基于“改良”策略遗传算法的配电网重构研究
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摘要
许多城市配电网采用闭环结构，开环运行方式，在这种运行方式下，可对众多的分段开关和少量的联络开关进行分合操作，实现配电网重构，达到降低网损、隔离故障、转移负荷等目的。
随着我国电力市场的建立，提高经济效益、改善供电质量已成为我国城市供电企业所面临的主要问题之一，而配电网重构则是提高配电系统安全性和经济性的重要手段。目前，配电自动化技术和负荷预测技术的发展已使进行配电网重构成为可能。
在配电网重构的研究方面，到目前为止，国内外提出的常用的优化算法有最优流模式法(OFP)、支路交换法、神经网络算法(ANN)、蚁群最优算法(ACO)、模拟退火算法(SA)、遗传算法(GA)、Tabu算法、专家系统等。在这些算法中，遗传算法由于具有较好的性能，可得到全局最优解，受到了众多专家学者的关注。
目前遗传算法用于配电网重构计算，所面临的主要问题有如何提高计算效率、消除“不可行解”、提高算法的实用性等。为了解决上述问题，本人在阅读大量相关文献，分析现有算法的基础上，根据配电网重构问题的应用需求，建立了相关的数学模型，提出了“特殊支”、“特殊节点”等用于配电网重构的概念，以及它们的存储方法；分析了“不可行解”的危害，并比较了现有的解决方法；在此基础上，提出了基于“改良”策略的配电网重构遗传算法及其实现技术，该算法可以有效地解决“不可行解”问题，具有较高的搜索效率；为提高算法的实用性，本人还提出了可以和前推回代潮流算法有效配合的动态编码和解码技术及其实现方法；最后，在前述理论和技术的基础上进行了编程，同时提出了父代结果保留和分组计算等策略。
本文采用三个标准算例，以重构后网损最小为目标进行了验算，表明本文提出的算法和技术可以有效地用于解决配电网重构问题，计算程序结构合理、编写正确。
本文提出的基于“改良”策略的配电网重构遗传算法，不仅可以应用于配电网重构，还可以用于业扩报装的电源引接优化，城网规划的优化设计以及改善网络电压水平等方面的工作，具有广泛的应用前景，而动态编码和解码技术、父代结果保留和分组计算策略则为该算法的实际应用奠定了基础。
The structures distribution networks are closed loops structure in the most cities, but when they are operating the loops will be opened. In this way, the distribution network reconfiguration can be realized by opening or closing the section breakers or tie breakers in order to reduce network losses, insulate faults, displace loads etc
With the establishing of Chinese power market, it has become one of the important problems for the city power companies in our country to enhance the economy benefit and improve the quality of power supply, and that distribution network reconfiguration is the important means to improve the economy benefit and security of distribution power system. At present, the developments of distribution power system automatization and load forecast techniques have made distribution network reconfiguration become possible.
Up to now, inside and outside the country, among all of the optimization algorithms that have been proposed for solving the distribution network reconfiguration problem, the OFP, branches exchange algorithm, ANN, ACO, SA, GA, Tabu and expert system are commonly used. In these algorithms because GA has preferable capability and can get the best solution of overall situation, it has been drawing more and more experts' attention.
Now when GA is used to solve the distribution network reconfiguration problem, the main problems that it is faced are how to enhance the calculation efficiency, eliminate the "infeasible solutions", and improve its practicability. For solving these problems, the author read a lot of correlation literatures, analyzied the algorithms that have been proposed and the application requirements of distribution network reconfiguration. Based on these, the author builds the maths model for distribution network reconfiguration, proposes the notions of "special branch", "special node" etc and their storing means; analyzes the harm of "infeasible solutions" and compares the methods have been proposed for solving this problem; proposes the genetic algorithm based on "improvement" strategy for power distribution network reconfiguration and its realization technique, which can solve the "infeasible solutions" problem effectively and has relatively high search efficiency; for enhancing the practicability of the algorithm, t
he author also proposes the dynamic encoding and decoding technique and their realization methods, which can be used with fore back super session power flow algorithm. At last, a program based on these
algorithms and techniques is presented, in which the solutions reserve and grouping calculation strategies are used.
