分散式风电接入配网无功优化控制

发布时间：2018-01-13 16:13

本文关键词：分散式风电接入配网无功优化控制　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：风力发电技术日益成熟,已成为我国电力工业的重要组成部分。国家出台相关政策鼓励分散式风电的发展。分散式风电是将风电机组以分散多点的方式接入低电压配电系统,风能的随机性和间歇性将会引起电网潮流和系统电压的频繁变化,给电网运行带来不利影响。制定分散式风电接入地区的无功优化控制策略,将有助于解决这一问题。本文以分散式风电接入地区配网为研究对象,根据电网中不同无功补偿设备的运行特点制定相关的控制策略,本文主要工作如下： (1)研究风电机组的有功无功出力特性,配电网中无功补偿设备的运行特性。分析配电网中无功补偿设备的配置原则,总结无功补偿设备在配电网的安装地点和容量的选择以及无功功率控制策略。 (2)分散式风电并网会对配电网的运行造成一定的影响。考虑风电出力的波动性和随机性,研究风电机组类型不同,接入位置不同及所接电网负荷不同时配电网的运行状况。并引入了电压网损改善指标,使用改进牛顿拉夫逊法进行潮流计算,分析了分散式风电接入后对电网电压网损的影响程度。通过对IEEE33节点系统的仿真,使用实测风电出力与负荷数据,分析各种情况下风电接入对系统影响的变化规律,为分散式风电接入电网提供了有益的参考。 (3)考虑分散式风电接入电网的影响制定相关控制策略：日无功优化控制和短时无功优化控制。考虑到投切电容器组投切次数限制,而且无功出力无法连续调节的特性,制订日无功优化策略,优化的决策变量为电容器组的投切时间及容量,以一天24小时总有功网损为目标函数；根据SVC/SVG及风电机组的无功出力连续快速调节特性,制定短时无功优化策略,优化决策变量为SVC/SVG及风电组的无功出力,选用全网节点电压偏移额定值最小为目标函数。使用实际电网模型进行仿真,验证优化策略的可行性。
[Abstract]:Wind power generation technology is becoming more and more mature. It has become an important part of China's power industry. The state has issued relevant policies to encourage the development of decentralized wind power. Decentralized wind power is to connect wind turbines to low-voltage distribution systems in a decentralized multi-point manner. The randomness and intermittency of wind energy will cause frequent changes in power flow and system voltage, which will adversely affect the operation of the power grid. The optimal reactive power control strategy for decentralized wind power access areas is formulated. This paper takes the decentralized wind power distribution network as the research object and formulates the relevant control strategy according to the operation characteristics of different reactive power compensation equipment in the power network. The main work of this paper is as follows: 1) the characteristics of active and reactive power output of wind turbines and the operation characteristics of reactive power compensation equipment in distribution network are studied, and the configuration principle of reactive power compensation equipment in distribution network is analyzed. The selection of installation location and capacity of reactive power compensation equipment in distribution network and reactive power control strategy are summarized. (2) decentralized wind power grid connection will have a certain impact on the operation of distribution network. Considering the fluctuation and randomness of wind power output, different types of wind turbine units are studied. The operation condition of distribution network with different access position and load is different, and the improved Newton-Raphson method is used to calculate the power flow by introducing the improvement index of voltage loss. The influence of distributed wind power on the network voltage loss is analyzed. Through the simulation of IEEE33 node system, the measured wind power output and load data are used. This paper analyzes the influence of wind power access on the system under various conditions and provides a useful reference for decentralized wind power access to the power network. (3) considering the influence of decentralized wind power access to the power network, the related control strategies are formulated: daily reactive power optimal control and short-time reactive power optimization control, taking into account the switching times of switching capacitor banks. Moreover, the reactive power can not be adjusted continuously. The optimal strategy of daily reactive power is formulated. The optimal decision variables are the switching time and capacity of the capacitor bank, and the total active power network loss 24 hours a day is taken as the objective function. According to the rapid and continuous regulation of reactive power of SVC/SVG and wind turbine, the short-time reactive power optimization strategy is formulated, and the optimal decision variable is the reactive power of SVC/SVG and wind power unit. The minimum voltage offset rating of the whole network node is chosen as the objective function, and the feasibility of the optimization strategy is verified by the simulation of the actual power network model.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM761.12

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