基于电压闭环控制和模糊控制的MPPT算法研究与硬件实现

发布时间：2018-03-05 05:01

本文选题：电压闭环控制　切入点：模糊控制　出处：《西南交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：光伏发电是将太阳能转化为电能的主要技术之一。独立光伏系统主要由太阳能电池、DC/DC变换电路、系统控制器及其负载组成。受到灰尘遮挡、温度变化以及天气突变等不可预知的环境因素影响,光伏阵列会出现局部阴影的情况,在局部阴影情景下会导致光伏阵列各部分工作在不同的状态,使光伏阵列的P-V特性曲线会呈现多个峰值的情况。为了解决在局部阴影情况下常用最大功率跟踪(MPPT)算法追踪时间长、易陷入局部最优,以及粒子群算法在追踪过程中产生过冲等问题,本文重点提出了一种基于电压闭环控制和模糊控制的MPPT算法,该算法不仅有效解决了常规算法陷入局部最优值和粒子群算法在追踪过程中产生的过冲问题,而且较常见的全局扫描算法提高了 MPPT的收敛速度。论文首先对光伏MPPT控制器的研究现状进行了分析。在理想的外部情景下模拟了三种不同光照温度下光伏电池的输出。采用光伏电池3×3串并连(SP)方式搭建了光伏阵列,并且在光伏阵列局部阴影情景下模拟其输出特性。分析了 DC/DC升压电路在电流连续和断续模式下的工作原理,以及升压电路器件的选型和参数计算。其次利用Simulink搭建了基于Boost电路独立光伏控制系统的仿真模型。在光伏电池理想情景下仿真验证了常用MPPT算法,如扰动观察法、电导增量法、模糊算法以及粒子群算法。并参考文献[43],实现了粒子群优化模糊控制MPPT算法。分析了在光伏阵列局部阴影情景下常用MPPT算法的局限性。然后在光伏阵列局部阴影情景下仿真实现了基于电压闭环控制和模糊控制的MPPT算法。通过Matlab仿真验证了电压闭环控制的电压追踪效果,并且对比分析了本文算法与基于电压闭环控制和扰动观察法的MPPT算法以及粒子群算法的优点。最后在光伏模拟器的基础上搭建了以DSP为核心光伏控制系统的硬件平台,并在硬件平台上实现了基于电压闭环控制和模糊控制MPPT算法以及粒子群算法,验证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.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM615;TP273

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