Power electronics architectures and controls for photovoltaic solar energy systems

dc.contributorHaskew, Tim A.
dc.contributorJackson, Jeff
dc.contributorLi, Dawen
dc.contributorFonseca, Daniel J.
dc.contributor.advisorAbu Qahouq, Jaber A.
dc.contributor.authorJiang, Yuncong
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2017-03-01T16:50:13Z
dc.date.available2017-03-01T16:50:13Z
dc.date.issued2013
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractThe increasing demand for clean and renewable energy sources utilization in our daily life has placed more challenging requirements on photovoltaic (PV) solar systems power efficiency, tracking speed, system dynamic response, system cost and size. Researchers have investigated various PV solar system architectures and control methods such as maximum power point tracking (MPPT) techniques to improve PV solar system tracking efficiencies under mismatching and partial shading conditions. Improvements in PV system architectures include the development of module integrated converter (MIC) architecture which performs distributed MPPT at panel-level and the development of sub-MIC architecture which is able to track the optimal operating point of PV cell or group of PV cells inside a PV panel. These two architectures improve the tracking efficiencies of the PV system under various weather and load conditions compared to conventional PV system architectures. However, the MIC and sub-MIC architectures all suffer from some common drawbacks: high cost, large size and high power losses due to the increased number of power components and control circuits. This is mainly because such architectures require larger number of power converters, MPPT controllers, and the related parts such as Analog-to-Digital Converters (ADCs) and other conditioning circuits. The target of this dissertation is to develop control schemes and architectures that will result in reduced cost and size and improved MPPT tracking speed. In order to address tracking speed with reduced sensing, this work develops an adaptive step size and adaptive perturbation frequency MPPT control that utilizes a single sensor, which yields improved tracking speed while maintaining reduced cost and size. Then, in order to reduce the cost and size and improve the efficiency of MIC and sub-MIC architectures, this work develops a two-mode single-sensor MPPT control algorithm for multi-channels PV solar systems that requires only one MPPT controller, one sensor, and one ADC and applies this algorithm to parallel and series PV solar systems configurations. However, while the single sensor MPPT controller reduces the cost and size of control part of the system, it still requires multiple power converters, one for each PV solar channel. Therefore, this work progresses to the next step and develops an architecture that only requires a single power converters with a single power inductor for multiple channels in addition to a single sensor MPPT controller and single ADC. Following the introduction chapter (Chapter 1), this dissertation is organized as follows: Chapter 2 presents a load-current-based MPPT digital controller with adaptive step size and adaptive perturbation frequency algorithm. By utilizing variable step size algorithm, the speed, accuracy and efficiency of the PV system MPPT are improved when compared to the fixed step size load-current-based algorithm. Furthermore, the proposed adaptive algorithm utilizes a novel variable perturbation frequency scheme which further improves the controller speed. Chapter 3 presents a two-mode single-sensor MPPT control algorithm (SS-MPPT) for N-channel PV solar system with parallel MIC PV solar system architecture. The N-channel SS-MPPT controller is able to track the MPP of each PV solar panel, cell, or groups of cells by using only one current sensor. Moreover, a modified SS-MPPT control strategy is proposed in this chapter that is suitable for parallel MIC PV systems that are connected to the grid through current source inverters. Two advanced MPPT algorithms which can be used to realize the SS-MPPT controller are discussed and compared. The SS-MPPT controllers achieve high tracking efficiency and fast dynamic response at reduced cost and size. Chapter 4 presents a cost-effective series-output-connection MPPT (SOC-MPPT) controller for sub-MIC PV system architecture adopting a single sensor at the output and a single digital MPPT controller. The proposed controller and system architecture is able to reduce the number of sensing circuitry, number of required digital controllers in sub-MIC PV system architecture while achieving high tracking efficiencies under mismatching and partial shading conditions. Chapter 5 presents a PV solar system architecture with a single power converter with a single inductor and single MPPT controller that only requires one sensor. This PV solar system architecture is able to perform maximum power point tracking for N-channel PV solar system at panel-level, cell-group-level and single-cell-level. The low-cost, small size and high-efficiency features of the architecture make it effective and attractive. Chapter 6 concludes the work and gives a brief outlook on possible future directions.en_US
dc.format.extent153 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0001348
dc.identifier.otherJiang_alatus_0004D_11655
dc.identifier.urihttps://ir.ua.edu/handle/123456789/1815
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectElectrical engineering
dc.titlePower electronics architectures and controls for photovoltaic solar energy systemsen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Electrical and Computer Engineering
etdms.degree.disciplineElectrical and Computer Engineering
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.
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