本文選題：電壓閉環(huán)控制　切入點：模糊控制　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：光伏發(fā)電是將太陽能轉(zhuǎn)化為電能的主要技術(shù)之一。獨立光伏系統(tǒng)主要由太陽能電池、DC/DC變換電路、系統(tǒng)控制器及其負(fù)載組成。受到灰塵遮擋、溫度變化以及天氣突變等不可預(yù)知的環(huán)境因素影響,光伏陣列會出現(xiàn)局部陰影的情況,在局部陰影情景下會導(dǎo)致光伏陣列各部分工作在不同的狀態(tài),使光伏陣列的P-V特性曲線會呈現(xiàn)多個峰值的情況。為了解決在局部陰影情況下常用最大功率跟蹤(MPPT)算法追蹤時間長、易陷入局部最優(yōu),以及粒子群算法在追蹤過程中產(chǎn)生過沖等問題,本文重點提出了一種基于電壓閉環(huán)控制和模糊控制的MPPT算法,該算法不僅有效解決了常規(guī)算法陷入局部最優(yōu)值和粒子群算法在追蹤過程中產(chǎn)生的過沖問題,而且較常見的全局掃描算法提高了 MPPT的收斂速度。論文首先對光伏MPPT控制器的研究現(xiàn)狀進(jìn)行了分析。在理想的外部情景下模擬了三種不同光照溫度下光伏電池的輸出。采用光伏電池3×3串并連(SP)方式搭建了光伏陣列,并且在光伏陣列局部陰影情景下模擬其輸出特性。分析了 DC/DC升壓電路在電流連續(xù)和斷續(xù)模式下的工作原理,以及升壓電路器件的選型和參數(shù)計算。其次利用Simulink搭建了基于Boost電路獨立光伏控制系統(tǒng)的仿真模型。在光伏電池理想情景下仿真驗證了常用MPPT算法,如擾動觀察法、電導(dǎo)增量法、模糊算法以及粒子群算法。并參考文獻(xiàn)[43],實現(xiàn)了粒子群優(yōu)化模糊控制MPPT算法。分析了在光伏陣列局部陰影情景下常用MPPT算法的局限性。然后在光伏陣列局部陰影情景下仿真實現(xiàn)了基于電壓閉環(huán)控制和模糊控制的MPPT算法。通過Matlab仿真驗證了電壓閉環(huán)控制的電壓追蹤效果,并且對比分析了本文算法與基于電壓閉環(huán)控制和擾動觀察法的MPPT算法以及粒子群算法的優(yōu)點。最后在光伏模擬器的基礎(chǔ)上搭建了以DSP為核心光伏控制系統(tǒng)的硬件平臺,并在硬件平臺上實現(xiàn)了基于電壓閉環(huán)控制和模糊控制MPPT算法以及粒子群算法,驗證了本文算法的可行性。
[Abstract]:Photovoltaic power generation is one of the main technologies to convert solar energy into electric energy. The independent photovoltaic system is mainly composed of DC / DC converter circuit, system controller and its load. Because of the unpredictable environmental factors such as temperature change and weather abrupt change, the photovoltaic array will appear the local shadow, and under the local shadow situation, the various parts of the photovoltaic array will work in different states. The P-V characteristic curve of photovoltaic array will present multiple peaks. In order to solve the problem that the MPPTS algorithm in common use in local shadow cases has long tracking time, it is easy to fall into local optimum. In this paper, a new MPPT algorithm based on voltage closed loop control and fuzzy control is proposed. This algorithm not only effectively solves the problem of local optimal value of conventional algorithm and the overshoot caused by particle swarm optimization algorithm in the process of tracking. Moreover, the convergence rate of MPPT is improved by the common global scanning algorithm. Firstly, the research status of photovoltaic MPPT controller is analyzed in this paper. Three photovoltaic cells with different illumination temperature are simulated in an ideal external scenario. The photovoltaic array is constructed by using the 3 脳 3 series of parallel SPs of photovoltaic cells. The output characteristics of the photovoltaic array are simulated under the local shadow condition. The principle of the DC/DC boost circuit in the continuous and intermittent mode is analyzed. Secondly, the simulation model of independent photovoltaic control system based on Boost circuit is built by using Simulink. The common MPPT algorithm, such as disturbance observation method, is verified by simulation in the ideal situation of photovoltaic cell. Conductance increment method, Fuzzy algorithm and particle swarm optimization (PSO) algorithm are introduced in this paper. With reference to [43], the MPPT algorithm of PSO fuzzy control is implemented. The limitations of MPPT algorithm in local shadow scenarios of photovoltaic array are analyzed. Then, the local shadow of PV array is analyzed. The MPPT algorithm based on voltage closed loop control and fuzzy control is realized by simulation in the scenario. The voltage tracking effect of voltage closed loop control is verified by Matlab simulation. The advantages of this algorithm, the MPPT algorithm based on voltage closed-loop control and disturbance observation method, and the particle swarm optimization algorithm are compared and analyzed. Finally, the hardware platform of photovoltaic control system with DSP as the core is built based on the photovoltaic simulator. The MPPT algorithm and particle swarm optimization algorithm based on voltage closed loop control and fuzzy control are implemented on the hardware platform, and the feasibility of this algorithm is verified.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM615;TP273

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本文編號：1568816