發(fā)布時間：2018-03-08 08:46

  本文選題：微網(wǎng)　切入點：容量優(yōu)化配置　出處：《北京交通大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著風力發(fā)電和光伏發(fā)電等可再生能源在電網(wǎng)中滲透率的不斷提升,電動汽車充電負荷的大量接入,電網(wǎng)的安全穩(wěn)定運行將面臨又一次挑戰(zhàn)。風能、太陽能發(fā)電的隨機波動性和電動汽車充電負荷的隨機性,將對電網(wǎng)形成巨大沖擊,微網(wǎng)作為平抑電網(wǎng)波動、消納清潔能源的一種重要方式,對傳統(tǒng)電網(wǎng)向清潔能源轉(zhuǎn)型具有重要意義。微網(wǎng)的容量優(yōu)化配置作為系統(tǒng)前期規(guī)劃階段的重要一環(huán),是保證系統(tǒng)供電可靠性和運行經(jīng)濟性的重要前提;采用運行優(yōu)化調(diào)度策略對于提高系統(tǒng)的穩(wěn)定運行與合理制訂微網(wǎng)調(diào)度計劃有著重要影響。本文針對含電動汽車的微網(wǎng)中風光儲容量配置和優(yōu)化調(diào)度策略進行了研究,主要研究內(nèi)容如下:(1)采用依據(jù)季節(jié)性變化的隨機抽樣方法,基于北京地區(qū)的實際氣象數(shù)據(jù)建立了微網(wǎng)中風力發(fā)電和光伏發(fā)電功率模型,對常規(guī)負荷和電動汽車充電負荷功率曲線進行了建模,為微網(wǎng)中風光儲容量的優(yōu)化配置和微網(wǎng)運行調(diào)度策略研究奠定了基礎(chǔ)。(2)針對含有電動汽車的風光儲微網(wǎng),提出了基于改進差分進化算法的容量優(yōu)化配置計算方法。首先通過考慮氣象數(shù)據(jù)的季節(jié)性變化,對輸入數(shù)據(jù)進行擬合,以風光-負荷偏差率、儲能投資成本、風光投資成本、從電網(wǎng)購電費用等作為優(yōu)化目標,以儲能電池充放電約束、并網(wǎng)點功率波動率約束等作為約束條件,建立了微網(wǎng)風、光、儲容量優(yōu)化配置模型,并給出了在兩種不同負荷類型應(yīng)用場景下的容量配置方案,驗證了所提方法的靈活性和有效性。(3)對含電動汽車的風光儲微網(wǎng)日前調(diào)度策略進行了研究,以削峰填谷和減小系統(tǒng)功率波動為目標進行優(yōu)化,并在負荷類型為居民負荷的微網(wǎng)模型中進行了仿真驗證,結(jié)果表明在滿足用戶側(cè)電動汽車充電需求的基礎(chǔ)上,通過日前調(diào)度策略優(yōu)化可以實現(xiàn)網(wǎng)側(cè)減小負荷峰谷差的需求。(4)提出了基于濾波系數(shù)自適應(yīng)的低通濾波算法的實時調(diào)度策略,并與定濾波系數(shù)的低通濾波算法進行了對比分析,仿真結(jié)果表明:在實時調(diào)度策略的優(yōu)化下,可以跟蹤日前調(diào)度計劃并平抑風光發(fā)電的隨機性波動,驗證了所提方法的有效性。
[Abstract]:With the increasing permeability of renewable energy, such as wind power generation and photovoltaic power generation, and the massive access of electric vehicle charging load, the safe and stable operation of the power grid will face another challenge. The random fluctuation of solar power generation and the randomness of charging load of electric vehicles will have a huge impact on the power grid. Microgrid is an important way to calm the fluctuation of power grid and absorb clean energy. It is of great significance for the transformation of traditional power grid to clean energy. As an important part of the early planning stage of the system, the optimal configuration of the capacity of the microgrid is an important prerequisite to ensure the reliability of the power supply and the operation economy of the system. It is very important to adopt the optimal scheduling strategy to improve the stable operation of the system and to make the scheduling plan of microgrid reasonably. This paper studies the configuration of the wind-storage capacity and the optimal scheduling strategy of the micro-grid with electric vehicles. The main research contents are as follows: (1) based on the actual meteorological data in Beijing, the power models of wind power generation and photovoltaic power generation in the microgrid are established by using the random sampling method based on seasonal variation. In this paper, the power curve of conventional load and electric vehicle charging load is modeled, which lays a foundation for the optimal configuration of wind storage capacity in microgrid and the study of micro-grid operation scheduling strategy. Based on the improved differential evolution algorithm, a capacity optimal allocation method is proposed. Firstly, the input data are fitted by considering the seasonal variation of meteorological data, and then the wind-load deviation rate, the investment cost of energy storage and the cost of wind investment are calculated. The optimal configuration model of wind, light and storage capacity of microgrid is established by taking the charge and discharge constraints of energy storage cells and the network power fluctuation constraints as the optimization objectives from the power purchase cost of the power grid. The capacity configuration scheme under two different load application scenarios is given, and the flexibility and effectiveness of the proposed method are verified. The pre-day scheduling strategy of the solar microgrid with electric vehicles is studied. With the aim of cutting peak and filling valley and reducing the power fluctuation of the system, the simulation is carried out in the micro-grid model with load type as the resident load. The results show that, on the basis of satisfying the charging demand of the electric vehicle on the user side, the simulation results show that, By optimizing the scheduling strategy before day, the demand of reducing load peak and valley difference on network side can be realized. (4) A real-time scheduling strategy based on filter coefficient adaptive low-pass filtering algorithm is proposed, and compared with low-pass filtering algorithm with fixed filtering coefficient. The simulation results show that under the optimization of real-time scheduling strategy, the scheduling plan before the day can be tracked and the random fluctuation of wind power generation can be stabilized. The effectiveness of the proposed method is verified.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM727;TM73

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