Development of Maximum Power Extraction Algorithms for PV system With Non-Uniform Solar Irradiances

This thesis addresses the problem of extraction of maximum power from PV arrays subjected to non-uniform solar irradiances e.g partial shading. In the past, a number of maximum power point tracking algorithms (MPPTs) such as Perturb & Observe, Hill climbing, Incremental Conductance, etc. have been proposed. These are extensively used for obtaining maximum power from a PV module to maximize power yield from PV systems under uniform solar irradiance. However, these techniques have not considered partial shading conditions and the stochastic nature of solar insolation. In the event of non-uniform solar insolation, a number multiple maximum power points (MPPs) appear in the power-voltage characteristic of the PV module. In the present thesis, the stochastic nature of the solar insolation is considered to obtain the global MPP of a PV module with a focus on developing global optimization techniques for MPPT that would handle the multiple MPPs. Thus, the thesis will address the above problem by developing a number of global MPPT algorithms. In this thesis, an extensive review on MPPT algorithms for both uniform and non-uniform insolation levels is presented. Subsequently, an analysis with respect to their merits, demerits and applications have been provided in order to design new MPPTs to achieve higher MPPT efficiency under non-uniform solar irradiances. Firstly, PV modules are modelled with and without bypass diodes for handling Partial shading conditions (PSCs). Then, a new Ring pattern (RP) configuration has been proposed which is compared with different existing configurations such as Series parallel (SP), Total cross tied(TCT) and Bridge linked(BL) configurations on the basis of maximum power and fill factor. As described earlier, under non-uniform irradiances the MPPT problem boil down to determining the global MPP. Thus, the MPPT problem can be cast as a global optimization problem. It may be noted that evolutionary computing approaches are extensively used for obtaining global optimum solutions. One of the most recent evolutionary optimization techniques called grey wolf optimization technique has gained enormous popularity as an efficient global optimization approach. In view of this, Grey wolf optimization is employed to design a global MPPT such that maximum power from PV modules can be extracted which will work under partial shading conditions. Its performance has been compared with two existing MPPTs namely P&O and IPSO based MPPT methods. From the obtained simulation and experimental results, it was found that the GWO based MPPT exhibits superior MPPT performance as compared to both P&O and IPSO MPPTs on the basis of dynamic response, faster convergence to GP and higher tracking efficiency. Further, in order to scale down the search space of GWO which helps to speed up for achieving convergence towards the GP, a fusion of GWO-MPPT with P&O MPPT for obtaining maximum power from a PV system with different possible patterns is developed. An experimental setup of 600W solar simulator is used in the laboratory having characteristics of generating partial shading situation. Firstly, the developed algorithms were implemented for a PV system using MATLAB/SIMULINK. Subsequently, the aforesaid experimental setup is used to implement the proposed global MPPT algorithms. From the obtained simulation and experimental results it is observed that the Hybrid-MPPT converges to the GP with least time enabling highest possible maximum power from the solar PV system. In this thesis, analytical modeling of PV modules for handling non-uniform irradiances is pursued as well as a new RP configuration of PV modules is developed to achieve maximum power and fill factor. In order to extract maximum power from PV panels subjected to non-uniform solar irradiances, two new MPPT algorithms are developed namely Grey wolf optimization based MPPT (GWO-MPPT) and GWO assisted PO (GWO-PO)

Power optimization in partially shaded photovoltaic systems

The Power-Voltage characteristic of a photovoltaic (PV) array exhibits non-linear behaviour when exposed to uniform solar irradiance. Maximum Power Point (MPP) tracking is challenging due to the varying climatic conditions in a solar PV system. Moreover, the tracking algorithm becomes more complicated due to the presence of multiple peaks in the power voltage characteristics under the condition of partial shading. This research is devoted to the Stochastic Beam Search (SBS) based algorithm and Stochastic Hill Climbing (SHC) for a maximum power point tracking (MPPT) at a partial shading condition in the PV system. To give a partial shading effect over the entire array of a PV system, a mast is placed in front of the modules. The modules in the array are connected in such a way that one does not need to rewire the electrical connection during the rearrangement of modules. It is validated that the power generation performance of an array under a moving shading condition is increased. Furthermore, it is observed that the SHC method outperforms the SBS method in the MMP tracking

Investigation of a PV System Using a Mathematical Model and Available Data

Master's thesis in Renewable energy (ENE500

Enhanced Voltage-Sourced Inverters for Large-Scale Grid-Connected Photovoltaic Systems

