Thermal energy harvesting: Parameter tuning of maximum power point tracking algorithm for real-time temperature data from solar irradiance
Keywords:Thermoelectric generator, Perturb and Observe, Incremental conductance, Real-time temperature
Thermal energy becomes priceless renewable energy due to the impoverishment of fossil fuels and the increasing carbon pollution. Implementing the thermoelectric generator (TEG) in real-time temperature gradient calls for the intensive appraisal for the energy management circuit to accomplish the maximum power transfer from the thermal source to the output load. Successful implementation of the TEG relies on the MPPT algorithm to confirm the maximum power point achievement at a particular thermal energy level. In-depth analyses for the most acceptable MPPT algorithm methods are convenient to the TEG realistic behavior. Perturb and Observe (P&O) and Incremental Conductance (INC) MPPT algorithms are popular in thermal energy harvesting. Therefore, the comparison between these two (2) MPPT algorithms in TEG raised to study the efficiency, power losses, and oscillation range based on the parameter tuning results. Furthermore, the qualification of this MPPT algorithm in conjunction with the real-time temperature changing due to solar irradiance is evaluated. P&O shows potential to achieve the MPPT, but INC gives superior capability regarding the TEG implementation at rapid temperatures changing.
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