基于GHO和HHO的部分遮阳条件下的光伏系统最大功率点跟踪算法研究

发布时间：2021-11-04 16:39

　　全球变暖的加剧、化石燃料的枯竭以及成本效益高的制造技术的进步,使可再生能源成为一种可靠的能源。燃料电池、地热、风能、水力、生物质量和太阳能是领先的可再生能源。其中最有希望的是太阳能。太阳能利用光伏技术直接转化为电能。太阳能电池板与房屋、汽车、充电站和移动平台、抽水站等的集成在现实世界中提供了广泛的应用。太阳能的主要优点是成本低、可扩展性好、碳足迹小、维护少、机械疲劳小、安装快捷、无噪音、无污染。虽然光伏系统具有广阔的发展前景,但其固有的非线性特性、对运行条件的敏感性、不同的光照强度和温度使得这项任务具有挑战性。部分阴影（PS）会导致可用功率的严重损失。提高光伏系统生产率的最有效途径是引入控制系统,迫使光伏系统在最大功率点上运行。这种技术被称为最大功率点跟踪（MPPT）。MPPT技术被分为许多种类,有自己的优点和缺点。MPPT控制器的优点是MPP的快速跟踪、全局最大值（GM）检测和鲁棒性。本文提出了两种高效的基于生物激励的MPPT控制技术。本研究的主要目的是发展光伏系统的控制策略,以克服现有多点跟踪控制技术的缺点。首先,针对多点跟踪问题,在多点跟踪控制器上实现了一种基于群体智能的蝗虫优化... 

【文章来源】：中国科学技术大学安徽省 211工程院校 985工程院校

【文章页数】：126 页

【学位级别】：硕士

【文章目录】：
摘要
ABSTRACT
List of Abbreviations
Chapter 1. Introduction
    1.1 Energy
        1.1.1 Renewable energy
        1.1.2 The future of renewables
    1.2 Leading renewable energy resources
        1.2.1 Hydroelectric energy
        1.2.2 Wind Power
        1.2.3 Biomass
        1.2.4 Geothermal power
        1.2.5 Solar
        1.2.6 Ocean tidal energy
        1.2.7 Hydrogen and fuel cells
        1.2.8 Thermoelectric generators (TEG)
        1.2.9 Other renewable energy sources
    1.3 Trends in PV technologies and effectiveness
        1.3.1 Global technology trends and prices
        1.3.2 PV cell efficiency
        1.3.3 PV system efficiency
    1.4 Motivation
    1.5 Research Contents
    1.6 Innovation
    1.7 Chapter Layout
Chapter 2. PV System Modeling and Characteristics
    2.1 Mathematical modeling of PV cell
    2.2 PV cell modeling
        2.1.1 Single diode model
        2.1.2 Double diode model
    2.3 PV model characteristics
        2.3.1 Solar Cell I-V Characteristic Curves
        2.3.2 Solar Array series-parallel combination
        2.3.3 PV Parameters description
        2.3.4 Effects of temperature condition
        2.3.5 Effects of Uniform irradiance condition
        2.3.6 Partial shading condition
    2.4 The components of the PV system
        2.4.1 DC converter
            2.4.1.1 Boost converter
            2.4.1.2 Buck converter
            2.4.1.3 Buck-Boost converter
            2.4.1.4 Cuk converter
        2.4.2 MPPT controller
        2.4.3 Inverters
            2.4.3.2 Types of inverters for PV systems
        2.4.4 Load management and grid connectivity
Chapter 3. Soft Computing based MPPT techniques
    3.1. Introduction
        3.1.1 Literature review
        3.1.2 Artificial Neural Networks (ANN)
        3.1.3 Fuzzy logic controller (FLC)
    3.2 The Proposed GHO MPPT
        3.2.1 The mathematical model of GHO
        3.2.2 GHO for MPPT of PV systems
        3.2.3 Tracking mechanism of GHO
        3.2.4 GHO under Complex Partial Shading
        3.2.5 Advantages of GHO on MPPT
    3.3 Results and discussion
        3.3.1 Case 1: Fast varying irradiance
        3.3.2 Case 2 partial shading
        3.3.3 Case 3: Partial shading
        3.3.5 Case 4 Complex partial shading
        3.3.6 Case 5: Complex Partial Shading
        3.3.7 Efficiency and performance evaluation
    3.4 Conclusion
Chapter 4. Swarm Intelligence based MPPT Techniques
    4.1 Some conventional swarm intelligence based MPPT techniques
        4.1.1 Particle swarm optimization (PSO)
        4.1.2 Grey Wolf Optimization (GWO)
        4.1.3 Artificial bee colony (ABC)
        4.1.4 ABC Application for MPPT control
        4.1.5 Cuckoo Search (CS)
            4.1.5.1 Main features and sequence of CS
            4.1.5.2 Cuckoo search for MPPT in PV system
        4.1.6 Adoptive cuckoo search algorithm
    4.2 The proposed HHO based MPPT technique
        4.2.1 The HHO model
        4.2.2 Soft besiege
        4.2.3 Hard besiege
        4.2.4 Soft besiege with progressive rapid dives
        4.2.5 Hard besiege with progressive rapid dives
        4.2.6 Working methodology of HHO
        4.2.7 Advantages of HHO on MPPT
        4.2.8 Case partial shading
        4.2.9 Results of Quantitative and statistical results
    4.3 Case field atmospheric data
        4.3.1 Weather conditions
        4.3.2 Spring results
        4.3.3 Summer results
    4.4 Hardware setup
    4.5 Conclusion
Chapter 5. Conclusion and Future Work
    5.1 Contributions
    5.2 Future Work
References
List of Publications



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