Kolluru, Venkata Ratnam (2016) Design and Development of FPGA based Controllers for Photovoltaic Power System. PhD thesis.
In the recent years owing to increased energy consumption and consequent rise in crude oil price and global climatic change have motivated researchers to focus towards harnessing power from renewable energy resources such as photovoltaic (PV), fuel cell, biomass and wind energy systems. Among the different renewable resources, PV technology is one of the fastest growing technologies, because of abundance availability of solar irradiance and it has no adverse environmental impacts. But, the cost of PV energy is higher than the other conventional sources owing to its low PV conversion efficiency. Therefore, research opportunities lie in applying power electronics and control techniques for harvesting PV power at higher efficiencies for appropriate utilization. For simulation, analysis and control design of a PV power system, an accurate model of the PV cell is essential because PV cell is the basic bulding block of a PV power system. To maximise the power generation of a PV system it is necessary that the PV array should be operated at the maximum power point. A maximum power point tracker (MPPT) is required in the PV system to enable it to operate at the MPP. The output current-voltage (I-V) and power-voltage (P-V) characteristics of a PV vell are non-linear and hence its power fluctuates in accordance with the variation in solar irradiance and temperature. During the last decade, a lot of research has been directed to develop efficient MPPT schemes. But, research opportunities are still promising for designing new MPPT algorithms and to address their digital implementation issues. Further, there lies challenge to design MPPTs that can handle partial shading conditions. The thesis first proposes development of new MPPT algorithms and different pulse width modulated-voltage source inverter control strategies for a PV system. Firstly an integral sliding mode MPPT controller (ISMC) has been proposed for achieving an effective MPPT scheme, and then a modified P&O MPPT controller is developed which is implemented using a real-time digital simulator called Opal-RT. The performance of the modified ISMC is compared with that of the conventional proportional integral (PI) MPPT controller using both MATLAB simulation and real-time experimentation. The performance of the modified P&O MPPT controller with fixed step size is compared with that of the conventional incremental conductance (Inc Cond) and P&O MPPT controllers, and these are validated by using Opal-RT and subsequently through FPGA implementation. A modified incremental conductance MPPT controller with variable step size is then proposed for handling partial shading conditions. The tracking performance of the proposed modified Inc Cond MPPT controller is also compared with that of the conventional Inc Cond MPPT controller, from the obtained results by using Opal-RT. Further, an experimental prototype PV set-up is developed in the laboratory to implement the proposed MPPT algorithms on the physical hardware. After having developed efficient parameter extraction algorithms for a PV panel, the thesis subsequently proposes five new MPPT algorithms such as Integral sliding mode MPPT, modified P&O MPPT, modified Inc Cond MPPT, Model predictive MPPT, and modified Inc Cond variable step size MPPT controllers. All these developed MPPT algorithms have been implemented on a Solar array simulator (SAS) PV system, in MATLAB/SIMULINK, OPAL-RT and on a prototype hardware PV set-up. From the obtained results, it is found that these MPPTs adjust the power of a PV system effectively to its maximum power value smoothly with fast response and accuracy whilst reducing the fluctuations in its power. Tracking performance of all these proposed MPPT algorithms are found to be superior to some of the existing MPPTs such as perturb and observe (P&O), incremental conductance (INC), HCC and adaptive HCC. Further more, a PV system is observed to be stable with all these proposed MPPTs. From the results obtained it is also confirmed that the proposed modified P&O MPPT exhibits better MPP tracking performance in terms of quick settling time and least steady state error. Further, less voltage fluctuation and less maximum overshoot are observed in the case of the proposed modified Inc Cond MPPT among all the proposed MPPT algorithms. The proposed controllers are also well suited to all weather conditions. A grid connected PV system involves a power conversion from DC power into AC power. Due to high switching frequencies of this conversion by inverter, there is a power loss. An efficient control scheme needs to be developed for integrating the PV system to the grid. The thesis then proposes a Model Predictive Control (MPC) for integrating a PV system to the grid. The performance of the MPC is compared with conventional hysteresis current controller (HCC) and also with that of an adaptive HCC (AHCC) through a real-time simulatin using the Opal-RT then through FPGA implementations. FPGA implementation of the controllers such as HCC, AHCC and MPC were also performed by using LABVIEW configured with NI-cRIO-9014 platform. For elimination of current harmonic and reactive power of the grid connected PV system, there is a need of designing a filter. The PV system based shunt active power filter (SAPF) with modified incremental conductance MPPT controller with variable step size is then designed. From the MATLAB simulation and real-time digital simulation studies it is envisaged that the proposed PV based SAPF exhibits good harmonics compensation.
|Item Type:||Thesis (PhD)|
|Uncontrolled Keywords:||Photovoltic technology, PWM technique, Voltage Source Regulator, Synchronous Reference Frame Theory|
|Subjects:||Engineering and Technology > Electronics and Communication Engineering > Intelligent Instrumentaion|
|Divisions:||Engineering and Technology > Department of Electronics and Communication Engineering|
|Deposited By:||Mr. Sanat Kumar Behera|
|Deposited On:||21 Jul 2016 11:40|
|Last Modified:||21 Jul 2016 11:40|
|Supervisor(s):||Mahapatra, K and Subudhi, B|
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