This thesis is mainly focused on (i) modeling of large-scale PV systems in order to study the factors that influence the capacity, efficiency, power quality and safety in connection with the power grid and (ii) proposing system- and circuit-level solutions and control strategies/techniques to improve the aforementioned factors. To that end, a model for PV array is developed to study the mismatch power loss in different PV array interconnection methods, especially during the partial shading condition. Further, a two-MPPT structure is proposed to reduce the mismatch power loss in centrally structured PV systems. Then, a single-stage VSC-based system is proposed to utilize the two-MPPT structure for better efficiency. The proposed system also doubles the DC-link voltage while respecting the safety standards, which in turn, increases the capacity and the efficiency of the central inverter. To further improve capacity and efficiency, a two-stage system is proposed in which the variable MPP voltage of smaller sub-arrays are regulated, by dedicated DC-DC boost converters, at the inverter DC-side terminals. This lets the inverter use the full DC voltage permissible rating and reduces the ohmic loss in DC and AC wirings and in the transformer. The system employs a three-level NPC inverter which generates output with better power quality, facilitates the adoption of two-MPPT structure, and permits utilizing low-voltage (half-rated) switches. The system also promotes the modular/distributed structure which improves the efficiency under partial shading and enables the possibility of utilizing PV modules of different types, ratings, and alignments. Finally, a mitigation technique is proposed in the inverter and grid-interface structures to prevent formation of damaging temporary overvoltages, which sometimes are produced in power systems by distributed generations including PV. The technique utilizes a fourleg inverter connected to a grid through a Y/YG isolation transformer. The effectiveness of the proposed techniques and control strategies are demonstrated through time-domain simulation studies conducted in the PSCAD/EMTDC software environment

Photovoltaic Emulation System and Maximum Power Point Tracking Algorithm Under Partial Shading Conditions

In this thesis, a novel photovoltaic (PV) emulator and the state-of-art learning–based real-time hybrid maximum power point tracking (MPPT) algorithms have been presented. Real-time research on PV systems is a challenging task because it requires a precise PV emulator that can faithfully reproduce the nonlinear properties of a PV array. The prime objective of the constructed emulator based on integration of unilluminated solar panels with external current sources is to overcome the constraints such as the need for wide surrounding space, high installation cost, and lack of control over the environmental conditions. In addition, the proposed PV emulator is able to simulate the electrical characteristics of the PV system under uniform irradiation as well as partially shading conditions (PSC). Moreover, the application of MPPT technology in PV systems under PSC conditions is challenging. Under complex environmental conditions, the power-voltage (P-V) characteristic curve of a PV system is likely to contain both local global maximum power points (LMPPs) and global maximum power points (GMPP). The MPPT algorithm applied to a PV system should have minimal steady-state oscillations to reduce power losses while accurately searching for the GMPP. The proposed MPPT algorithms resolved the drawbacks of the conventional MPPT method that have poor transient response, high continuous steady-state oscillation, and inefficient tracking performance of maximum power point voltage in the presence of partial shading. The intended algorithms have been verified using MATLAB/Simulink and the proposed PV emulator by applying comparative analysis with the traditional MPPT algorithms. In addition, the performance of the proposed MPPT algorithms and control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-Time-Interface (RTI) 1007 processor board and DS2004 A/D and CP4002 Digital I/O boards. The results indicate that the algorithm is effective in reducing power losses and faster in tracking the speed of the maximum power point with less oscillation under partial shading conditions. In addition, excellent dynamic characteristics of the proposed emulator have been proven to be an ideal tool for testing PV inverters and various maximum power point tracking (MPPT) algorithms for commercial applications and university studies

Solar And Fuel Cell Circuit Modeling, Analysis And Integrations With Power Conversion Circuits For Distributed Generation

Renewable energy is considered to be one of the most promising alternatives for the growing energy demand in response to depletion of fossil fuels and undesired global warming issue. With such perspective, Solar Cells and Fuel Cells are most viable, environmentally sound, and sustainable energy sources for power generation. Solar and Fuel cells have created great interests in modern applications including distributed energy generation to provide clean energy. The purpose of this thesis was to perform a detailed analysis and modeling of Solar and Fuel cells using Cadence SPICE, and to investigate dynamic interactions between the modules and power conversion circuits. Equivalent electronic static and dynamic models for Solar and Fuel Cells, their electrical characteristics, and typical power loss mechanisms associated with them are demonstrated with simulation results. Power conversion circuits for integration with the dynamic models of these renewable low voltage sources are specifically chosen to boost and regulate the input low dc voltage from the modules. The scope of this work was to analyze and model solar and fuel cells to study their terminal characteristics, power loss mechanisms, modules and their dynamics when interfaced with power converters, which would lead to better understanding of these renewable sources in power applications

Solar array fed synchronous reluctance motor driven water pump : an improved performance under partial shading conditions

An improved performance of a photovoltaic (PV) pumping system employing a synchronous reluctance motor (SynRM) under partial shading conditions is proposed. The system does not include the dc-dc converter that is predominantly being utilized for maximizing the output power of the PV array. In addition, storage batteries are also not contained. A conventional inverter connected directly to the PV array is used to drive the SynRM. Further, a control strategy is proposed to drive the inverter so that the maximum output power of the PV array is achieved while the SynRM is working at the maximum torque per Ampere condition. Consequently, this results in an improved system efficiency and cost. Moreover, two maximum power point tracking (MPPT) techniques are compared under uniform and partial shadow irradiation conditions. The first MPPT algorithm is based on the conventional perturbation and observation (P&O) method and the second one uses a differential evolution (DE) optimization technique. It is found that the DE optimization method leads to a higher PV output power than using the P&O method under the partial shadow condition. Hence, the pump flow rate is much higher. However, under a uniform irradiation level, the PV system provides the available maximum power using both MPPT techniques. The experimental measurements are obtained to validate the theoretical work