【摘要】：分布式電源具有能就地分配電力、節(jié)省輸變電投資和運(yùn)行費(fèi)用、減少集中輸電線路損耗、對(duì)大電網(wǎng)起有力補(bǔ)充和有效支撐的作用等一系列優(yōu)點(diǎn)，，且在眾多分布式電源中，分布式光伏發(fā)電(distributed photovoltaic generation，簡(jiǎn)稱(chēng)DPVG)以其更靈活、更易維護(hù)等優(yōu)點(diǎn)而受到電網(wǎng)的重視。將分布式光伏電源以微網(wǎng)形式接入電網(wǎng)，是發(fā)揮其效能的最佳方式，而儲(chǔ)能技術(shù)與光伏發(fā)電結(jié)合則具有平抑波動(dòng)、提高能效和供電可靠性的作用。因此，由光伏、儲(chǔ)能等分布式能源以及負(fù)荷構(gòu)成的分布式光儲(chǔ)微電網(wǎng)，不僅能夠有效利用分布式光伏電源，更能提高電力系統(tǒng)供電可靠性水平和能源利用率。 為了對(duì)微電網(wǎng)內(nèi)的能源管理進(jìn)行優(yōu)化，針對(duì)以微電網(wǎng)為研究主體的調(diào)度策略的研究成為熱點(diǎn)。根據(jù)優(yōu)化目標(biāo)的不同，調(diào)度策略大致分為兩種：以提升微網(wǎng)內(nèi)分布式能源利用效率為目標(biāo)的固定策略和以在滿足負(fù)荷需求的基礎(chǔ)上盡可能提升微網(wǎng)運(yùn)行經(jīng)濟(jì)效益為目標(biāo)的經(jīng)濟(jì)調(diào)度策略。不管采用怎樣的微網(wǎng)調(diào)度策略，一旦調(diào)度策略制定后，保證光儲(chǔ)微電網(wǎng)能夠按照制定的調(diào)度策略進(jìn)行調(diào)控就變得很重要。因此，本文對(duì)光儲(chǔ)微電網(wǎng)系統(tǒng)的調(diào)控技術(shù)展開(kāi)研究，旨在為進(jìn)一步提升微網(wǎng)內(nèi)能源管理水平提供參考。本文主要工作如下： 1、以某智能微電網(wǎng)實(shí)驗(yàn)室研究平臺(tái)為原型，建立了光儲(chǔ)微電網(wǎng)系統(tǒng)各組成部分模型。其中，光伏陣列的建模采用工程簡(jiǎn)化模型；儲(chǔ)能采用KiBaM模型的蓄電池；變流器則是從主電路拓?fù)浣Y(jié)構(gòu)入手建立了其在dq同步旋轉(zhuǎn)坐標(biāo)下的模型；控制系統(tǒng)的建模包括最大功率點(diǎn)跟蹤控制、蓄電池充放電控制和逆變器功率因數(shù)控制。 2、以某智能微電網(wǎng)實(shí)驗(yàn)室中的光伏發(fā)電系統(tǒng)為研究對(duì)象，建立了基于改進(jìn)BP神經(jīng)網(wǎng)絡(luò)的發(fā)電功率短期預(yù)測(cè)模型。模型以改進(jìn)BP神經(jīng)網(wǎng)絡(luò)為預(yù)測(cè)方法，將相似日歷史發(fā)電序列、氣象信息以及預(yù)測(cè)日的氣象預(yù)報(bào)信息作為輸入來(lái)預(yù)測(cè)發(fā)電功率。 3、對(duì)在不同調(diào)度策略下的光儲(chǔ)微電網(wǎng)系統(tǒng)調(diào)控進(jìn)行仿真研究。在光儲(chǔ)微電網(wǎng)系統(tǒng)各組成部分模型的基礎(chǔ)上搭建了光儲(chǔ)微電網(wǎng)系統(tǒng)仿真模型，并對(duì)光儲(chǔ)微電網(wǎng)系統(tǒng)在兩種不同調(diào)度策略下的調(diào)控了進(jìn)行仿真研究。一種是以提升分布式光伏的能源利用效率為目標(biāo)的固定策略，另一種是考慮峰谷電價(jià)和光伏發(fā)電功率預(yù)測(cè)的經(jīng)濟(jì)調(diào)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.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TM615

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