algorithm is effective.
This system designed in this thesis, using advanced planning algorithm as a guide, combining with present information management systems of electric company, makes some contribution to the patrol inspection and the improvement of the electric management level.
引文
[1]纪建伟.电力系统分析[M].北京:中国水利水电出版社,2002.8
[2]王兴博.架空电力线路巡检飞行机器人路径规划研究[M]华北电力大学- 2006-05
[3] Jaensch G,,Hoffmann H, Markees A. Locating defects in high voltage transmission lines. Proceeding of the IEEE 8th International Conference on Transmission & Distribution Construction, Operation &Live-line Maintenance,1998:179-186
[4]张勇,谢强,李杰.电力系统防灾安全保障的现状与对策[C]. 2006年中国电机工程学会年会,郑州,2006.
[5]国内外自然灾害造成的电力系统事故[J].中国电力教育.2008 3
[6]陈竞成.输电网安全形势与对策[J].电力安全技术.2003,5(8).
[7]谢强,李杰.电力系统自然灾害的现状与对策[J].自然灾害学报.2006,15(4):126-131.
[8]胡超凡.2004年国家电网安全运行情况分析[J].中国电力.2005,38(5):9-10.
[9] Peungsungwal S, Pungsiri B, Chamnongthai K, et al.Autonomous robot for a power transmission line inspection. The IEEE International Symposium on Circuits and System, Sydney, Australia, 2001:121-124
[10]李杰.生命线工程抗震—基础理论与应用[M].北京:科学出版社,2005.
[11]孙才新.重视和加强防止复杂气候环境及输变电设备故障导致电网大面积事故的安全技术研究[J].中国电力,2004,37(6):1-8.
[12]谢强,张勇,李杰.华东电网500 kV任上5237线飑线风致倒塔事故调查分析[J].电网技术,2006年,30(10) :59-63,89
[13]谢强,钱摇琨,何涛,李杰.华东电网输电线路风致倒塔事故调查研究,同济大学生命线工程研究所研究报告,2005年12月
[14]日本電力安全委員会.送電線鉄塔倒壊事故調查報告書,平成14年11月28日.電力安全小委員会送電線鉄塔倒壊事故調查グルプ
[15] AIJ, JSCE and JGS, Report on the damage investigation of the Kocaeli Earthquake in Turkey. 2001, Maruse Corp., Tokyo, Japan.
[16] Task Force C2.02.24.Defense plan against extreme contingencies [R].CIGRE Technical Brochure 316,2007.
[17] Working Group B2.06.Big Storm Events:What we have learned [R].CIGRE Technical Brochure 344,2008.
[18]郭应龙、李国兴、尤传永.输电线路舞动[M].北京:中国电力出版社,2003年1月
[19]张玉生,何红太.基于GPRS无线技术的架空电力线路监测系统[J].微计算机信息,2005.21,(5):131-133.
[20]丁荣. 10kv及以下配电线路典型故障分析与预防[M].北京:中国电力出版社,2005.08
[21] G.Jaensch.,H.Hoffmann,A.Markees.Locating defects in high voltage transmission lines.Proceedings of the 1 998 IEEE 8th International Conference on Transmission& Distribution Construction,Operation&Live-line Maintenance.Orlando,FL USA:1998.179-186.
[22] D.M.Chiekering,D.Geiger,D.Heekerman.Learning Bayesian Networks:Search Methods and Experimental Results.In Proceedings of Fifth Conference on Artificial Intelligence and Statistics. Ft,Lauderdale,FL,Society for Artificial Intelligence in Statistics.1995.112-128
[23]李艳美.基于贝叶斯网络的数据挖掘应用研究[M].西安电子科技大学. 2008.01
[24] Agrawal R,Srikant R.Fast Algorithm for MiningAssociation Rules in Large Databases.In Research Report RJ9839,IBM Almaden Research Center,San Jose,CA.1994,6.
