MPPT Control Optimization And Experimental Studies On PV Systems

The rapid development of economics relies heavily on the energy system. Coal, fuel, and gas belong to un-sustainable energies and will be depleted, which require renewable energies for future consumption. PV is one of the distinguished renewable energies. It is widely distributed, large-stored, and can be utilized conveniently. However, traditional PV systems are low-efficient and high-cost, and this will restrict the large scale application of PV projects. Fortunately, Maximum Power Point Tracking (MPPT) technology is a vital way to address this problem. After decades of development, PV MPPT has been improved and widely applied, In this thesis, we aim to study the key technologies of PV MPPT systems as follows.First, based on the modeling of PV system, we analyze the input-output characteristics in varying environments such as irradiation, temperature, etc. By comparing the existing MPPT algorithms, we find the main shortcomings of traditional methods as:relatively low tracking speed, unstable MPPT, erroneous judgment in case of varying external environments, and complex computation but poor application. To solve the problem, we develop an improved variable step-size incremental conductance MPPT method for PV systems. With the analysis of relationship between the output power and duty-cycle, the advantages of being simple and practical of the duty-cycle method are shown, which help achieve rapid and stable MPPT, and avoid erroneous judgment in abruptly changing environments.Then, three control models are built up for the duty-cycle disturbance observer method, traditional variable step-size incremental conductance method, and the proposed improved variable step-size incremental conductance MPPT method. Simulation experiments are also carried out to verify and analyze the performance of three algorithms in abruptly varying irradiation cases. The simulation results show that the improved variable step-size incremental conductance MPPT method achieves more stable and rapid tracking performance.Moreover, based on the improved variable step-size incremental conductance MPPT method, the hardware and software design of the control system are developed on an actual PV system platform. The practical experiments depict that the improved MPPT shows superior performance with faster response and higher charge efficiency. Finally, we blend the controller with the "internet of things", and come up with a rough scheme for remote and intelligent monitoring of PV lighting facilities, realizing the basic requirements of remote monitoring of PV systems.