發(fā)布時間：2018-01-29 13:48

  本文關(guān)鍵詞： 光伏微電網(wǎng) 光伏預(yù)測 經(jīng)濟調(diào)度 小樣本 多時段優(yōu)化　出處：《浙江大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著社會經(jīng)濟的發(fā)展,能源短缺和環(huán)境污染問題日益突出,開發(fā)與利用可再生能源已成為解決能源和環(huán)境問題的重要途徑。微電網(wǎng)作為分布式可再生能源友好接入大電網(wǎng)的一種方式,引起了廣泛的關(guān)注。本文以光伏微電網(wǎng)為研究對象,圍繞其發(fā)電預(yù)測與經(jīng)濟運行問題展開研究,研究工作主要包括:1)分析光伏微電網(wǎng)特性,包括微電網(wǎng)結(jié)構(gòu)特性與各元件特性。重點闡述光伏發(fā)電系統(tǒng)的發(fā)電原理與輸出功率特性、光伏微電網(wǎng)主要元件的數(shù)學(xué)模型,為光伏微電網(wǎng)發(fā)電預(yù)測方法研究與經(jīng)濟運行問題研究提供研究基礎(chǔ)。2)研究光伏發(fā)電預(yù)測問題。針對投運初期的光伏電站歷史數(shù)據(jù)不足的問題,提出一種對樣本量需求較少的神經(jīng)網(wǎng)絡(luò)光伏預(yù)測方法。根據(jù)光伏發(fā)電各環(huán)節(jié)影響因素的解耦特性,利用改進的雙層神經(jīng)網(wǎng)絡(luò)模型進行未來一天內(nèi)的光伏輸出功率預(yù)測,實現(xiàn)在較少樣本量下,對神經(jīng)網(wǎng)絡(luò)預(yù)測模型的有效訓(xùn)練�；趯嶋H數(shù)據(jù),驗證了所提出的光伏預(yù)測方法在小樣本條件下的有效性。3)研究光伏微電網(wǎng)并網(wǎng)經(jīng)濟運行問題。綜合考慮光伏發(fā)電超短期、短期預(yù)測技術(shù)的特點與微電網(wǎng)經(jīng)濟運行問題的需求,提出一種混合時長多時段滾動優(yōu)化方法。在日前調(diào)度層的優(yōu)化模型中,通過前密后疏的時段劃分,有效利用光伏發(fā)電預(yù)測數(shù)據(jù)的時間粒度與預(yù)測精度特點,為實時調(diào)度層提供可靠的運行計劃,從而保證了系統(tǒng)運行的經(jīng)濟性和安全性。與此同時,所提出的混合時長多時段滾動優(yōu)化方法減少了日前調(diào)度層優(yōu)化模型的變量數(shù)量,減少了問題求解的計算耗時。
[Abstract]:With the development of social economy, energy shortage and environmental pollution problems have become increasingly prominent, the development and utilization of renewable energy has become an important way to solve the problem of energy and environment. The micro grid as a distributed renewable energy friendly grid, has attracted wide attention. In this paper, photovoltaic micro grid as research object, focuses on the research of the power of prediction and economic operation problem, the main work includes: 1) analysis of photovoltaic micro grid characteristics, including the structure characteristics of micro grid and characteristics of each component. Focuses on the principle of power generation and power output characteristics of photovoltaic power generation system, the mathematical model of the main components of photovoltaic micro grid, photovoltaic micro grid power generation prediction method study and research the economic operation provides research foundation for the study of photovoltaic power generation.2) prediction. According to the historical data of the initial operation stage of the photovoltaic power station provided problems. A prediction method for the small sample of demand of the neural network. According to the photovoltaic PV power decoupling characteristics of each link factors, for the PV output power in the next day's forecast by the double improved neural network model, achieved with less sample size, effective prediction model of neural network training. Based on the actual data. Verify the PV prediction effectiveness of the proposed method in.3 under the condition of small sample) of photovoltaic micro grid economic operation problem. Considering the characteristics of photovoltaic power generation of ultra short term, short-term forecasting technology and micro grid economic operation problem, this paper proposes a hybrid optimization method of multi period length of rolling optimization model in Japan. Before scheduling layer, the density after thinning of the time division, the effective use of photovoltaic power generation forecast data and prediction accuracy of time granularity characteristics, to provide reliable real-time scheduling layer The operation plan, so as to ensure the safety and economy of system operation. At the same time, the proposed hybrid long time rolling optimization method to reduce the number of variables of the optimization model for day ahead scheduling layer, reduce the computation time of problem solving.

【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM615

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本文編號：1473555