Photovoltaic (pv) Applications Optimized Control Study

Nowadays,as the fossil fuel exhaustion and environmental pollution are aggravated, development of alternative energy systems,which are renewable and pollution-free,has been increased continuously.Among these energy systems,the photovoltaic energy stands out as an important solution because it can directly transform solar irradiation into electricity by a photovoltaic generation system without inducing environmental pollution. Photovoltaic cell,which is the core component of a photovoltaic generation system,has its own characteristics under different conditions.Many researchers have focused on optimization research of photovoltaic cell's efficiency.One of these researches is maximum power point tracking(MPPT),which is essential for photovoltaic generation systems.By taking a typical photovoltaic application system as the research object,this paper emphasizes on the research of MPPT both in theory and experiment in order to improve the efficiency of photovoltaic cell.More details about this paper are listed as follows.Firstly,research background and present research situation are summarized systemically.Secondly,based on the operational theory and mathematical model,output characteristics of a photovoltaic cell are simulated by programming under MATLAB environment.Simulation and experimental results on a TH110(17) photovoltaic array show the accuracy of this approach.And then a simulation model for photovoltaic array,which can simulate the characteristics corresponding to different ambient temperatures,solar radiations and photovoltaic array's parameters,is proposed.Subsequently,several conventional MPPT methods are detailed analyzed.Guided by these MPPT methods,a simulation model for a photovoltaic application system is proposed.In addition,a modified Perturbation and Observation Algorithm is introduced.Simulation and experimental results demonstrate that the proposed method can effectively reduce the tracking power loss and have good performance in both dynamic response and steady-state.At last,process of optimizing Radial-Basis Function neural network with Genetic Algorithm is explained in details. Compared the simulation and experimental results with traditional Radial-Basis Function neural network,validity of the optimized network in maximum power point tracking is verified.