At the end of the paper the solutions of three standard test computations are shown, in which network losing is minimized by distribution network reconfiguration. They make clear that the algorithms and techniques proposed in this paper can be effectively used in solving the distribution network reconfiguration problem; the structure of the program is reasonable and the writing of program is right.
The genetic algorithm based on "improvement" strategy for power distribution network reconfiguration proposed in this paper not only can be used in distribution network reconfiguration, but also can be used in the power source selection optimization in power company business extension, the design of distribution network, and the improvement of voltage level. It has vast range of application prospects. The dynamic encoding and decoding, the solution reserve and grouping calculation strategies lay a foundation of its practical application.
随着我国电力市场的建立，提高经济效益、改善供电质量已成为我国城市供电企业所面临的主要问题之一，而配电网重构则是提高配电系统安全性和经济性的重要手段。目前，配电自动化技术和负荷预测技术的发展已使进行配电网重构成为可能。
在配电网重构的研究方面，到目前为止，国内外提出的常用的优化算法有最优流模式法(OFP)、支路交换法、神经网络算法(ANN)、蚁群最优算法(ACO)、模拟退火算法(SA)、遗传算法(GA)、Tabu算法、专家系统等。在这些算法中，遗传算法由于具有较好的性能，可得到全局最优解，受到了众多专家学者的关注。
目前遗传算法用于配电网重构计算，所面临的主要问题有如何提高计算效率、消除“不可行解”、提高算法的实用性等。为了解决上述问题，本人在阅读大量相关文献，分析现有算法的基础上，根据配电网重构问题的应用需求，建立了相关的数学模型，提出了“特殊支”、“特殊节点”等用于配电网重构的概念，以及它们的存储方法；分析了“不可行解”的危害，并比较了现有的解决方法；在此基础上，提出了基于“改良”策略的配电网重构遗传算法及其实现技术，该算法可以有效地解决“不可行解”问题，具有较高的搜索效率；为提高算法的实用性，本人还提出了可以和前推回代潮流算法有效配合的动态编码和解码技术及其实现方法；最后，在前述理论和技术的基础上进行了编程，同时提出了父代结果保留和分组计算等策略。
本文采用三个标准算例，以重构后网损最小为目标进行了验算，表明本文提出的算法和技术可以有效地用于解决配电网重构问题，计算程序结构合理、编写正确。
本文提出的基于“改良”策略的配电网重构遗传算法，不仅可以应用于配电网重构，还可以用于业扩报装的电源引接优化，城网规划的优化设计以及改善网络电压水平等方面的工作，具有广泛的应用前景，而动态编码和解码技术、父代结果保留和分组计算策略则为该算法的实际应用奠定了基础。
The structures distribution networks are closed loops structure in the most cities, but when they are operating the loops will be opened. In this way, the distribution network reconfiguration can be realized by opening or closing the section breakers or tie breakers in order to reduce network losses, insulate faults, displace loads etc
With the establishing of Chinese power market, it has become one of the important problems for the city power companies in our country to enhance the economy benefit and improve the quality of power supply, and that distribution network reconfiguration is the important means to improve the economy benefit and security of distribution power system. At present, the developments of distribution power system automatization and load forecast techniques have made distribution network reconfiguration become possible.
Up to now, inside and outside the country, among all of the optimization algorithms that have been proposed for solving the distribution network reconfiguration problem, the OFP, branches exchange algorithm, ANN, ACO, SA, GA, Tabu and expert system are commonly used. In these algorithms because GA has preferable capability and can get the best solution of overall situation, it has been drawing more and more experts' attention.
Now when GA is used to solve the distribution network reconfiguration problem, the main problems that it is faced are how to enhance the calculation efficiency, eliminate the "infeasible solutions", and improve its practicability. For solving these problems, the author read a lot of correlation literatures, analyzied the algorithms that have been proposed and the application requirements of distribution network reconfiguration. Based on these, the author builds the maths model for distribution network reconfiguration, proposes the notions of "special branch", "special node" etc and their storing means; analyzes the harm of "infeasible solutions" and compares the methods have been proposed for solving this problem; proposes the genetic algorithm based on "improvement" strategy for power distribution network reconfiguration and its realization technique, which can solve the "infeasible solutions" problem effectively and has relatively high search efficiency; for enhancing the practicability of the algorithm, t
he author also proposes the dynamic encoding and decoding technique and their realization methods, which can be used with fore back super session power flow algorithm. At last, a program based on these
algorithms and techniques is presented, in which the solutions reserve and grouping calculation strategies are used.
