Dissertation > Excellent graduate degree dissertation topics show

Research on Maximum Power Point Tracking Algorithm of Grid-connected PV

Author: ZhaoMin
Tutor: DuanQiChang
School: Chongqing University
Course: Control Theory and Control Engineering
Keywords: Grid-connected PV RBF Neural Network Particle Swarm Optimization Maximum Power Point Tracking
CLC: TM615
Type: Master's thesis
Year: 2009
Downloads: 1007
Quote: 9
Read: Download Dissertation

Abstract


The development and utilization of renewable energy and various green energy which actualize sustainable development has been becoming the sustainable measures of human beings and the environment. With the development of solar cells and power electronics technology,solar photovoltaic has enjoyed great development, and has become one of the mainstream of new energy source. The PV grid-connected system generally is comprised of the solar panels,the controller pillar,the inverter and the electric fence. Among them, maximum power tracking is the core of the PV power generation systems. The purpose of the maximum power tracking technology is to find the maximum power point of volt-ampere characteristic curve of the output of PV modules, which will improve the output power of PV modules to the utmost extent.When the original control algorithm mutates in the external environment, we can not find the maximum power point quickly and accurately.Therefore, the study of new control algorithms and real-time adjustment of the maximum power output will be propitious to improve the efficiency photovoltaic power generation.In order to adminstrate the photovoltaic solar power array more effectually and enhance the reliability and utility ratio of the electric power., the paper interposes how to use the particle swarm optimization to optimize RBF neural network ,apply it to the new method of maximum power tracking .The method tracks the chang of sunshine steadily and apace,and makes photovoltaic devices work stability in the proximity of the maximum power point .The main contents:Introducting the RBF neural network and the basic theory of PSO, ameliorating their limitations ,interposing the method of how to use HPSO overall to optimizes RBF neural network,using the simulation and analysis of numerical experiments to verify the performance of the proposed method;According to the PV array module of the mathematical model,the paper rearchs the related features of the PV array module in theory,establishs simulation model which simulates photovoltaic array module and the output characteristics of sunlight intensity under different solar cell output and different temperature, compares the measured data with the simulation results, verifies the correctness of the simulation model, lays the foundation for follow-up simulation;The article exposites the working principle and control strategy of the photovoltaic grid-connected. The entire control system sets up for dual-loop control, the outer loop is a voltage control ,which controls the maximum power point reference voltage that is offered by the output voltage of photovoltaic array maximum power point tracking control algorithm; The inner loop is a current control loop, which mates the inverter output current with the reference current .Buiding the photovoltaic system simulation model based on the chang of synchronous rotating frame,which combines the photovoltaic arrays maximum the power tracking with voltage source invertercontralled by current, accomplishing the function of every module through programme,checking the feasibility and effectiveness of the method according to the experimental results.

Related Dissertations

  1. Research on Feature Extraction and Classification of Tongue Shape and Tooth-Marked Tongue in TCM Tongue Diagnosis,TP391.41
  2. Computing Minimum Distance between Curves/Surfaces Based on PSO Algorithm,O182
  3. Active Power Filter and Its Application in Distribution Network,TN713.8
  4. The Grid-Connected Wind-solar Hybrid Generation System and Maximum Power Point Tracking,TM61
  5. Research on Fuzzy C-Mean Clustering Algorithm Based on Particle Swarm Optimization and Shuffled Frog Leaping Algorithm,TP18
  6. Research on Intrusion Detection Based on Feature Selection,TP393.08
  7. Research on the Improvements and Applications of Particle Swarm Optimization,TP18
  8. Study on Risk Identification and Evaluation of Manufacturing Green Products R & D,F205;F224
  9. Segmentation of cDNA Microarray Image Using Fuzzy C-means Algorithm Optimized by Particle Swarm,TP391.41
  10. Research on Photoltaic and Its Key Technology,TM615
  11. Reactive Power Optimization Based on Modified PSO,TP301.6
  12. Study on Electromagnetic Bandgap Structure with Bow-tie Units,TN454
  13. Design of Positive Draw-back Motion of Wool Spinning Frame and Comparison of Prediction Models of Worsted Yarns Performances,TP183
  14. Research of Medical Image Registration Method Based on DTCWT and NPSO,TP391.41
  15. Research on Multi-time Period Production and Procurement Plan of Supply Chain under Uncertainty,F273
  16. Research on the Grid-connected Photovoltaic System Based on Cascaded Multilevel Inverter,TM464
  17. Research and Application of Swarm Intelligence Algorithm,TP301.6
  18. Research on Modification and Application of Particle Swarm Optimization Algorithm Based on Control Methods,TP301.6
  19. Analysis and Extraction of Geodesic Curve in Curved Surface,TH122
  20. Design and Simulation of a Strategy for Backbone Node Deployment in Space Information Networks,TN915.09
  21. Research on WSN Routing Technology with Natural Computation,TN929.5

CLC: > Industrial Technology > Electrotechnical > Power generation, power plants > Variety of power generation > Solar power
© 2012 www.DissertationTopic.Net  Mobile