【摘要】：熱電聯(lián)供微網(wǎng)系統(tǒng)是解決當(dāng)下能源危機(jī)的一項(xiàng)重要技術(shù),高效的能源利用率,種類繁多的分布式單元為聯(lián)供系統(tǒng)的組建提供了多種類的選擇。本文選擇建立基于風(fēng)力-PVT-燃料電池-電解裝置的熱電聯(lián)供微網(wǎng)系統(tǒng),旨在實(shí)現(xiàn)能源的節(jié)約和環(huán)境的保護(hù)。但由于風(fēng)力、光伏發(fā)電因環(huán)境因素帶來(lái)的發(fā)電隨機(jī)性、波動(dòng)性和間歇性的特點(diǎn),以及負(fù)載需求的季節(jié)性和階段性特點(diǎn),使得系統(tǒng)的容量配置成為研究重點(diǎn)。本文就系統(tǒng)20年全壽命周期下,如何優(yōu)化配置各單元容量,在滿足系統(tǒng)熱電負(fù)載需求的同時(shí)最小化系統(tǒng)運(yùn)行成本進(jìn)行研究。主要研究工作圍繞PVT效率優(yōu)化控制和風(fēng)力-PVT-燃料電池?zé)犭娐?lián)供系統(tǒng)容量配比優(yōu)化展開,研究思路如下:首先介紹研究當(dāng)下我國(guó)面臨的能源問(wèn)題和背景,提出基于風(fēng)力、PVT、燃料電池等新能源為基礎(chǔ)的熱電聯(lián)供微網(wǎng)系統(tǒng)是解決當(dāng)下能源問(wèn)題的一種重要手段。其次設(shè)計(jì)PVT熱電聯(lián)供系統(tǒng),對(duì)當(dāng)下已有的PVT系統(tǒng)進(jìn)行優(yōu)化;控制PVT系統(tǒng)水循環(huán)速率達(dá)到最優(yōu)集熱效率,通過(guò)熱力學(xué)第一定律綜合效率來(lái)評(píng)價(jià)系統(tǒng)的綜合效率,通過(guò)對(duì)比獨(dú)立型熱水器系統(tǒng)與PV光伏系統(tǒng)來(lái)評(píng)判系統(tǒng)的優(yōu)點(diǎn)。重點(diǎn)研究熱電聯(lián)供系統(tǒng)最優(yōu)容量配置問(wèn)題,對(duì)熱電聯(lián)供微能系統(tǒng)中的各單元進(jìn)行建模,以NASA氣象數(shù)據(jù)庫(kù)為依據(jù),獲取特定區(qū)域的氣象資料,并對(duì)實(shí)時(shí)風(fēng)力光照資源進(jìn)行分析;提出了以電定熱的運(yùn)行模式,通過(guò)分析風(fēng)力、光伏實(shí)時(shí)發(fā)熱電輸出與熱電負(fù)荷需求的不同,建立供需平衡關(guān)系式;對(duì)系統(tǒng)整體運(yùn)行策略進(jìn)行分析,并由此推導(dǎo)出燃料電池、制氫裝置的容量的計(jì)算公式,以及各分布式單元容量范圍。進(jìn)而建立以最小投資成本為優(yōu)化目標(biāo)的目標(biāo)函數(shù),為接下來(lái)具體算法的選擇和最優(yōu)容量配比的計(jì)算提供依據(jù)。最后通過(guò)對(duì)比各類算法的特點(diǎn),選擇了自適應(yīng)型改進(jìn)型粒子群算法(PSO)作為本文求解最優(yōu)配比的算法。運(yùn)用已建立的目標(biāo)函數(shù)作為優(yōu)化適應(yīng)度函數(shù)來(lái)求解最優(yōu)配比,最后對(duì)最優(yōu)配比下的熱電聯(lián)供系統(tǒng)從成本、實(shí)時(shí)供需狀況、及環(huán)保性等多條件下的可行性分析;并選擇系統(tǒng)某一時(shí)間段運(yùn)行狀況,詳細(xì)分析系統(tǒng)中各單元如何相互配合來(lái)滿足用戶熱電負(fù)載平衡。綜合多個(gè)方面對(duì)系統(tǒng)進(jìn)行了分析和評(píng)估,證明系統(tǒng)的有效性及合理性。
[Abstract]:The microgrid system is an important technology to solve the energy crisis. High efficiency of energy utilization and a wide variety of distributed units provide a variety of options for the construction of the co-supply system. In this paper, a thermoelectric microgrid system based on wind power PVT- fuel cell electrolytic unit is established, which aims to save energy and protect the environment. However, due to wind power, the characteristics of randomness, volatility and intermittence of photovoltaic power generation due to environmental factors, as well as the seasonal and phased characteristics of load demand, the capacity allocation of the system becomes the focus of research. In this paper, we study how to optimize the capacity of each unit in order to meet the requirement of thermoelectric load and minimize the operating cost of the system under the life cycle of 20 years. The main research work is focused on the optimization of PVT efficiency control and the optimization of the capacity ratio of the wind-PVT- fuel cell heat and power system. The research ideas are as follows: firstly, the energy problems and background facing our country are introduced. Based on new energy sources, such as wind power PVT and fuel cell, a thermoelectric microgrid system is proposed as an important means to solve the energy problem. Secondly, the PVT heat and power supply system is designed to optimize the existing PVT system, to control the water cycle rate of the PVT system to achieve the optimal heat collection efficiency, and to evaluate the comprehensive efficiency of the system through the first law of thermodynamics synthesis efficiency. The advantages of the system are evaluated by comparing the independent water heater system with the PV photovoltaic system. This paper focuses on the optimal capacity allocation of the combined heat and power supply system, models each unit in the heat and power supply micro-energy system, obtains the meteorological data of the specific area based on the NASA meteorological database, and analyzes the real-time wind power and illumination resources. By analyzing the difference between the demand of wind power, photovoltaic real-time heating output and thermoelectric load, the relationship between supply and demand is established, and the overall operation strategy of the system is analyzed, and the fuel cell is deduced. The calculation formula of the capacity of hydrogen production unit and the capacity range of each distributed unit. Then the objective function with the minimum investment cost as the optimization objective is established, which provides the basis for the selection of the following specific algorithm and the calculation of the optimal capacity ratio. Finally, the adaptive modified particle swarm optimization (PSO) algorithm is chosen as the algorithm to solve the optimal matching by comparing the characteristics of various algorithms. The established objective function is used as the optimization fitness function to solve the optimal matching. Finally, the feasibility analysis of the heat and power co-supply system under the optimal ratio is made under the conditions of cost, real-time supply and demand, and environmental protection. At the same time, the operation condition of the system is selected, and how the units in the system cooperate with each other to meet the load balance of the users is analyzed in detail. The system is analyzed and evaluated in many aspects, and the validity and rationality of the system are proved.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM727

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本文編號(hào)：2250304