Thermoelectric Generators (TEGs) modules—Optimum electrical configurations and performance determination

Author:

Bayendang Nganyang Paul,Kahn Mohamed Tariq,Balyan Vipin

Abstract

<abstract> <p>Renewable energy technologies such as solar, thermal, wind, hydro, bio-fuels, fuel cells etc. are becoming trendy and being commissioned in large-scales, due to their environmental friendliness and energy sustainability. This manuscript focuses on alternative energy based-on thermoelectricity, particularly thermoelectric generators (TEGs). From the literature review, there is less emphasis on how multiple TEGs can be best configured electrically for optimum operations. In light of this, Matlab/Simulink were employed to institute a unique theoretical framework, that can easily be comprehensively used to simulate thermoelectricity parameters, with focus to determine TEG modules (of any quantity/configuration) optimal resistance matching and performance. The principal findings of the study are; 1) the effects of TEGs internal resistance, which proportionally causes output voltage drop and power loss as well as efficiency loss and 2) TEG modules may not be connected anyhow in series and or in parallel, but in a setup that gives a total electrical resistance that matches the load electrical resistance. Thus, TEGs should be a) of the same model with the same or approximate internal resistance, b) in a configuration whereby the TEGs total resistance equals the load resistance, as doing so ensures maximum power is transferred between the source (TEGs) and the electrical load and c) preferably be in a symmetrical electrical configuration. A symmetrical electrical configuration ensures ⅰ) the TEG modules total output resistance, irrespective of the quantity used, approximates that of a single TEG, with the overall TEG modules simply becoming now one large powerful TEG having an equivalent resistance of a single TEG and ⅱ) the TEGs power, voltage and current operations are optimal.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

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