發(fā)布時間：2018-05-28 03:14

  本文選題：風(fēng)電場 + 機(jī)組優(yōu)化調(diào)度　； 參考：《重慶大學(xué)》2014年碩士論文

【摘要】：隨著全球范圍內(nèi)能源需求的增長和環(huán)境問題的日益突出，風(fēng)能作為可再生能源中最具經(jīng)濟(jì)發(fā)展前景的清潔能源，逐漸受到世界各國的重視和青睞，風(fēng)電并網(wǎng)容量逐年增加。但是，與常規(guī)發(fā)電機(jī)組不同，由于風(fēng)電功率具有隨機(jī)性和波動性，大規(guī)模風(fēng)電的接入必然會給電力系統(tǒng)機(jī)組的優(yōu)化調(diào)度和運行帶來一系列的挑戰(zhàn)和要求。因此，合理制定含風(fēng)電場電力系統(tǒng)的機(jī)組調(diào)度計劃對于提高風(fēng)電的利用率具有重要意義。本文圍繞含風(fēng)電場電力系統(tǒng)的機(jī)組優(yōu)化調(diào)度問題，開展了如下的研究工作： 計及負(fù)荷和風(fēng)電功率的不確定性，結(jié)合拉丁超立方抽樣和場景技術(shù)分析了負(fù)荷和風(fēng)電功率的聯(lián)合多時段場景模型。針對風(fēng)電功率預(yù)測誤差缺乏統(tǒng)一的概率分布模型，通過建立風(fēng)電功率預(yù)測誤差的經(jīng)驗分布函數(shù)，結(jié)合樣條插值法建立了風(fēng)電功率預(yù)測誤差總體分布函數(shù)的解析表達(dá)式，并采用拉丁超立方技術(shù)對負(fù)荷和風(fēng)電功率的預(yù)測誤差進(jìn)行抽樣，，結(jié)合場景削減技術(shù)分析了負(fù)荷和風(fēng)電功率了負(fù)荷和風(fēng)電功率的聯(lián)合多時段場景模型。算例分析結(jié)果表明了該方法的可行性和有效性。 計及不同場景間負(fù)荷和風(fēng)電功率的波動性對機(jī)組優(yōu)化調(diào)度的影響，以所有場景下發(fā)電成本的期望值和方差的加權(quán)和為目標(biāo)函數(shù)，建立了綜合考慮負(fù)荷及風(fēng)電功率不確定性影響的機(jī)組優(yōu)化調(diào)度模型，并采用改進(jìn)的粒子群優(yōu)化算法對模型進(jìn)行求解。針對負(fù)荷和風(fēng)電功率的不確定性影響，基于不同場景之間負(fù)荷和風(fēng)電功率的極限波動區(qū)間確定系統(tǒng)的正負(fù)旋轉(zhuǎn)備用需求。為提高算法迭代過程中的收斂性能，提出以種群最優(yōu)值為引導(dǎo)動態(tài)調(diào)整機(jī)組的出力范圍。以某典型10機(jī)測試系統(tǒng)為例進(jìn)行算例分析，驗證了所提模型和算法的正確性和有效性。 考慮到機(jī)組優(yōu)化調(diào)度與環(huán)境成本、負(fù)荷預(yù)測誤差以及風(fēng)電滲透率等參數(shù)密切相關(guān)，為分析這些參數(shù)變化對機(jī)組優(yōu)化調(diào)度的影響，給出了含風(fēng)電場電力系統(tǒng)機(jī)組優(yōu)化調(diào)度的算例仿真分析。算例分析結(jié)果表明：環(huán)境成本對機(jī)組調(diào)度的發(fā)電成本影響不大，但對機(jī)組調(diào)度的環(huán)境效益影響顯著；負(fù)荷預(yù)測誤差和風(fēng)電滲透率對機(jī)組調(diào)度的發(fā)電成本影響較大。
[Abstract]:With the increase of global energy demand and the increasingly prominent environmental problems, wind energy, as the most promising clean energy in renewable energy, has been paid more and more attention and favor in the world, and the wind power grid capacity is increasing year by year. However, unlike conventional generators, because of the randomness and volatility of wind power, large-scale wind power access will inevitably bring a series of challenges and requirements to the optimal scheduling and operation of power system units. Therefore, it is of great significance to make the dispatching plan of wind farm power system reasonably for improving the utilization ratio of wind power. In this paper, the following research work is carried out on the optimal dispatching of units with wind farm power system: Considering the uncertainty of load and wind power, combined with Latin hypercube sampling and scenario technology, the combined multi-period scenario model of load and wind power is analyzed. In view of the lack of a unified probability distribution model for wind power prediction error, an analytical expression of wind power prediction error overall distribution function is established by establishing the empirical distribution function of wind power prediction error and combining spline interpolation method. The prediction error of load and wind power is sampled by using Latin hypercube technique, and the combined multi-period scenario model of load and wind power is analyzed with scene reduction technology. The results of an example show that the method is feasible and effective. Considering the effect of fluctuation of load and wind power between different scenarios on the optimal scheduling of generating units, the weighted sum of expected value and variance of generation cost in all scenarios is taken as the objective function. An optimal scheduling model considering the uncertainty of load and wind power is established, and the improved particle swarm optimization algorithm is used to solve the model. According to the uncertainty of load and wind power, the requirement of positive and negative rotation reserve is determined based on the limit fluctuation range of load and wind power between different scenarios. In order to improve the convergence performance of the iterative algorithm, the optimal population value is proposed to guide the dynamic adjustment of the generating range. Taking a typical 10-machine test system as an example, the correctness and validity of the proposed model and algorithm are verified. Considering that the optimal scheduling of the unit is closely related to the environmental cost, load forecasting error and wind power permeability, the influence of these parameters on the optimal scheduling of the unit is analyzed. An example of optimal dispatching of power system units with wind farm is presented. The result of example analysis shows that the environmental cost has little effect on the generation cost of unit dispatching, but it has a significant effect on the environmental benefit of unit dispatching, and the load forecasting error and wind power permeability have great influence on the generation cost of unit dispatching.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM614;TM73

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本文編號：1945012