As photovoltaic power plants provide an ever-increasing share of the world’s electricity and assist in the mitigation of environmental degradation, engineers need to consider new challenges associated with the integration of this variable and intermittent source of energy into the grid. The associated challenges can only be solved by deploying appropriate technologies. This thesis proposes some technological solutions by developing control algorithms for power electronic interfaces involved in photovoltaic (PV) energy conversion. The overall objective is to develop control algorithms and the associated power converter topologies so as to efficiently harvest solar energy with minimal losses and at minimal cost, while providing the much-needed system reliability. The thesis details the analyses and modelling of photovoltaic subsystems, their simulation studies, the control approaches adopted, and the application of maximum power point tracking technique to extract maximum power from the photovoltaic system.udThis thesis starts out with the development of a workable PV simulation model that considers the effects of environmental variables on system’s performance for deeper understanding of PV characteristics and for accurate prediction of the PV system’s behaviour in deployment. Also, introduced in the same chapter is a novel optimisation tool for the design of standalone PV power plants. To convert the “raw energy” from sunlight into usable regulated dc energy, the thesis proposes using a SEPIC (single ended primary inductance converter) dc-dc converter for the interfacing function. An in depth analysis and design of an 800W-capacity SEPIC converter is introduced and deployed for both simulation and experimental studies. Also developed for the SEPIC converter is a robust control system that is able to regulate the dc link voltage to the desired value, irrespective of changes in input voltage or system loading.udThe thesis, also, proposes an improved maximum power point tracking (MPPT) algorithm derived from the incremental conductance MPPT technique. This ensures the efficient operation of the PV power plant by rapidly and accurately tracking the maximum power point (MPP) of the PV array regardless of changes in environmental conditions. In addition, in chapter 5, to ensure the reliability and availability of the PV power plant, the thesis proposes a control system for the bidirectional dc-dc converter that interfaces the energy storage system. The control system offers the desired management of the energy storage system by ensuring proper charging and discharging, protection, and power balance between the PV subsystems. A 500W capacity of the converter is analysed, designed and later constructed in the laboratory.udTo convert the generated dc energy into useful ac power, the thesis develops models and control strategies for the dc-ac converter (inverter) to ensure that sinusoidal waveform of the desired voltage magnitude and frequency is generated. Control strategies for three-phase operation in standalone and grid connected modes are also introduced.udThe developed control algorithms and designed converters are subjected to rigorous simulation studies using MATLAB/Simulink/SimPowerSystems software. Such simulation studies provide useful insight into the PV system’s behaviour when deployed in operation. However, simulation results without experimental backup offers limited practical value. Consequently, the thesis presents the hardware implementation of the entire PV power plant. It discusses the building of the power converter prototypes, the printed circuit boards (PCBs) for data acquisition, conditioning, isolation and gate-driving. The real time control of the plant using a digital signal processor platform is discussed in detail and the experimental results presented for the validation of the simulation results.udThe main contributions of this thesis include: 1) the development of a workable photovoltaic power system simulation model for characterisation studies; 2) development of a software tool for the design of standalone PV plants; 3) development of an improved algorithm for maximum power point tracking; 4) development of an improved current mode based algorithm for control of the energy storage interface converter; 5) development of models for standalone and grid connected PV systems with the associated controls; and 6) experimental implementation of an effective, versatile, low-cost, low-component-count, data acquisition and conditioning system for a PV systems using dSPACE DS1104 DSP system.
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