分布式光储微电网系统调控技术研究

发布时间：2018-09-01 05:56

【摘要】：分布式电源具有能就地分配电力、节省输变电投资和运行费用、减少集中输电线路损耗、对大电网起有力补充和有效支撑的作用等一系列优点，，且在众多分布式电源中，分布式光伏发电(distributed photovoltaic generation，简称DPVG)以其更灵活、更易维护等优点而受到电网的重视。将分布式光伏电源以微网形式接入电网，是发挥其效能的最佳方式，而储能技术与光伏发电结合则具有平抑波动、提高能效和供电可靠性的作用。因此，由光伏、储能等分布式能源以及负荷构成的分布式光储微电网，不仅能够有效利用分布式光伏电源，更能提高电力系统供电可靠性水平和能源利用率。为了对微电网内的能源管理进行优化，针对以微电网为研究主体的调度策略的研究成为热点。根据优化目标的不同，调度策略大致分为两种：以提升微网内分布式能源利用效率为目标的固定策略和以在满足负荷需求的基础上尽可能提升微网运行经济效益为目标的经济调度策略。不管采用怎样的微网调度策略，一旦调度策略制定后，保证光储微电网能够按照制定的调度策略进行调控就变得很重要。因此，本文对光储微电网系统的调控技术展开研究，旨在为进一步提升微网内能源管理水平提供参考。本文主要工作如下： 1、以某智能微电网实验室研究平台为原型，建立了光储微电网系统各组成部分模型。其中，光伏阵列的建模采用工程简化模型；储能采用KiBaM模型的蓄电池；变流器则是从主电路拓扑结构入手建立了其在dq同步旋转坐标下的模型；控制系统的建模包括最大功率点跟踪控制、蓄电池充放电控制和逆变器功率因数控制。 2、以某智能微电网实验室中的光伏发电系统为研究对象，建立了基于改进BP神经网络的发电功率短期预测模型。模型以改进BP神经网络为预测方法，将相似日历史发电序列、气象信息以及预测日的气象预报信息作为输入来预测发电功率。 3、对在不同调度策略下的光储微电网系统调控进行仿真研究。在光储微电网系统各组成部分模型的基础上搭建了光储微电网系统仿真模型，并对光储微电网系统在两种不同调度策略下的调控了进行仿真研究。一种是以提升分布式光伏的能源利用效率为目标的固定策略，另一种是考虑峰谷电价和光伏发电功率预测的经济调度策略。
[Abstract]:Distributed generation has a series of advantages, such as local distribution of power, saving investment and operation cost of transmission and transformation, reducing the loss of centralized transmission lines, and playing a complementary and effective supporting role to large power networks, and in many distributed power sources. Distributed photovoltaic (distributed photovoltaic generation, (DPVG) is paid more attention to by power grid because of its more flexibility and easier maintenance. It is the best way to connect the distributed photovoltaic power to the power grid in the form of microgrid, while the combination of energy storage technology and photovoltaic power generation has the function of stabilizing the fluctuation, improving the energy efficiency and the reliability of power supply. Therefore, the distributed optical microgrid, which consists of distributed energy sources such as photovoltaic, energy storage and load, can not only effectively utilize the distributed photovoltaic power, but also improve the power supply reliability and energy utilization efficiency of power system. In order to optimize the energy management in microgrid, the research of dispatching strategy based on microgrid has become a hot topic. Depending on the objectives of the optimization, Scheduling strategies can be divided into two types: a fixed strategy aimed at improving the efficiency of distributed energy utilization in microgrids and an economic scheduling strategy aimed at maximizing the economic benefits of microgrid operation on the basis of satisfying load requirements. No matter what kind of microgrid scheduling strategy is adopted, once the scheduling policy is formulated, it is very important to ensure that the optical storage microgrid can be regulated according to the established scheduling policy. Therefore, the regulation technology of optical microgrid system is studied in this paper, in order to provide a reference for further improving the level of energy management in microgrid. The main work of this paper is as follows: 1. Based on a smart microgrid laboratory research platform, the model of each component of optical microgrid system is established. Among them, the photovoltaic array is modeled by a simplified engineering model, a battery with KiBaM model for energy storage, a converter based on the topology of the main circuit, and a model based on the synchronous rotating coordinates of the dq. The modeling of the control system includes maximum power point tracking control, battery charge and discharge control and inverter power factor control. Based on improved BP neural network, a short-term prediction model of generating power is established. The model uses the improved BP neural network as the prediction method, and uses the similar daily historical generation sequence as the prediction method. The meteorological information and the weather forecast information of the forecasting day are used as input to predict the generation power. 3. The simulation study on the regulation and control of the optical storage and microgrid system under different dispatching strategies is carried out. The simulation model of optical microgrid system is built on the basis of each component model of optical microgrid system, and the simulation research on the regulation and control of optical microgrid system under two different dispatching strategies is carried out. One is a fixed strategy aimed at improving the energy efficiency of distributed photovoltaic, the other is an economic scheduling strategy considering peak and valley price and PV power prediction.
【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】：TM615

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