At the end of the paper the solutions of three standard test computations are shown, in which network losing is minimized by distribution network reconfiguration. They make clear that the algorithms and techniques proposed in this paper can be effectively used in solving the distribution network reconfiguration problem; the structure of the program is reasonable and the writing of program is right.
The genetic algorithm based on "improvement" strategy for power distribution network reconfiguration proposed in this paper not only can be used in distribution network reconfiguration, but also can be used in the power source selection optimization in power company business extension, the design of distribution network, and the improvement of voltage level. It has vast range of application prospects. The dynamic encoding and decoding, the solution reserve and grouping calculation strategies lay a foundation of its practical application.
引文
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[2] 刘健．变结构耗散网络——配电自动化新算法．北京：中国水利水电出版社，1999．
[3]刘莉，陈学允．基于模糊遗传算法的配电网络重构．中国电机工程学报，2000，20(2)：66-69．
[4] Shirmohammadi D,Wayne Hong H. Reconfiguration of Electric Distribution Networks for Resistive Line Losses Reduction. IEEE Transon Power Delivery, 1989,4(2): 1492～1498.
[5] Civanlar S, Grainger J J, Yin H, etal. Distribution feeder reconfiguration for loss reduction. IEEE Transon Power Delivery, 1988, (3): 1217-1223.
[6] 吴建中，余贻鑫．一种高效的配电网供电恢复算法．电网技术，2003，27(10)：82-86．
[7] Lin Whei-Min, Chin Hong-Chan. A New Approach for Distribution Feeder Reconfiguration for Loss Reduction and Service Restoration. IEEE Transon Power Delivery, 1998,13(3):870～875.
[8] 赵冬梅，郑朝明，高曙．配电网的供电优化恢复策略．电网技术，2003，27(5)：67-71．
[9] 杨明皓，黄单舸．配电网供电恢复决策的实时计算方法．电力系统自动化，2000，24(5)：23-26．
[10] Lin, C.-H. Distribution network reconfiguration for load balancing with a coloured Petri net algorithm[J]. Generation, Transmission and Distribution, lEE Proceedings-, 2003, 150(3):317-324.
[11] 段刚，余贻鑫．电力系统NP难问题全局优化算法的研究．电力系统自动化，2001，25(5)：14～18．
[12] 毕鹏翔，刘健，张文元．配电网络重构的研究．电力系统自动化，2001，25(14)：54～60．
[13] Stewart B S, Liaw C F, White Ⅲ C C. A Bibliography of Heuristic Search Research
Through 1992. IEEE Transon Systems, Man, and Cybernetics, 1994,24(2):268～2934
[14] 吴本悦，赵登福，刘云，等．一种新的配电网络重构最优流模式算法．西安交通大学学报，1999，33(4)：22-24．
[15] 毕鹏翔，刘健，张文元．配电网络重构的改进支路交换法．中国电机工程学报，2001，21(8)98-103．
[16] KimH, Ko Y, Jung K H. Artificial neural-network based on feeder reconfiguration for loss reduction in distribution systems. IEEE Transon Power Delivery, 1993, 8(3):1356-1366.
[17] Kim H, Ko Y, Jung K H. Artificial Neural-Network Based Feeder Reconfiguration for Loss Reduction in Distribution Systems. IEEE Transon Power Delivery, 1993,8(3): 1356～1366.
[18] 陈根军 王磊 唐国庆，基于蚁群最优的配电网络重构算法．电力系统及其自动化学报，2001，13(2)：48～53．
[19] 倪秋龙 黄民翔，基于支路交换的模拟退火算法在配电网规划中的应用．电力系统及其自动化学报，2000，12(4)：31～35．
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