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The efficiency of the generator is tested with different load and speed conditions.
The use of micromachining techniques allowed us to improve the thermal efficiency of the generator significantly.
Based on the analysis, thermoelectric components can be redesigned to obtain optimal power output and efficiency of the generator.
Furthermore, the dynamics of electrical efficiency of the generator are found to be parallel with those of the net system power.
Results showed that, the temperature in the heating and cooling channel of the micro-thermoelectric-generator was uniform; with the increasing of inlet reactant temperature, the highest temperature difference increased, but the total efficiency of the generator decreased.
The development of smart grid architecture for renewable energy production system is intensively studied for the possibilities that this architecture offers to optimize the global production and to increase the efficiency of the generator by monitoring individually the various sources subjected to diverse working conditions.
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The proposed Artificial Neural Networking controller is designed to be implemented to take decision on diesel generators ON/OFF status and maintain a minimum loading level on the generator under light load and high solar radiation levels and maintain high efficiency of the generators and switch off diesel generator when not required based on predictive information.
And when the solar irradiation is larger than 700 W/m2, and water temperature of 13 °C, the maximum instantaneous electrical power output was found to be 0.659 W at the load resistance 4.2 Ω, and the power generation efficiency of the thermoelectric generator (TEG) is 1.956%, which is close to that of a low temperature organic Rankine cycle system.
To improve the power output and efficiency of the thermoelectric generator system, the variation in the thermoelectric leg configuration is another option.
The efficiency of the new generator is above 80% in the low range of speed while in the high range of speed the efficiency is still above 70%.
As the rotors were directly locked into the shaft, knowing the conversion efficiency of the brushless generator, the fluid dynamic torque was obtained in the PC LabVIEW Controller [8].
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