Güneş panellerinde parçacık sürü optimizasyonu ile maksimum güç takibi

Studies on photovoltaic systems are increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the renewable energy system, it is necessary to track the maximum power point of the input source. Particle swarm optimization (PSO) technique is used to identify the optimal power point of a photovoltaic module used in a stand-alone (PV) system. The PSO algorithm searches the maximum power point of the PV module by determining the array power at maximum point. The tracked variable is used as a reference value (set point) to an ON/OFF controller of a dc boost chopper such that the PV module is forced to operate at the optimal power point. In this thesis the controller is ATmega32 by ATMEL©. This microcontroller by measuring voltage and current of panel and changing duty cycle ON/OFF switch of boost converter, and via PSO algorithm cause panel operate on maximum power point. The advantage of this method versus of other method which use microcontroller like look table-up method, this method does not need any information about panel and environment condition i.e, we can use this controller for any panel in any condition also changing of temperature and irradiation does not affect operation. This method does not need any control loop so it is low cost, which does process with AVR microcontroller and current sensor. By comparing this algorithm with other intelligent systems like fuzzy controller or neural network system this algorithm is more simple.