University Of Tasmania
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A Simulated annealing global maximum power point tracking method for photovoltaic systems experiencing non-uniform environmental conditions

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posted on 2023-05-27, 10:26 authored by Sarah LydenSarah Lyden
Photovoltaic (PV) systems have immense potential due to the abundance of available solar energy and the capability of these systems to be implemented in a distributed manner. This clean, renewable and sustainable energy source can provide a solution to concerns about the shortage of fossil fuels, global warming, greenhouse gas emissions and pollution in general. Residential PV systems enable consumers to take control of generating electricity to satisfy their own load requirements and potentially export any excess energy to the distribution grid. Investing in a PV system requires significant initial capital and PV cells have a very limited efficiency. Residential customers who invest in a PV system expect to be able to have the best return on their investment by utilising the power available in the sunlight to the greatest extent possible. The potential power available from such systems can be dramatically reduced due to shading of the modules and ineffective control strategies to overcome the influence of shading. PV cells exhibit a non-linear Power-Voltage (P-V) characteristic leading to a unique point corresponding to optimal operation. This point is referred to as the Maximum Power Point (MPP), and varies depending on the environmental conditions. Typical conditions in a residential environment involve obstacles such as trees, houses and power poles which may cause shading across all or part of the PV system throughout the day. Shading from these obstacles leads to increased non-linearity in the P-V characteristic as multiple maxima can be exhibited. Traditionally, Maximum Power Point Tracking (MPPT) techniques have been developed to track a single maximum on the P-V characteristic based on simple techniques such as hill climbing. These techniques inherently fail when multiple maxima are exhibited under Partial Shading Conditions (PSC). The work documented in this thesis consists of two main parts. In the first part, a study of modelling PV cells and an extensive shading study for an eight-module PV system is conducted. This analysis has led to the classification of partial shading phenomena based on the time scale as either constant, static or transient partial shading, and exploring the effect that each aspect of partial shading has on the relative location of the Global Maximum Power Point (GMPP). The second part comprehensively explores the concept of MPPT and presents a review of techniques proposed in the literature with consideration of their performance under non-uniform environmental conditions. A Global MPPT (GMPPT) method is proposed based on the global optimisation technique of Simulated Annealing (SA) and its performance is verified through simulations and experimental application. The key contributions of this thesis include proposing a shading classification based on the time of influence of the shading and studying how this affects the relative location of the GMPP, development and optimisation of a SA based GMPPT method, and the merging of these results to develop a comprehensive and enhanced GMPPT strategy. The main concerns associated with modelling PV cells and modules are introduced and a model of the BP380 PV module is developed based on the commonly used Single Diode Model (SDM) for PV modules. The SDM provides a good balance between accuracy and simplicity and is shown to model the experimentally measured P-V and Current-Voltage (I-V) characteristics of the BP380 modules with acceptable accuracy. A model is also developed and experimentally validated based on combining two series-connected modules modelled using the SDM to explore PSC. A PV system comprised of eight series-connected PV modules, modelled based on the BP380 PV modules, is developed to explore the influence of PSC. A methodology for calculating the position of the shadow tip and determining which cells are shaded by an object is proposed and used to perform five case studies exploring the effects of constant, static and transient partial shading. Constant partial shading is defined as a mismatch in the potential of the modules in a system based on factors such as manufacturing tolerance, cell degradation and damage over time. This type of shading should remain roughly the same for all time. Static partial shading is considered as shading that moves much slower than the movement of clouds across the sky and represents the shading that occurs on the modules due to the presence of obstacles in the environment. Finally, transient shading is the quickest shading phenomena and is represented by the changing irradiance due to the movement of clouds across the sky. An extensive review of maximum power extraction strategies is presented. Each technique is assessed against key criteria identified as being essential for a universally applicable GMPPT strategy. In particular, the methods are assessed on whether they can locate a global maximum reliably, the method complexity and its ease of application to other PV systems. The analysis suggests that a global maximum power extraction strategy with moderate complexity and limited dependence on system specific parameters is needed. The proposed SA based GMPPT method is introduced in the form of simple studies showing the effectiveness of the method in converging to a GMPP based on a two module PV system, eight module PV system, basic grid connected system and through experimental verification on the two series-connected BP380 PV modules. The key parameters of the SA method are explored in more detail to assess their influence on the effectiveness of the proposed method. The main advantages of the proposed methodology for GMPPT is that it is not significantly more complex than the common perturb and observe (P&O) MPPT technique, yet has far superior performance in converging to the GMPP. Additionally, when compared to the Particle Swarm Optimisation (PSO) method which is commonly used for GMPPT, the SA based method has less complexity yet similar performance in converging to the GMPP. By incorporating understanding of the relative location of the GMPP under different PSC, the technique is enhanced to improve accuracy and convergence time. In residential environments one of the key factors is minimising cost and ensuring maximum effciency. For this reason, a low cost and low complexity MPPT method that can achieve GMPP identification is essential, to enable systems implemented in residential environments to be utilised to the greatest extent possible.


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