[25] De Campos L M,Huete J F.A new approach for learning belief networks using independence criteria[J].International Journal of Approximate Reasoning,2000,24,11-37
[26]杨莉,孙华昕,朱宏超.基于贝叶斯网络的多目标优化算法.华北电力大学学报[J].2007,34(1).128-131
[27]冀俊忠,刘椿年,江川等.贝叶斯网及其概率推理在智能教学中的应用[J].北京工业大学学报.2002,28(3).353-357
[28]周忠宝,董豆豆,周经伦.贝叶斯网络在可靠性分析中的应用[J].系统工程理论与实践.2006(6).95-100
[29]冀俊忠,阎静,刘椿年.基于I-B&B-MDL的贝叶斯网结构学习改进算法[J].北京工业大学学报.2006,32(5).437-441
[30]王双成,张明,陈乃激.基于因果语义定向的贝叶斯网络结构学习[J].计算机工程与应用.2007,43(8).29-31
[31] Yu I K. A novel shortterm generation scheduling technique of thermal units using ant colony search alg orithms. ElectricalPower and Energy Systems , 2001,23:471～479
[32]? Bonabeau E. Inspiration for optimization from social insectbehaviour. Nature 2000 , 406 :39～42
[33]楚瑞,基于蚁群算法的无人机航路规划[D].[硕士学位论文]西安:西北工业大学,2006
[34]李鹏,王自强,邝艳敏.基于改进蚁群算法的分类规则挖掘[J].农业网络信息,2007(10):13-15
[35]?税薇.?基于贝叶斯推理与蚁群算法的仿真飞行器航迹规划研究[M].?青岛科技大学. 2009.04.
[36]纪建伟著.电力系统分析[M].北京:中国水利水电出版社,2002.8
[37] Chanda R S, Bhattacharjee P K. A reliability approach to transmission expansion planning using fuzzy fault-tree model [J].Electric Power Systems Research (S0064-3075), 1998, 5(4): 101-108.
[37] Chanda R S, Bhattacharjee P K. A reliability approach to transmission expansion planning using fuzzy fault-tree model [J].Electric Power Systems Research (S0064-3075), 1998, 5(4): 101-108.
[39] Snjezana Blagajac,MineaFilipec,SlavkoKrajcar,et al.CADDiN=DATA+GIS+GA.IEEE,1998:1117-1121
[40] E.C.Yeh, Hahn Tram.Information integration in computerized distribution system planning.IEEE Transaction on Power System, 1997, 12(2):335-338
[41] Vladimiro Miranda,Ranito J V,Proencal L M,et al.Genetic algorithm in optilnal multistage distribution network planning[J].IEEE Trans. On Power Systems,1994,9(1):224-330
[2]王兴博.架空电力线路巡检飞行机器人路径规划研究[M]华北电力大学- 2006-05
[3] Jaensch G,,Hoffmann H, Markees A. Locating defects in high voltage transmission lines. Proceeding of the IEEE 8th International Conference on Transmission & Distribution Construction, Operation &Live-line Maintenance,1998:179-186
[4]张勇,谢强,李杰.电力系统防灾安全保障的现状与对策[C]. 2006年中国电机工程学会年会,郑州,2006.
[5]国内外自然灾害造成的电力系统事故[J].中国电力教育.2008 3
[6]陈竞成.输电网安全形势与对策[J].电力安全技术.2003,5(8).
[7]谢强,李杰.电力系统自然灾害的现状与对策[J].自然灾害学报.2006,15(4):126-131.
[8]胡超凡.2004年国家电网安全运行情况分析[J].中国电力.2005,38(5):9-10.
[9] Peungsungwal S, Pungsiri B, Chamnongthai K, et al.Autonomous robot for a power transmission line inspection. The IEEE International Symposium on Circuits and System, Sydney, Australia, 2001:121-124
[10]李杰.生命线工程抗震—基础理论与应用[M].北京:科学出版社,2005.
[11]孙才新.重视和加强防止复杂气候环境及输变电设备故障导致电网大面积事故的安全技术研究[J].中国电力,2004,37(6):1-8.
[12]谢强,张勇,李杰.华东电网500 kV任上5237线飑线风致倒塔事故调查分析[J].电网技术,2006年,30(10) :59-63,89
[13]谢强,钱摇琨,何涛,李杰.华东电网输电线路风致倒塔事故调查研究,同济大学生命线工程研究所研究报告,2005年12月
[14]日本電力安全委員会.送電線鉄塔倒壊事故調查報告書,平成14年11月28日.電力安全小委員会送電線鉄塔倒壊事故調查グルプ
[15] AIJ, JSCE and JGS, Report on the damage investigation of the Kocaeli Earthquake in Turkey. 2001, Maruse Corp., Tokyo, Japan.
