【摘要】：風(fēng)力發(fā)電是目前技術(shù)最成熟、最具有成本競(jìng)爭(zhēng)力的可再生能源發(fā)電形式,風(fēng)電大規(guī)模并網(wǎng)緩解了我國(guó)能源壓力并帶來(lái)巨大的經(jīng)濟(jì)和環(huán)境效益。然而風(fēng)電作為間歇性電源,其大規(guī)模并網(wǎng)勢(shì)必增加電力系統(tǒng)運(yùn)行與控制難度,給系統(tǒng)運(yùn)行帶來(lái)風(fēng)險(xiǎn)。準(zhǔn)確地量化風(fēng)電接入所帶來(lái)的影響,優(yōu)化發(fā)電與備用計(jì)劃,制定綜合考慮系統(tǒng)經(jīng)濟(jì)性和安全性的系統(tǒng)調(diào)度策略,成為未來(lái)高比例可再生能源接入電力系統(tǒng)所面臨的重要問(wèn)題。針對(duì)這一問(wèn)題,本文從風(fēng)電功率場(chǎng)景優(yōu)化建模和調(diào)度計(jì)劃優(yōu)化建模兩個(gè)方面進(jìn)行研究。本文將含風(fēng)電電力系統(tǒng)運(yùn)行調(diào)度問(wèn)題與風(fēng)險(xiǎn)理論相結(jié)合,把條件風(fēng)險(xiǎn)價(jià)值(Conditional Value-at-Risk,CVaR)引入系統(tǒng)運(yùn)行風(fēng)險(xiǎn)分析中,更為準(zhǔn)確地反映系統(tǒng)運(yùn)行風(fēng)險(xiǎn)及調(diào)度決策風(fēng)險(xiǎn)態(tài)度對(duì)調(diào)度計(jì)劃制定的影響。主要進(jìn)行了以下研究:(1)提出了考慮風(fēng)電功率波動(dòng)與預(yù)測(cè)誤差條件分布特性的場(chǎng)景生成及場(chǎng)景消減方法。風(fēng)電功率波動(dòng)性與不確定性的準(zhǔn)確量化及建模分析對(duì)系統(tǒng)調(diào)度計(jì)劃的制定至關(guān)重要。本文基于歷史數(shù)據(jù)分析了風(fēng)電功率波動(dòng)與預(yù)測(cè)誤差在不同維度上的條件分布特性。采用考慮時(shí)序相關(guān)性的動(dòng)態(tài)場(chǎng)景生成技術(shù),提出了綜合考慮風(fēng)電功率波動(dòng)特性和預(yù)測(cè)誤差條件分布特性的風(fēng)電功率場(chǎng)景生成方法。針對(duì)常規(guī)聚類消減算法的缺點(diǎn),引入改進(jìn)的K-medoids聚類算法進(jìn)行場(chǎng)景消減,生成能夠準(zhǔn)確反映風(fēng)電功率波動(dòng)性與不確定性的代表性場(chǎng)景。(2)提出了基于概率場(chǎng)景和條件風(fēng)險(xiǎn)價(jià)值的發(fā)電與備用協(xié)調(diào)優(yōu)化模型。代表性場(chǎng)景能夠準(zhǔn)確刻畫(huà)系統(tǒng)的隨機(jī)過(guò)程,以評(píng)估系統(tǒng)的調(diào)節(jié)能力和備用需求。本文利用概率場(chǎng)景的形式描述風(fēng)電功率波動(dòng)性和不確定性,建立了考慮風(fēng)電功率波動(dòng)性及不確定性的發(fā)電與備用協(xié)調(diào)優(yōu)化模型。由于基于期望均值的評(píng)價(jià)方法把不同損失程度的概率場(chǎng)景均一化看待,難以準(zhǔn)確體現(xiàn)系統(tǒng)決策的風(fēng)險(xiǎn)態(tài)度以及所關(guān)注的損失范圍的。為準(zhǔn)確評(píng)價(jià)風(fēng)險(xiǎn)實(shí)現(xiàn)風(fēng)險(xiǎn)管控,將發(fā)電與備用協(xié)調(diào)優(yōu)化問(wèn)題與風(fēng)險(xiǎn)理論相結(jié)合,引入條件風(fēng)險(xiǎn)價(jià)值理論對(duì)棄風(fēng)、失負(fù)荷經(jīng)濟(jì)性損失進(jìn)行風(fēng)險(xiǎn)度量,分析了系統(tǒng)調(diào)度不同風(fēng)險(xiǎn)傾向?qū)Πl(fā)電計(jì)劃與備用分配的影響。(3)引入條件風(fēng)險(xiǎn)價(jià)值理論建立了綜合考慮儲(chǔ)能與需求響應(yīng)的優(yōu)化調(diào)度模型。針對(duì)未來(lái)含高比例風(fēng)電的電力系統(tǒng)僅依靠常規(guī)機(jī)組難以實(shí)現(xiàn)風(fēng)電消納且調(diào)節(jié)成本高的問(wèn)題,本文將儲(chǔ)能和需求響應(yīng)納入到日前發(fā)電調(diào)度模型中。從場(chǎng)景分析的角度建立了考慮儲(chǔ)能調(diào)節(jié)能力的儲(chǔ)能模型和計(jì)及用戶滿意度約束的需求響應(yīng)模型。引入條件風(fēng)險(xiǎn)價(jià)值理論進(jìn)行風(fēng)險(xiǎn)度量,對(duì)比分析了不同調(diào)度模式下不同風(fēng)險(xiǎn)態(tài)度對(duì)系統(tǒng)調(diào)度的影響。算例結(jié)果表明綜合考慮儲(chǔ)能和需求響應(yīng)的調(diào)度模型能夠有效提高風(fēng)電接納水平和系統(tǒng)運(yùn)行經(jīng)濟(jì)性,有效降低極端場(chǎng)景帶來(lái)的風(fēng)險(xiǎn)損失。
[Abstract]:Wind power generation is the most mature and the most competitive renewable energy generation form at present. Wind power large-scale grid connection alleviates the energy pressure and brings huge economic and environmental benefits. However, wind power as an intermittent power supply, its large-scale grid connection is bound to increase the difficulty of power system operation and control, bring risks to the system operation. Accurately quantifying the impact of wind power access, optimizing power generation and standby plans, and formulating system scheduling strategies that take into account the economy and security of the system are important issues facing the future access of high proportion renewable energy sources to power systems. In order to solve this problem, this paper studies wind power scene optimization modeling and scheduling planning optimization modeling. In this paper, the operation scheduling problem of wind power system is combined with the risk theory, and the conditional risk value (Conditional Value-at-Risk,CVaR) is introduced into the system operation