scholarly journals Optimization of Biogas Electrical Power Generation using Neuro-Fuzzy Controller

2020 ◽  
Vol 7 (6) ◽  
pp. 21-29
Author(s):  
Araoye Timothy Oluwaseun ◽  
Alor Michael Onyeamaechi ◽  
Okika Stephen Sunday
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Power System ◽  
Electrical Power Generation ◽  
Power Output ◽  
Fuzzy Controller ◽  
Electrical Power ◽  
Fuzzy Model ◽  
Neuro Fuzzy ◽  
Electrical Power Output

Biogas electrical power generation is a renewable energy which originated from biological materials. The technology design and model power system that predict and control the generation of biogas Electrical production. This research paper develops a Neuro-fuzzy controller model for generation of Biogas power production. A Neuro-fuzzy controller is design to the Biogas power system in order to improve the power quality delivery to the load. The set of 27 rules are written for proper training of biogas electrical data in the neural network. The training is used to control signal of the Biogas Power output of the system. The  output  of  Neural Network  unit  is  given  as  input  to  the de-fuzzification  unit and the linguistic variables are converted back into the crisp form. Therefore the algorithm was designed to decide power supply to the load as to improve the performance of the biogas system using MATLAB/SIMULINK and Neuro-fuzzy model was developed for easy input of the data. The result shows that biogas electrical power output increased by 4.39kw, which is 54.8% increase when Neuro-fuzzy controller is incorporated. The improvement in the system is due to the training of input parameters of the biogas generated. The result obtained shows that there is Real Power improvement in Biogas system when Neuro-fuzzy is incorporated in the system model

Performance Analysis of Near-Field Thermophotovoltaic With a Multilayer Metallodielectric Emitter

2016 ◽  
Author(s):  
Y. Yang ◽  
J. Y. Chang ◽  
L. P. Wang
Keyword(s):  
Heat Flux ◽  
Power Output ◽  
Indium Tin Oxide ◽  
Effective Medium Theory ◽  
Near Field ◽  
Electrical Power ◽  
Electrical Contacts ◽  
Alumina Layer ◽  
Photon Transport ◽  
Electrical Power Output

The photon transport and energy conversion of a near-field thermophotovoltaic (TPV) system with a selective emitter composed of alternate tungsten and alumina layers and a photovoltaic cell sandwiched by electrical contacts are theoretically investigated in this paper. Fluctuational electrodynamics along with the dyadic Green’s function for a multilayered structure is applied to calculate the spectral heat flux, and photocurrent generation and electrical power output are solved from the photon-coupled charge transport equations. The tungsten and alumina layer thicknesses are optimized to match the spectral heat flux with the bandgap of TPV cell. The spectral heat flux is much enhanced when plain tungsten emitter is replaced with the multilayer emitter due to the mechanism of surface plasmon polariton coupling in the tungsten thin film. In addition, the invalidity of effective medium theory to predict photon transport in the near field with multilayer emitters is discussed. Effects of a gold back reflector and indium tin oxide front coating with nanometer thickness, which could practically act as the electrodes to collect the photon-generated charges on the TPV cell, are explored. Conversion efficiency of 23.7% and electrical power output of 0.31 MW/m2 are achieved at 100 nm vacuum gap when the emitter and receiver are respectively at temperatures of 2000 K and 300 K.

Experiments on High-Temperature Inert Gas Plasma MHD Electrical Power Generation with Hall and Diagonal Connections

2015 ◽  
Vol 193 (3) ◽  
pp. 17-23 ◽  
Author(s):  
Fumihiko Komatsu ◽  
Manabu Tanaka ◽  
Tomoyuki Murakami ◽  
Yoshihiro Okuno
Keyword(s):  
Power Generation ◽  
High Temperature ◽  
Electrical Power Generation ◽  
Electrical Power ◽  
Inert Gas ◽  
Gas Plasma

scholarly journals Evaluating Energy Generation Capacity of PVDF Sensors: Effects of Sensor Geometry and Loading

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1895
Author(s):  
Mohammad Uddin ◽  
Shane Alford ◽  
Syed Mahfuzul Aziz
Keyword(s):  
Surface Area ◽  
Power Output ◽  
Energy Harvester ◽  
Mechanical Strain ◽  
Electrical Power ◽  
Human Movement ◽  
Loading Frequency ◽  
Dielectric Thickness ◽  
Generating Capacity ◽  
Electrical Power Output

This paper focuses on the energy generating capacity of polyvinylidene difluoride (PVDF) piezoelectric material through a number of prototype sensors with different geometric and loading characteristics. The effect of sensor configuration, surface area, dielectric thickness, aspect ratio, loading frequency and strain on electrical power output was investigated systematically. Results showed that parallel bimorph sensor was found to be the best energy harvester, with measured capacitance being reasonably acceptable. Power output increased with the increase of sensor’s surface area, loading frequency, and mechanical strain, but decreased with the increase of the sensor thickness. For all scenarios, sensors under flicking loading exhibited higher power output than that under bending. A widely used energy harvesting circuit had been utilized successfully to convert the AC signal to DC, but at the sacrifice of some losses in power output. This study provided a useful insight and experimental validation into the optimization process for an energy harvester based on human movement for future development.

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