【摘要】：為了改善能源短缺和環(huán)境保護的現(xiàn)狀,適應(yīng)全球能源互聯(lián)網(wǎng)的發(fā)展需求,大力發(fā)展風(fēng)電、光伏等清潔能源已經(jīng)得到各國的普遍認可。然而,風(fēng)電的隨機性、波動性和反調(diào)峰等特點,成為阻礙大規(guī)模風(fēng)電消納的主要原因,同時也給系統(tǒng)的安全穩(wěn)定運行帶來巨大威脅。需求響應(yīng)作為重要的靈活互動響應(yīng)模式,能夠?qū)崿F(xiàn)負荷資源與發(fā)電資源的優(yōu)化調(diào)度,也為提高風(fēng)電并網(wǎng)電量提供了一條重要途徑。論文主要從需求側(cè)和發(fā)電側(cè)兩方面進行考慮,圍繞需求響應(yīng)參與下的風(fēng)電消納策略展開研究,旨在解決風(fēng)電消納問題以及削弱風(fēng)電不確定性給系統(tǒng)安全穩(wěn)定運行帶來的影響。首先提出一種基于遺傳K-means算法的二次聚類方法,通過聚類分析挖掘用戶負荷的需求響應(yīng)潛力,確定需求響應(yīng)的實施對象,分析其實施需求響應(yīng)的可行性和必要性,其中重點研究了空調(diào)負荷的需求響應(yīng)潛力,并將其作為重要的需求側(cè)資源納入到發(fā)電調(diào)度中。在此基礎(chǔ)上,針對需求側(cè)建立需求響應(yīng)優(yōu)化調(diào)度模型,實現(xiàn)對風(fēng)電、火電以及需求側(cè)資源優(yōu)化調(diào)度的收益最大化。通過與傳統(tǒng)機組組合模型進行對比,說明需求響應(yīng)既能實現(xiàn)峰時段用電負荷的削減和轉(zhuǎn)移,使得日負荷曲線更加平緩;還能實現(xiàn)系統(tǒng)備用的合理分配,降低發(fā)電成本,從而提高風(fēng)電并網(wǎng)電量,減少棄風(fēng)現(xiàn)象。而對于發(fā)電側(cè)則實現(xiàn)風(fēng)電的魯棒優(yōu)化,對需求響應(yīng)優(yōu)化調(diào)度模型進行改進,建立魯棒雙層優(yōu)化調(diào)度模型,通過對比說明其主要目的在于為發(fā)電側(cè)和需求側(cè)資源的經(jīng)濟調(diào)度劃定出“經(jīng)濟紅線”,用于檢驗系統(tǒng)實際經(jīng)濟調(diào)度收益的合理性。這樣在保證系統(tǒng)安全穩(wěn)定運行的前提下,提高風(fēng)電消納水平,使得研究更加具有現(xiàn)實意義。
[Abstract]:In order to improve the current situation of energy shortage and environmental protection, adapt to the development of global energy Internet, vigorously develop wind power, photovoltaic and other clean energy has been widely recognized. However, the randomness, volatility and anti-peak-shaving characteristics of wind power are the main reasons that hinder the large-scale wind power consumption, and also bring a great threat to the safe and stable operation of the system. As an important flexible and interactive response mode, demand response can realize the optimal scheduling of load resources and generation resources, and also provide an important way to improve the grid connection of wind power. This paper mainly considers the demand side and the generation side, and studies the strategy of wind power absorption under the participation of demand response, aiming at solving the problem of wind power consumption and weakening the impact of wind power uncertainty on the safe and stable operation of the system. First of all, a quadratic clustering method based on genetic K-means algorithm is proposed. Through clustering analysis, the demand response potential of user load is mined, the implementation object of demand response is determined, and the feasibility and necessity of implementing demand response are analyzed. The demand response potential of air conditioning load is studied, and it is integrated into power generation scheduling as an important demand side resource. On this basis, the demand response optimal scheduling model is established to maximize the benefits of wind power, thermal power and demand-side resource optimization scheduling. By comparing with the traditional unit combination model, it is shown that the demand response can not only reduce and transfer the peak period load, make the daily load curve more smooth, but also realize the reasonable allocation of system reserve and reduce the generation cost. In order to improve the wind power grid power, reduce the phenomenon of wind abandonment. For the generation side, the robust optimization of wind power is realized, the optimal scheduling model of demand response is improved, and the robust bilevel optimal scheduling model is established. The main purpose of this paper is to draw the "economic red line" for the economic dispatch of power generation side and demand side resources, which can be used to check the rationality of the actual economic dispatch income of the system. In order to ensure the safe and stable operation of the system, improve the wind power absorption level, make the research more practical significance.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM73

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