[16] Task Force C2.02.24.Defense plan against extreme contingencies [R].CIGRE Technical Brochure 316,2007.
[17] Working Group B2.06.Big Storm Events:What we have learned [R].CIGRE Technical Brochure 344,2008.
[18]郭应龙、李国兴、尤传永.输电线路舞动[M].北京:中国电力出版社,2003年1月
[19]张玉生,何红太.基于GPRS无线技术的架空电力线路监测系统[J].微计算机信息,2005.21,(5):131-133.
[20]丁荣. 10kv及以下配电线路典型故障分析与预防[M].北京:中国电力出版社,2005.08
[21] G.Jaensch.,H.Hoffmann,A.Markees.Locating defects in high voltage transmission lines.Proceedings of the 1 998 IEEE 8th International Conference on Transmission& Distribution Construction,Operation&Live-line Maintenance.Orlando,FL USA:1998.179-186.
[22] D.M.Chiekering,D.Geiger,D.Heekerman.Learning Bayesian Networks:Search Methods and Experimental Results.In Proceedings of Fifth Conference on Artificial Intelligence and Statistics. Ft,Lauderdale,FL,Society for Artificial Intelligence in Statistics.1995.112-128
[23]李艳美.基于贝叶斯网络的数据挖掘应用研究[M].西安电子科技大学. 2008.01
[24] Agrawal R,Srikant R.Fast Algorithm for MiningAssociation Rules in Large Databases.In Research Report RJ9839,IBM Almaden Research Center,San Jose,CA.1994,6.
[25] De Campos L M,Huete J F.A new approach for learning belief networks using independence criteria[J].International Journal of Approximate Reasoning,2000,24,11-37
[26]杨莉,孙华昕,朱宏超.基于贝叶斯网络的多目标优化算法.华北电力大学学报[J].2007,34(1).128-131
[27]冀俊忠,刘椿年,江川等.贝叶斯网及其概率推理在智能教学中的应用[J].北京工业大学学报.2002,28(3).353-357
[28]周忠宝,董豆豆,周经伦.贝叶斯网络在可靠性分析中的应用[J].系统工程理论与实践.2006(6).95-100
[29]冀俊忠,阎静,刘椿年.基于I-B&B-MDL的贝叶斯网结构学习改进算法[J].北京工业大学学报.2006,32(5).437-441
[30]王双成,张明,陈乃激.基于因果语义定向的贝叶斯网络结构学习[J].计算机工程与应用.2007,43(8).29-31
[31] Yu I K. A novel shortterm generation scheduling technique of thermal units using ant colony search alg orithms. ElectricalPower and Energy Systems , 2001,23:471～479
[32]? Bonabeau E. Inspiration for optimization from social insectbehaviour. Nature 2000 , 406 :39～42
[33]楚瑞,基于蚁群算法的无人机航路规划[D].[硕士学位论文]西安:西北工业大学,2006
[34]李鹏,王自强,邝艳敏.基于改进蚁群算法的分类规则挖掘[J].农业网络信息,2007(10):13-15
[35]?税薇.?基于贝叶斯推理与蚁群算法的仿真飞行器航迹规划研究[M].?青岛科技大学. 2009.04.
[36]纪建伟著.电力系统分析[M].北京:中国水利水电出版社,2002.8
[37] Chanda R S, Bhattacharjee P K. A reliability approach to transmission expansion planning using fuzzy fault-tree model [J].Electric Power Systems Research (S0064-3075), 1998, 5(4): 101-108.
[37] Chanda R S, Bhattacharjee P K. A reliability approach to transmission expansion planning using fuzzy fault-tree model [J].Electric Power Systems Research (S0064-3075), 1998, 5(4): 101-108.
[39] Snjezana Blagajac,MineaFilipec,SlavkoKrajcar,et al.CADDiN=DATA+GIS+GA.IEEE,1998:1117-1121
[40] E.C.Yeh, Hahn Tram.Information integration in computerized distribution system planning.IEEE Transaction on Power System, 1997, 12(2):335-338
[41] Vladimiro Miranda,Ranito J V,Proencal L M,et al.Genetic algorithm in optilnal multistage distribution network planning[J].IEEE Trans. On Power Systems,1994,9(1):224-330