基于有序二叉决策图的电网主动解列策略搜索方法研究

发布时间：2019-05-07 12:06

【摘要】：随着电力系统的飞速发展,大型联合电网正在逐渐形成。互联电网的结构、规模日趋复杂和庞大,运行条件和潮流分布也越来越灵活,对互联电网的安全稳定运行提出了更高的要求;并且,随着互联电网的不断扩大,电网互联的联动效应更加明显,在事故扰动过程中,其影响和波及的范围也将扩大,如果处理不当,很可能出现大范围的停电事故,造成严重的社会影响和巨大的经济损失。基于此,针对目前关于主动解列在线搜索研究的不足,本文将实际电网与图论及布尔函数相联系,研究了电网的主动解列安全运行策略的搜索方法,主要成果有以下几方面:第一、研究了电网主动解列必须满足的三个稳态约束条件,并建立了适用于有序二叉决策图(OBDD)技术搜索电网解列策略的图论模型——节点权图模型。通过深入研究电网解列前后电网结构的物理特性以及工作状态的变化,设计了电网图论模型中的节点权重,建立了适用于电网解列分析的实用简化数学模型,并给出了适用于OBDD分析的电网模型数学表达矩阵;第二、通过分析电力系统解列前后的拓扑结构和运行特性的变化,提出了电力系统网络拓扑的化简方法,形成了电网简化拓扑模型。根据电网简化拓扑模型,给出了电网合理解列的边界条件,并给出了适用于有序二叉决策图(OBDD)分析的电网解列边界条件的数学表达。第三、提出了基于OBDD的电网解列策略的搜索方法。借助简单算例详细介绍了基于OBDD技术搜索电网备选解列策略的具体方法和过程,并给出了电网简化图与原始电网的解列策略之间的一一对应原则。此外,还提出了电网主动解列策略搜索工作的一种时间分配方案,为基于OBDD的电网解列策略的搜索方法的实际应用提供保障。对IEEE-39和IEEE-118节点系统的仿真结果表明,本文所提的方法在搜索电网的合理解列策略方面具有比较高效的求解性能,能够在较短的时间内为处于极端状态下的电力系统提供合理的解列方案。
[Abstract]:With the rapid development of power system, large-scale United power grid is gradually formed. The structure of interconnected power grid is becoming more and more complex and huge, and the distribution of operation conditions and power flow is becoming more and more flexible, which puts forward higher requirements for the safe and stable operation of interconnected power grid. Moreover, with the continuous expansion of the interconnected power grid, the linkage effect of the interconnection of the power grid is more obvious, and the scope of its influence and spread will also be expanded in the course of the accident disturbance. If handled incorrectly, there will probably be a large-scale blackout accident. Causing serious social impact and huge economic losses. Based on this, aiming at the deficiency of on-line search on active unlisting, this paper studies the searching method of active unlisted security operation strategy by linking the actual power grid with graph and Boolean function, and studies the searching method of active unlisted security operation strategy of power network. The main results are as follows: firstly, the three steady-state constraints that must be satisfied in active unlisting of power grid are studied. A graph theory model-node weight graph model, which is suitable for searching power network unlisting strategy with ordered binary decision graph (OBDD) technology, is established. Based on the in-depth study of the physical characteristics and working state changes of the power network structure before and after the de-listing, the node weights in the grid graph theory model are designed, and a practical simplified mathematical model suitable for the analysis of the power network unraveling is established. The mathematical expression matrix of power network model suitable for OBDD analysis is given. Secondly, by analyzing the changes of topology structure and operation characteristics of power system before and after unlisting, a simplified topology model of power system is proposed. According to the simplified topological model of power network, the boundary conditions of reasonable unalignment of power network are given, and the mathematical expression of the unlisted boundary condition of power network suitable for (OBDD) analysis of ordered binary decision graph is given. Thirdly, a search method based on OBDD is proposed for power network de-listing strategy. With the help of a simple example, the detailed method and process of searching the alternative unlisting strategy based on OBDD technology are introduced in detail, and the one-to-one correspondence principle between the simplified diagram of the power grid and the de-listing strategy of the original power grid is given. In addition, a time allocation scheme for searching active delisting strategy of power grid is proposed, which can guarantee the practical application of the searching method of power network unlisting strategy based on OBDD. The simulation results of IEEE-39 and IEEE-118 node systems show that the proposed method has high performance in searching the reasonable unmarshalling strategy of power grid. It can provide a reasonable de-listing scheme for the power system in the extreme state in a short period of time.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM727

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