Maximum power point tracking technique for PV panels with support of online learning artificial neural network is offered. Mathematical model of the system is implemented in Matlab/Simulink environment. Maximum power point tracking is performed using IncCond algorithm and radial basis function artificial neural network. Several criteria for estimation of system performance were derived. It is shown that ANN can increase overall system efficiency by 10%.
Presented the model based on the clear sky standard, which allows calculation of solar insolation values at each location in Lithuania. Model is associated with geographical coordinates of Lithuania and local time of every day of the year. It is made for modeling electronic systems for management of solar panels and solar thermal collectors. Model was tested by calculating solar insolation at 313 369 locations of Lithuania. It is shown that the lowest insolation in territory of Lithuania on noon of June 21 is 375 m2 and the highest is – 439 W/m2. Deviation of solar insolation values from average is ±8%. In addition, it is shown that the changes in solar insolation are caused by zenith or altitude angle variations. Model is suitable for calculation of optimal angles of solar panels and solar thermal collectors in any location of Lithuania. Ill. 4, bibl. 8 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.108.2.132
efficiency of solar cells is the biggest when the controller adjusts the load according to the temperature of the solar cell and solar energy flux. This task is accomplished by various maximum power point tracking (MPPT) algorithms. This paper presents the analysis of maximum power point tracking efficiency, when some modules of the solar power plant are partially shaded. Mathematical models of photovoltaic module and Incremental Conduction (IncCond) algorithm are implemented in Matlab/Simulink environment. The simulation is performed using saved solar power flux signal, imitating real-world environmental conditions. This signal allows to compare different working modes of MPPT tracker and to calculate the efficiency of the algorithm. It is proposed to use artificial neural network (ANN) to increase the efficiency of (IncCond) algorithm. Using ANN allows faster maximum power point tracking.
The paper presents the architecture of the control and statistical data collection system for solar thermal collectors, describing its operating principle and analysis of individual elements, in order to anticipate possible problems and find their solutions. Expanding functionality of the controller of solar thermal collector with online features one can collect data on solar thermal collectors performance in different regions. The paper describes the structure diagram, according to which the system will register operational parameters of the heating system and weather conditions. Data transfer mode, which allows avoiding instant database server load is offered. It is shown, that the simulation of the solar thermal collector operating cycle and optimization of recorded data stream allows over 14 times to reduce the amount of transferred data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.