Özet:

Industrial thermoelectric generators (TEJs) that can increase energy circulation efficiency to up to 10%, contribute to energy efficiency by using electricity from waste heat. The fact that the internal resistance of TEJ and the load resistance are not equal reduces the yield value significantly. Maximum Power Point Monitor (MGNI) algorithms are used to eliminate or minimize the imbalance between internal resistance and load resistance. In this study, the MGNI algorithm, based on the Mixed and Observed (K&G) method to ensure the equality between internal resistance and load resistance, was modeled with MATLAB/Simulink using a down-to-up translator. First, a TEJ modeling was made depending on Seebeck’s fixation and temperature difference. In this modeling, after determining the series and parallel TEJs to be connected, the direct variable load resistance is connected to the TEJ model's output. The load resistance and temperature difference are calculated for the exit force for the variable values. In this case, it has been found that the MGNI-free TEJ has been greatly affected by cargo changes. The value of the yield is also constantly releasing. Later, this temperature difference change and variable load was applied to the K&G MGNI down-up translator system. The developed K&G MGNI algorithmic TEJ, despite the change in load and temperature, observed the maximum power point (MGN) with 98.72 percent accuracy, and the TEJ was run with the highest efficiency in all circumstances. The model of a lower-up-translator TEJ system, controlled by this developed K&G MGNİ algorithm, has provided designers with a comparison work that will only be sufficient to enter the Seebeck fixed and serial-parallel TEJ numbers.

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