risk analysis. It more accurately reflects the impact of system running risk and scheduling decision risk attitude on scheduling planning. The main contributions are as follows: (1) A method of scene generation and scene reduction considering wind power fluctuation and prediction error condition distribution is proposed. Accurate quantification and modeling analysis of wind power fluctuation and uncertainty are very important for system scheduling planning. Based on historical data, the conditional distribution characteristics of wind power fluctuation and prediction error in different dimensions are analyzed in this paper. Based on the dynamic scene generation technique considering the correlation of time series, a method for generating wind power scene is proposed, which takes into account the fluctuation characteristics of wind power and the distribution of prediction error conditions. Aiming at the shortcomings of the conventional clustering subtractive algorithm, an improved K-medoids clustering algorithm is introduced for scene reduction. Representative scenarios which can accurately reflect the volatility and uncertainty of wind power are generated. (2) an optimal model of coordination between generation and reserve based on probabilistic scenarios and conditional risk value is proposed. The representative scene can accurately describe the stochastic process of the system to evaluate the system's adjustment ability and reserve requirement. In this paper, the volatility and uncertainty of wind power are described in the form of probabilistic scenarios, and an optimal model of coordination between generation and reserve is established considering the volatility and uncertainty of wind power. Because the evaluation method based on the expected mean value equalizes the probability scenarios of different loss degrees, it is difficult to accurately reflect the risk attitude of the system decision and the range of loss concerned. In order to accurately evaluate risk and realize risk control, combining the optimization problem of power generation and reserve with the risk theory, the conditional risk value theory is introduced to measure the economic loss of wind and load loss. The influence of different risk propensity of system scheduling on generation plan and reserve allocation is analyzed. (3) the optimal scheduling model considering energy storage and demand response is established by introducing conditional risk value theory. In order to solve the problem that the power system with high proportion of wind power in the future is difficult to achieve wind power absorption and high regulation cost only relying on conventional units, this paper brings the energy storage and demand response into the pre-day generation scheduling model. From the perspective of scenario analysis, the energy storage model considering the capacity of energy storage regulation and the demand response model considering the constraints of user satisfaction are established. The theory of conditional risk value is introduced to measure the risk, and the influence of different risk attitude on system scheduling under different scheduling modes is analyzed. The simulation results show that the scheduling model which takes energy storage and demand response into account can effectively improve the level of wind power acceptance and system operation economy and effectively reduce the risk loss caused by extreme scenarios.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM73

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