本文選題：風(fēng)電廠　切入點(diǎn)：動(dòng)態(tài)經(jīng)濟(jì)調(diào)度　出處：《南京大學(xué)》2013年碩士論文

【摘要】：由于風(fēng)的間歇性和隨機(jī)性,大規(guī)模風(fēng)電廠內(nèi)部的調(diào)度規(guī)劃面臨著一些困境。風(fēng)電廠的調(diào)度規(guī)劃的根本目的是在滿足電網(wǎng)需求的同時(shí),盡可能地最小化風(fēng)電廠運(yùn)營(yíng)的總成本,并且保證電網(wǎng)的運(yùn)行安全。本研究針對(duì)這個(gè)問(wèn)題提出了一個(gè)動(dòng)態(tài)經(jīng)濟(jì)調(diào)度模型和相應(yīng)的解決方法。此次研究的目標(biāo)函數(shù)是風(fēng)電廠的運(yùn)營(yíng)總成本,其中包括電力短缺成本、風(fēng)機(jī)運(yùn)維成本和風(fēng)機(jī)啟動(dòng)成本。為了求解文中提出的調(diào)度規(guī)劃模型,本文應(yīng)用了PSSWO算法,這是一種將傳統(tǒng)的粒子群優(yōu)化(PSO)算法與小世界網(wǎng)絡(luò)結(jié)構(gòu)相結(jié)合的強(qiáng)化算法。此外,本文還引入了一種溝通機(jī)制來(lái)進(jìn)行半封閉群落之間的信息交換,以達(dá)到探索和利用之間的平衡。 之后,本研究設(shè)計(jì)了兩個(gè)仿真實(shí)驗(yàn)來(lái)驗(yàn)證和分析由模型產(chǎn)生的優(yōu)化調(diào)度規(guī)劃方案。為了評(píng)估優(yōu)化方案的效果,設(shè)定了一個(gè)基準(zhǔn)規(guī)劃方案,用總成本收益比來(lái)說(shuō)明經(jīng)過(guò)優(yōu)化后的方案優(yōu)于基準(zhǔn)規(guī)劃方案的程度。實(shí)驗(yàn)結(jié)果表明,通過(guò)模型計(jì)算得到的優(yōu)化調(diào)度規(guī)劃方案的表現(xiàn)要優(yōu)于基準(zhǔn)規(guī)劃方案。通過(guò)分析優(yōu)化后的規(guī)劃方案,可以看出,并不是所有高功率的風(fēng)機(jī)都一直處于運(yùn)行狀態(tài)就能滿足風(fēng)電廠運(yùn)營(yíng)的要求,這是因?yàn)榭偝杀镜娜齻�(gè)組成部分之間存在著一種微妙的平衡,必須對(duì)風(fēng)機(jī)的啟停有所判斷,才能達(dá)到總成本最小化的目的。 最后,本文根據(jù)澳大利亞—新西蘭風(fēng)險(xiǎn)管理標(biāo)準(zhǔn)AS/NZS4360提出的標(biāo)準(zhǔn)過(guò)程,從風(fēng)險(xiǎn)的識(shí)別、分析、評(píng)估、控制、監(jiān)控和反饋等方面提出了一系列管理策略和措施,為未來(lái)的風(fēng)電廠調(diào)度規(guī)劃和風(fēng)險(xiǎn)管理提供有益的啟示。
[Abstract]:Due to the intermittent and randomness of wind, the internal scheduling planning of large-scale wind power plants faces some difficulties. The fundamental purpose of the scheduling planning of wind power plants is to minimize the total operating cost of wind power plants while satisfying the demand of the power network. In order to solve this problem, a dynamic economic dispatching model and corresponding solutions are proposed. The objective function of this study is the total operating cost of wind power plant, including the cost of power shortage. In order to solve the scheduling planning model proposed in this paper, the PSSWO algorithm is applied, which combines the traditional particle swarm optimization (PSO) algorithm with the small-world network structure. This paper also introduces a communication mechanism to exchange information between semi-closed communities in order to achieve a balance between exploration and utilization. Then, two simulation experiments are designed to verify and analyze the optimal scheduling scheme generated by the model. In order to evaluate the effect of the optimization scheme, a benchmark planning scheme is set up. The degree to which the optimized scheme is superior to the baseline planning scheme is illustrated by the total cost-benefit ratio. The experimental results show that, The performance of the optimal scheduling plan obtained by the model calculation is better than that of the benchmark planning scheme. Through the analysis of the optimized planning scheme, it can be seen that, Not all high-power fans can meet the operational requirements of wind power plants if they are always in operation. This is because there is a delicate balance between the three components of the total cost, and it is necessary to judge the starting and stopping of the fans. In order to achieve the goal of minimizing the total cost. Finally, according to the standard process proposed by Australia New Zealand risk Management Standard (AS/NZS4360), this paper puts forward a series of management strategies and measures from the aspects of risk identification, analysis, evaluation, control, monitoring and feedback. For the future wind power plant scheduling planning and risk management to provide useful inspiration.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F272.3;F426.61

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