电网防灾调度技术研究

发布时间：2018-04-19 11:14

本文选题：自然灾害 + 防灾调度　；参考：《浙江大学》2016年硕士论文

【摘要】：现代社会对电能供应的可靠性需求越来越高,一旦电力供应中断将造成难以估量的损失。极端外部自然灾害对电网的安全运行造成了严重的威胁,充分地了解我国电网当前的防灾减灾技术、方法与措施,归纳总结现有方法的问题与不足,利用大数据时代下的理论与技术来改善现状、设计开发新的防御功能,对于提高电网抵御自然灾害的能力意义重大,为此本文开展了以下研究：首先,探讨了我国电网的安全防御框架,详细地总结了电网防灾减灾的现状与问题。在归纳电网防灾大数据的基础上,提出了基于大数据的电网防灾调度系统设计方案,旨在解决电网防灾调度方面现存的突出问题。方案详细地设计了包括电网输供电能力评估在内的一系列重要功能,系统的数据流与逻辑决策、基于大数据平台的软件架构等内容,以达到提升电网防灾调度能力的目标。其次,提出了一种计及主变可载性约束的三阶段配电网供电能力评估方法。针对现有评估方法未能考虑主变可载能力的问题,建立了主变可载性约束模型,模型考虑变压器的绕组热点温度约束、故障率约束及经济损益约束,通过定级风险严重度等级对变压器增容系数进行风险约束校验。此外,针对现有评估方法难以适应复杂多变的实际场景的问题,提出不同工况下的评估原则。方法包含预评估、约束分析、校验评估三个阶段,以重复潮流法为基础进行循环评估得到最终结果。两个算例的仿真结果表明该方法可为不同场景下的配电网调度运行提供辅助决策建议。最后,在上述研究的基础上,对贵阳地区电网多维度风险调度与应急指挥系统的工程开发与实现进行详实的介绍,包括系统的总体流程、数据接口、各功能模块、开发与运行环境、硬件配置、后台模块的组织、人机界面效果等内容,旨在为贵阳地区电网运行人员提供多样化的防灾调度手段,提高电网的安全运行水平。
[Abstract]:The demand for the reliability of power supply is increasing in modern society. Once the power supply is interrupted, it will cause incalculable losses.The extreme external natural disasters pose a serious threat to the safe operation of the power grid, fully understand the current technology, methods and measures of disaster prevention and mitigation in China's power grid, and sum up the problems and shortcomings of the existing methods.It is of great significance to use the theory and technology under big data era to improve the present situation and to design and develop new defense functions to improve the power grid's ability to resist natural disasters. For this reason, this paper has carried out the following research: first of all,This paper discusses the security defense framework of China's power grid, and summarizes the present situation and problems of power grid disaster prevention and mitigation in detail.On the basis of summarizing big data's disaster prevention, the paper puts forward a design scheme of power network disaster prevention and dispatch system based on big data, which aims to solve the outstanding problems existing in power grid disaster prevention and dispatch.A series of important functions, such as power transmission and power transmission capability evaluation, system data flow and logic decision, and software architecture based on big data platform, are designed in detail to achieve the goal of improving power grid disaster prevention and dispatching capability.Secondly, a three-stage power supply capability evaluation method considering the load constraints of main transformer is proposed.In view of the failure of the existing evaluation methods to consider the loadability of the main transformer, a load constraint model of the main transformer is established. The model takes into account the temperature constraints of the windings of the transformer, the failure rate constraints and the economic profit and loss constraints.The capacity coefficient of transformer is checked by risk severity.In addition, in view of the problem that the existing evaluation methods are difficult to adapt to the complicated and changeable practical scenarios, the evaluation principles under different operating conditions are put forward.The method consists of three stages: pre-evaluation, constraint analysis and checkout evaluation. The final results are obtained by cyclic evaluation based on repeated power flow method.The simulation results of two examples show that the proposed method can provide auxiliary decision advice for dispatching operation of distribution network in different scenarios.Finally, on the basis of the above research, the engineering development and implementation of the multi-dimensional risk dispatching and emergency command system in Guiyang power network are introduced in detail, including the overall process of the system, the data interface, each functional module.The development and operation environment, hardware configuration, background module organization and man-machine interface effect are designed to provide a variety of disaster prevention and dispatch methods for the power grid operators in Guiyang area, and to improve the safe operation level of the power grid.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TM73

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