含分布式电源的配电网多目标电压无功优化研究
发布时间：2018-11-01 17:07
【摘要】：随着能源危机和环境恶化,越来越多的分布式电源并入配电网运行,但分布式电源的并网会使得配电网原有的电网结构及其运行方式发生较大的变化,一些传统的无功优化模型和优化算法由于其自身的局限性,已经不适用于含有多分布式电源的无功优化中。所以,如何建立含分布式电源的配电网无功优化模型和寻找与其相适应的优化算法已成为众多研究人员的共同目标。 本文首先简要介绍了传统配电网的接线方式以及其运行方式,归纳出各种配电网的接线都可以使用辐射型接线方式来进行等效的结论,并确定其潮流计算方法为前推回推法。由于本文所研究的分布式电源为小水电,通过对小水电的运行方式以及其接入配电网所带来的影响进行简要概述,根据小水电的特点建立含小水电的配电网无功优化模型。由于无功优化的目标选取了有功网损最小和电压偏差最小,所以本文以两个目标的优化问题对Pareto最优解的概念进行详细介绍,通过擂台赛法构造非支配解集,使用拥挤距离对非支配解进行裁剪并以拥挤距离最大的解作为全局最优解来引导搜索,最终形成解均匀分布的Pareto最优边界。在无功优化算法方面,本文选取了粒子群算法和“教与学”优化算法进行介绍,在对两种算法的优缺点、改进以及其在无功优化中的应用进行详细介绍之后,结合粒子群算法的寻优能力和“教与学”优化算法多样性搜索的优点,提出了适用于本文无功优化模型的改进粒子群算法。 为验证以上模型和算法的可行性,本文将以某市含小水电的配电线路进行无功优化。首先对该市两条无小水电和含小水电的线路进行潮流分析,计算结果表明本文所使用的潮流计算方法对配电网的潮流计算是可行的。接着结合文中所阐述的三种算法分别对含小水电的线路进行无功优化,通过对三种算法的优化结果进行比较分析,可以得出改进后的粒子群算法具有更好的优化效果,可以获得较为全面的Pareto最优曲线,即获得更为全面的优化解集以供决策者进行选择,对实现含小水电配电网的降损调压以及经济运行具有很好的理论指导价值。
[Abstract]:With the energy crisis and environmental deterioration, more and more distributed power sources are incorporated into the distribution network operation, but the distribution network structure and operation mode will be greatly changed by the grid connection of distributed generation. Some traditional reactive power optimization models and algorithms are not suitable for reactive power optimization with multiple distributed power sources due to their own limitations. Therefore, how to establish a reactive power optimization model with distributed generation and find suitable optimization algorithms has become the common goal of many researchers. In this paper, the traditional distribution network connection mode and its operation mode are introduced briefly, and the conclusion that all kinds of distribution network wiring can be equivalent by radiation connection mode is concluded, and the method of power flow calculation is determined as forward push back push method. Because the distributed power source studied in this paper is small hydropower, the reactive power optimization model of distribution network with small hydropower is established according to the characteristics of small hydropower through a brief summary of the operation mode of small hydropower and the influence of its access to distribution network. Because the target of reactive power optimization selects the minimum active power network loss and the minimum voltage deviation, the concept of Pareto optimal solution is introduced in detail with the optimization problem of two objectives, and the non-dominant solution set is constructed by the beating table method. The non-dominated solution is clipped by crowding distance, and the solution with the largest congestion distance is used as the global optimal solution to guide the search. Finally, the Pareto optimal boundary of uniform distribution of the solution is formed. In the aspect of reactive power optimization, particle swarm optimization algorithm and teaching and learning optimization algorithm are selected in this paper. After introducing the advantages and disadvantages of the two algorithms, their improvement and their application in reactive power optimization are introduced in detail. Combining the advantages of particle swarm optimization and diversity search of "teaching and learning" optimization algorithm, an improved particle swarm optimization algorithm, which is suitable for the reactive power optimization model in this paper, is proposed. In order to verify the feasibility of the above model and algorithm, the reactive power optimization of a distribution line with small hydropower in a certain city will be carried out in this paper. First, the power flow analysis of two lines without and with small hydropower in the city is carried out. The results show that the power flow calculation method used in this paper is feasible for the power flow calculation of distribution network. Then combined with the three algorithms described in this paper, the reactive power optimization of the lines with small hydropower is carried out respectively. Through the comparison and analysis of the optimization results of the three algorithms, it can be concluded that the improved particle swarm optimization algorithm has better optimization effect. A more comprehensive Pareto optimal curve can be obtained, that is, a more comprehensive set of optimal solutions can be obtained for decision makers to choose, which has a good theoretical guiding value for the realization of loss reduction and voltage regulation and economic operation of distribution networks with small hydropower.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM714.3
本文编号：2304554
[Abstract]:With the energy crisis and environmental deterioration, more and more distributed power sources are incorporated into the distribution network operation, but the distribution network structure and operation mode will be greatly changed by the grid connection of distributed generation. Some traditional reactive power optimization models and algorithms are not suitable for reactive power optimization with multiple distributed power sources due to their own limitations. Therefore, how to establish a reactive power optimization model with distributed generation and find suitable optimization algorithms has become the common goal of many researchers. In this paper, the traditional distribution network connection mode and its operation mode are introduced briefly, and the conclusion that all kinds of distribution network wiring can be equivalent by radiation connection mode is concluded, and the method of power flow calculation is determined as forward push back push method. Because the distributed power source studied in this paper is small hydropower, the reactive power optimization model of distribution network with small hydropower is established according to the characteristics of small hydropower through a brief summary of the operation mode of small hydropower and the influence of its access to distribution network. Because the target of reactive power optimization selects the minimum active power network loss and the minimum voltage deviation, the concept of Pareto optimal solution is introduced in detail with the optimization problem of two objectives, and the non-dominant solution set is constructed by the beating table method. The non-dominated solution is clipped by crowding distance, and the solution with the largest congestion distance is used as the global optimal solution to guide the search. Finally, the Pareto optimal boundary of uniform distribution of the solution is formed. In the aspect of reactive power optimization, particle swarm optimization algorithm and teaching and learning optimization algorithm are selected in this paper. After introducing the advantages and disadvantages of the two algorithms, their improvement and their application in reactive power optimization are introduced in detail. Combining the advantages of particle swarm optimization and diversity search of "teaching and learning" optimization algorithm, an improved particle swarm optimization algorithm, which is suitable for the reactive power optimization model in this paper, is proposed. In order to verify the feasibility of the above model and algorithm, the reactive power optimization of a distribution line with small hydropower in a certain city will be carried out in this paper. First, the power flow analysis of two lines without and with small hydropower in the city is carried out. The results show that the power flow calculation method used in this paper is feasible for the power flow calculation of distribution network. Then combined with the three algorithms described in this paper, the reactive power optimization of the lines with small hydropower is carried out respectively. Through the comparison and analysis of the optimization results of the three algorithms, it can be concluded that the improved particle swarm optimization algorithm has better optimization effect. A more comprehensive Pareto optimal curve can be obtained, that is, a more comprehensive set of optimal solutions can be obtained for decision makers to choose, which has a good theoretical guiding value for the realization of loss reduction and voltage regulation and economic operation of distribution networks with small hydropower.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM714.3
【引证文献】
相关硕士学位论文 前2条
1 张韵平;基于改进粒子群算法的配电网无功优化研究[D];广东工业大学;2015年
2 罗欢;含风电及小水电群的配电网无功优化策略研究[D];重庆大学;2015年
，本文编号：2304554
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