基于NSGA-Ⅱ的多目标配电网重构
发布时间：2018-09-07 17:52
【摘要】：配电网重构是配电自动化内容的重要组成部分,在保持配电网运行经济性、提高供电质量和供电可靠性方面,配电网重构都是不错的选择。在配电网正常运行时,可以通过改变网络结构,调整开关通断状态,达到消除过载,平衡负荷,优化网损的目的；在配电网出现故障时,又可以隔离故障,并尽可能多的对非故障负荷恢复供电,减少停电区域。本文根据配电网的发展趋势,从配电网经济、安全、可靠性运行方面考虑,得出配电网重构将是一个多目标优化问题,多目标优化将成为配电网重构新的研究方向。在总结前人研究的基础上,本文做了如下几方面的工作。首先,本文分析了配电网的发展现状以及配电网重构的方法,根据配电网重构的多目标优化的要求,本文提出了三个目标函数,即有功网损最优、节点电压偏移量最小以及负荷均衡化,分别从配电网的经济性,电能质量和安全可靠性方面考虑。其次,较为详细的阐述了遗传算法的基本原理,并分析了遗传算法在求解配电网单目标和多目标优化时的优势和不足。由于简单遗传算法在处理多目标配电网重构时效果不太好,权重系数对结果影响较大,因此引入了基于快速非支配排序的遗传算法(NSGA-II),采用NSGA-II算法对种群个体进行非支配排序分层,实现对种群中个体的全局最优,最终寻找到Pareto最优前沿,得到多目标配电网重构的Pareto最优解集：为了提高搜索效率,提出了一种对种群中“非法”个体筛选的方法。建立配电网络节点和边的关联矩阵,在除去任意一行向量后,通过判断矩阵中余下行向量是否线性相关来确定个体是否满足配电网辐射结构。最后,将快速非支配遗传算法用于16节点和PGE的69节点的配电网重构中,根据计算结果,表明结合配电网特点的NSGA-II算法,具有良好的全局搜索能力,能够有效降低网络损耗,提高节点电压,平衡负荷,验证了NSGA-II算法在配电网重构中的实用性。
[Abstract]:Distribution network reconfiguration is an important part of distribution automation. Distribution network reconfiguration is a good choice in maintaining the economic operation of distribution network and improving the quality and reliability of power supply. In the normal operation of the distribution network, we can change the network structure, adjust the on-off state of the switch to eliminate the overload, balance the load, optimize the network loss, and isolate the fault when the distribution network fails. And as much as possible to restore power to non-fault load, reduce power failure areas. According to the development trend of distribution network, considering the economy, security and reliability of distribution network, this paper concludes that the reconfiguration of distribution network will be a multi-objective optimization problem, and multi-objective optimization will become a new research direction of distribution network reconfiguration. On the basis of summing up the previous studies, this paper has done the following work. First of all, this paper analyzes the current situation of distribution network development and the method of distribution network reconfiguration. According to the requirements of multi-objective optimization of distribution network reconfiguration, this paper proposes three objective functions, that is, the optimal loss of active power network. The minimum node voltage offset and load equalization are considered in terms of economy, power quality and safety and reliability of distribution network. Secondly, the basic principle of genetic algorithm is described in detail, and the advantages and disadvantages of genetic algorithm in solving single-objective and multi-objective optimization of distribution network are analyzed. Because the simple genetic algorithm is not very effective in dealing with the reconfiguration of multi-objective distribution network, the weight coefficient has a great influence on the result. Therefore, the genetic algorithm (NSGA-II) based on fast undominated ordering is introduced, and the NSGA-II algorithm is used to stratify the individual in order to achieve the global optimization of the individual in the population, and finally to find the Pareto optimal frontier. The Pareto optimal solution set of multi-objective distribution network reconfiguration is obtained. In order to improve the search efficiency, a method of "illegal" individual selection in the population is proposed. The correlation matrix of distribution network nodes and edges is established. After removing any row of vectors, whether the residual downlink vectors in the matrix are linearly correlated or not is determined to determine whether the individual satisfies the radiation structure of the distribution network. Finally, the fast non-dominated genetic algorithm is applied to the distribution network reconfiguration of 16-bus and PGE 69-bus. According to the calculation results, the NSGA-II algorithm combined with the characteristics of the distribution network has good global search ability and can effectively reduce the network loss. The utility of NSGA-II algorithm in distribution network reconfiguration is verified by increasing node voltage and balancing load.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM727
本文编号：2228990
[Abstract]:Distribution network reconfiguration is an important part of distribution automation. Distribution network reconfiguration is a good choice in maintaining the economic operation of distribution network and improving the quality and reliability of power supply. In the normal operation of the distribution network, we can change the network structure, adjust the on-off state of the switch to eliminate the overload, balance the load, optimize the network loss, and isolate the fault when the distribution network fails. And as much as possible to restore power to non-fault load, reduce power failure areas. According to the development trend of distribution network, considering the economy, security and reliability of distribution network, this paper concludes that the reconfiguration of distribution network will be a multi-objective optimization problem, and multi-objective optimization will become a new research direction of distribution network reconfiguration. On the basis of summing up the previous studies, this paper has done the following work. First of all, this paper analyzes the current situation of distribution network development and the method of distribution network reconfiguration. According to the requirements of multi-objective optimization of distribution network reconfiguration, this paper proposes three objective functions, that is, the optimal loss of active power network. The minimum node voltage offset and load equalization are considered in terms of economy, power quality and safety and reliability of distribution network. Secondly, the basic principle of genetic algorithm is described in detail, and the advantages and disadvantages of genetic algorithm in solving single-objective and multi-objective optimization of distribution network are analyzed. Because the simple genetic algorithm is not very effective in dealing with the reconfiguration of multi-objective distribution network, the weight coefficient has a great influence on the result. Therefore, the genetic algorithm (NSGA-II) based on fast undominated ordering is introduced, and the NSGA-II algorithm is used to stratify the individual in order to achieve the global optimization of the individual in the population, and finally to find the Pareto optimal frontier. The Pareto optimal solution set of multi-objective distribution network reconfiguration is obtained. In order to improve the search efficiency, a method of "illegal" individual selection in the population is proposed. The correlation matrix of distribution network nodes and edges is established. After removing any row of vectors, whether the residual downlink vectors in the matrix are linearly correlated or not is determined to determine whether the individual satisfies the radiation structure of the distribution network. Finally, the fast non-dominated genetic algorithm is applied to the distribution network reconfiguration of 16-bus and PGE 69-bus. According to the calculation results, the NSGA-II algorithm combined with the characteristics of the distribution network has good global search ability and can effectively reduce the network loss. The utility of NSGA-II algorithm in distribution network reconfiguration is verified by increasing node voltage and balancing load.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM727
【参考文献】
相关期刊论文 前1条
1 朱峻;薛禹胜;;配电网系统恢复专家系统[J];电力系统自动化;1991年03期
，本文编号：2228990
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