Optimization approaches for parameter estimation and maximum power point tracking (MPPT) of photovoltaic systems

Optimization approaches for parameter estimation and maximum power point tracking (MPPT) of photovoltaic systems. PhD thesis, University of Liverpool.

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Optimization techniques are widely applied in various engineering areas, such as modeling, identi�cation, optimization, prediction, forecasting and control of complex systems. This thesis presents the novel optimization methods that are used to control Photovoltaic (PV) generation systems. PV power systems are electrical power systems energized by PV modules or cells. This thesis starts with the introduction of PV modeling methods, on which our research is based. Parameter estimation is used to extract the parameters of the PV models characterizing the utilized PV devices. To improve e�ciency and accuracy, we proposed sequential Cuckoo Search (CS) and Parallel Particle Swarm Optimization (PPSO) methods to extract the parameters for di�erent PV electrical models. Simulation results show the CS has a faster convergence rate than the traditional Genetic Algorithm (GA), Pattern Search (PS) and Particle Swarm Optimization (PSO) in sequential processing. The PPSO, with an accurate estimation capability, can reduce at least 50% of the elapsed time for an Intel i7 quad-core processor. A major challenge in the utilization of PV generation is posed by its non linear Current-Voltage (I-V ) relations, which result in the unique Maximum Power Point (MPP) varying with di�erent atmospheric conditions. Maximum Power Point Tracking (MPPT) is a technique employed to gain maximum power available from PV devices. It tracks operating voltage corresponding to the MPP and constrains the operating point at the MPP. A novel model-based two-stage MPPT strategy is proposed in this thesis to combine the o�ine maximum power point estimation using the Weightless Swarm Algorithm (WSA) with an online Adaptive Perturb & Observe (APO) method. In addition, an Approximate Single Diode Model (ASDM) is developed for the fast evaluations of the output power. The feasibility of the proposed method is veri�ed in an MPPT system implemented with a Single-Ended Primary-Inductor Converter (SEPIC). Simulation results show the proposed MPPT method is capable of locating the operating point to the MPP under various environmental conditions.

Item Type: Thesis (PhD)
Additional Information: Date: 2014-08 (completed)
Depositing User: Symplectic Admin
Date Deposited: 09 Feb 2015 11:18
Last Modified: 17 Dec 2022 01:27
URI: https://livrepository.liverpool.ac.uk/id/eprint/2006662