Development of an algori̇thm for maxi̇mum power poi̇nt tracking to generate low power photovoltaic electricity generation

Terms of global competition have led to reduce the price of many electrical devices required high level technology to reasonable levels and fall in investment costs in particular; this may obviously be seen in renewable energy or similar applications. Among renewable energy sources, photovoltaic energy is increasingly used to generate electricity for homes and workplaces today. In residential buildings, power is usually generated by photovoltaic panels mounted on their roofs. However, environmental conditions such as irradiation level and temperature are extremely influential on photovoltaic panels and this leads to vary system efficiency depending on which with a sharp decrease. It is necessary to control the photovoltaic system to continuously produce its maximum power for elimination of this drawback. This is typically called maximum power point tracking system and is designed by few researchers through various approaches. In this thesis, a design of maximum power point tracking system for photovoltaic panels mounted on a roof of a typical residential building under instantly varying irradiation level and temperature is achieved. This design is initially based on software application work and has relatively produced meaningful and encouraging outcomes with respect to those of similar works carried out so far. Keywords: Renewable energy applications, Photovoltaic energy generation, Maximum power point tracking system, dc-dc converters, Optimization by genetic algorithms