OPTIMISATION OF MICROTHERMOELECTRIC GENERATORS FOR SOLAR ENERGY CONVERSION

Abstract - Current research trend is going on the hybrid systems to enhance the amount of power generation from a single source. The same idea is implemented in the Photo- voltaic/Thermal (PV/T) systems, where the light energy utilized by the PV system to convert it into electrical energy while the heat energy is the source for all the PV/T system configurations. So, a simple analysis to predict the module temperature for different climatic conditions is required. The module temperature depends on the climatic conditions such as solar irradiation, ambient temperature and wind velocity. These parameters continuously vary non-linearly with respect to time. In this work, used the real time climatic data measured at Nagpur location for the duration of 15 days and proposes a novel approach to find the module temperature by using the Adaptive Neuro Fuzzy Interface System (ANFIS) tool in MATLAB/SIMULINK. This work majorly concentrates on the Thermoelectric Generator (TEG) integrated with the PV systems and is referred as the PV-TEG. First the simulation for the individual systems of commercially available PV and TEG systems are made and they are combined to make PV-TEG configuration. This approach is helpful for the commercialization of the PV-TEG configuration in effective way. The individual and combined performance of PV-TEG is analyzed with the overall efficiency of the system. The over- all efficiency of PV system is increased by integrating the TEG is 6% at Standard Test Conditions (STC). Key Words: PV-TEG, Thermoelectric generator, Energy conservation, Seebeck effect