Abstract
The use of control systems for photovoltaic installations significantly increases the generation of electrical energy and the efficiency of their use. Solar power supply systems are highly dependent on various climatic factors and therefore there is a real need to use automatic control systems for their various energy parameters, such as current, voltage and power. One of the promising systems for monitoring the energy characteristics of photovoltaic installations is MPPT systems (systems for monitoring maximum power points). This article explores the impact of various maximum power point (MPP) tracking methods applied to photovoltaic systems. This work uses methods like climb-to-top (HC), incremental conduction (IC), and perturbation and observation (P&O). A model of a photovoltaic module and a DC boost converter with various TMM “machine theory” methods were modeled using Matlab software . A joint simulation between Matlab Simulink software packages is used to establish the TMM method. Co-simulation is performed to take advantage of each program to process certain parts of the system. The response of various TMM methods is evaluated in rapidly changing weather conditions. The results show that IC performed best among the compared TMM methods, followed by P&O and HC TMM methods in both dynamic response and steady-state over most of the normal operating range. The incremental conduction method has the advantage of extracting more power compared to perturbation and observation. Method and climb-to-top method and are therefore more competitive than the other two methods in a photovoltaic system.
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