本文選題：風(fēng)力發(fā)電　切入點(diǎn)：儲(chǔ)能容量　出處：《湖北工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：可再生能源中,風(fēng)能是最具有發(fā)展?jié)摿Φ?而發(fā)展風(fēng)能最有效的途徑就是將其轉(zhuǎn)換為電能。受制于風(fēng)能具有波動(dòng)性和不連續(xù)性,風(fēng)電也帶有極大的波動(dòng)性和不連續(xù)性,這一特點(diǎn)是導(dǎo)致風(fēng)電無法大規(guī)模并入電力系統(tǒng)的主要原因,因?yàn)樗鼑?yán)重影響了大電網(wǎng)的穩(wěn)定運(yùn)行。解決這一問題的理想方案是采用風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)的輸出功率配合大電網(wǎng)的調(diào)度計(jì)劃,也就是說,將儲(chǔ)能技術(shù)應(yīng)用于風(fēng)力發(fā)電,利用儲(chǔ)能填平風(fēng)電場(chǎng)輸出電能的功率波動(dòng)。但是如何最優(yōu)化配置儲(chǔ)能系統(tǒng)、如何將儲(chǔ)能系統(tǒng)的輸出功率適應(yīng)規(guī)劃的電網(wǎng)調(diào)度,如何提高電網(wǎng)容納風(fēng)電的能力又是幾項(xiàng)復(fù)雜的大問題。這些問題的解決與否直接關(guān)系著風(fēng)電能否大規(guī)模發(fā)展,因此解決這些問題具有巨大的理論、工程和現(xiàn)實(shí)意義。為風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)的儲(chǔ)能容量能夠被更合理的優(yōu)化配置,使得風(fēng)電儲(chǔ)能聯(lián)合發(fā)電系統(tǒng)能夠穩(wěn)定輸出功率,本文首先詳細(xì)介紹了風(fēng)力發(fā)電系統(tǒng)和儲(chǔ)能系統(tǒng)的模型,并對(duì)風(fēng)力機(jī)、風(fēng)力發(fā)電機(jī)及儲(chǔ)能系統(tǒng)模型的特征做出了總結(jié);然后說明了風(fēng)電場(chǎng)輸出功率的預(yù)測(cè),是影響風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)儲(chǔ)能容量的兩個(gè)關(guān)鍵因素之一,另一個(gè)關(guān)鍵因素是儲(chǔ)能容量優(yōu)化目標(biāo)。為解決這兩個(gè)因素,本文采取持續(xù)預(yù)測(cè)的辦法,通過獲取風(fēng)電場(chǎng)小時(shí)預(yù)測(cè)出力,提出了以棄風(fēng)能量、充放電失去量、運(yùn)營成本的費(fèi)用最少為設(shè)計(jì)目的的儲(chǔ)能系統(tǒng)優(yōu)化模型;在這一模型的基礎(chǔ)上,本文進(jìn)一步提出了風(fēng)電儲(chǔ)能聯(lián)系系統(tǒng)儲(chǔ)能容量優(yōu)化算法,這一算法基于“調(diào)度置信度水平”,也結(jié)合了歷史輸出功率和預(yù)測(cè)調(diào)度計(jì)劃的差值功率分布。該算法也應(yīng)用了兩個(gè)函數(shù),即積累分布函數(shù)和概率分布函數(shù),這兩個(gè)函數(shù)都運(yùn)用了非參數(shù)估計(jì)擬合差值功率。最后,本文以功率型儲(chǔ)能系統(tǒng)作為研究對(duì)象,結(jié)合在上海的某一風(fēng)電場(chǎng)實(shí)地測(cè)試數(shù)據(jù),進(jìn)行了仿真分析。這種風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)容量優(yōu)化的仿真結(jié)果表明,相比傳統(tǒng)的方法,本文所提出的方法能夠使儲(chǔ)能系統(tǒng)的運(yùn)行總費(fèi)用最小,且總費(fèi)用和“調(diào)度置信度水平”成反比例的關(guān)系。考慮到風(fēng)電場(chǎng)的輸出功率的預(yù)測(cè)值與儲(chǔ)能容量優(yōu)化目標(biāo)是影響風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)儲(chǔ)能容量的最關(guān)鍵因素,本文采用“調(diào)度置信度水平”的方法來優(yōu)化風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)儲(chǔ)能容量,它具有儲(chǔ)能系統(tǒng)的費(fèi)用總和與置信度成反比例的規(guī)律,置信度越高,費(fèi)用就越低。因此,本文的研究成果為優(yōu)化配置風(fēng)電儲(chǔ)能聯(lián)合系統(tǒng)儲(chǔ)能容量提供了一種新的途徑。
[Abstract]:Among renewable energy sources, wind energy has the most potential, and the most effective way to develop wind energy is to convert it into electric energy, which is constrained by the volatility and discontinuity of wind energy and the great volatility and discontinuity of wind power. This feature is the main reason why wind power cannot be incorporated into the power system on a large scale. Because it seriously affects the stable operation of large power grid, the ideal solution to this problem is to adopt the output power of wind energy storage joint system to match the dispatching plan of large power grid, that is, to apply energy storage technology to wind power generation. However, how to optimize the configuration of the energy storage system, how to adapt the output power of the energy storage system to the planned power grid scheduling, How to improve the capacity of power grid to hold wind power is also a complex problem. The solution of these problems is directly related to the large-scale development of wind power, so there is a huge theory to solve these problems. Engineering and practical significance. In order to optimize the storage capacity of the combined wind energy storage system, the wind energy storage combined power generation system can output power stably. In this paper, the models of wind power generation system and energy storage system are introduced in detail, and the characteristics of wind turbine, wind turbine and energy storage system are summarized, and the prediction of output power of wind farm is explained. It is one of the two key factors that affect the energy storage capacity of the combined wind power storage system, and the other is the optimization goal of the energy storage capacity. In order to solve these two factors, this paper adopts the method of continuous prediction and obtains the hourly predictive force of the wind farm. In this paper, an optimization model of energy storage system is proposed, which is designed for the purpose of energy dissipation, charge / discharge loss and minimum operating cost, and on the basis of this model, an optimization algorithm for energy storage capacity of wind energy storage associated system is further proposed in this paper. This algorithm is based on the "level of confidence in scheduling" and combines the historical output power with the differential power distribution of the forecast scheduling plan. The algorithm also uses two functions, namely, the cumulative distribution function and the probability distribution function. These two functions use non-parametric estimation to fit the difference power. Finally, the power storage system is taken as the research object, and the field test data of a wind farm in Shanghai are combined. The simulation results show that compared with the traditional method, the proposed method can minimize the total operating cost of the energy storage system. And the total cost is inversely proportional to the "level of confidence in dispatching". Considering that the prediction value of output power of wind farm and the optimization objective of energy storage capacity are the most critical factors affecting the storage capacity of wind power storage combined system, In this paper, the method of "dispatching confidence level" is used to optimize the energy storage capacity of the combined wind energy storage system. It has the rule that the total cost of the energy storage system is inversely proportional to the confidence degree. The higher the confidence level, the lower the cost. The results of this paper provide a new way to optimize the energy storage capacity of wind energy storage system.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM614;TM73

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