Estimation of Bioethanol Production from Jatropha curcas Using Neural Network

2013 ◽  
Vol 594-595 ◽  
pp. 943-947
Author(s):  
Norliza Abd. Rahman ◽  
N.T. Kofli ◽  
Zahira Yaakob ◽  
S. Gauri
Keyword(s):  
Neural Network ◽  
Renewable Energy ◽  
Input Data ◽  
Fossil Fuel ◽  
Toxic Substance ◽  
Energy Sources ◽  
Bioethanol Production ◽  
Back Propagation Algorithm ◽  
Seed Cake ◽  
Short Period

Fossil fuel is one of the main energy sources for almost all country in the world. However, it is non-renewable energy source, not environmental friendly and the limited supply of the fossil fuel encouraged the scientist to discover other alternative way of new renewable energy supply. New alternative source should be considered for prolonged lifetime. Thus, non-conventional energy sources should be placed in the prior consideration, for instant bioethanol. Jatropha curcas seed is a toxic substance; however, it has a very high oil content which is approximately 3545%. After the extraction of oil from the seed, Jatropha seed cake is formed. In the pressed seed cake, it is found that it contains cellulose and glucose that can be used as substrate in bioethanol production. The production of bioethanol can be estimated by neural network using data from previous research. A programme using MATLAB 7.8 was used to develop the neural network. The software consists of Neural Network Toolbox which functions to train the input data and estimate the production of glucose and bioethanol as output data. An input layer represents the criteria of the production properties of glucose and bioethanol concentration. The hidden layer determines either the input data can be proceed to further production of glucose and bioethanol, whereas the output layer gives the estimation values of glucose and bioethanol production. Back propagation algorithm with TANSIG transfer function was used to accomplish the estimation of production of bioethanol. The error value given by the network was 0.0390. Thus, training sessions were considered successful. Therefore, the users could determine and estimate the production of glucose and bioethanol concentration in just a short period of time.

scholarly journals Biotechnological tools to improve ethanol production from plant biomass

2022 ◽  
Vol 7 (1) ◽  
pp. 63-68
Author(s):  
Juraj Faragó
Keyword(s):  
Renewable Energy ◽  
Genetic Engineering ◽  
Abiotic Stresses ◽  
Fossil Fuel ◽  
Plant Biomass ◽  
Starch Content ◽  
Renewable Energy Sources ◽  
Renewable Resource ◽  
Energy Sources ◽  
Bioethanol Production

Increasing concerns for security of the fossil fuel supply emphasizes the need to complement fossil fuel-based energy sources with renewable energy sources. Plant biomass represents an abundant renewable resource for the production of bioenergy and biomaterials. This review summarizes the last advancements in the use of biotechnological tools to improve bioethanol production from plant biomass through genetic engineering the starch content and composition and lignocellulosic matter characteristics, and increasing the capacity of plants to produce harvestable yield and ameliorating the negative abiotic stresses on plants so as to increase yield.

Process of metal−organic framework (MOF)/covalent−organic framework (COF) hybrids-based derivatives and their applications on energy transfer and storage

Nanoscale ◽  
2022 ◽  
Author(s):  
Bingbing Cui ◽  
Guo-Dong Fu
Keyword(s):  
Renewable Energy ◽  
Energy Transfer ◽  
Fossil Fuel ◽  
Metal Organic Framework ◽  
Renewable Energy Sources ◽  
Environmental Issues ◽  
Energy Sources ◽  
Metal Organic ◽  
And Storage ◽  
Organic Framework

The fossil-fuel shortage and severe environmental issues have posed ever-increasing demands on clean and renewable energy sources, for which the exploration of electrocatalysts has been in a big challenge toward...

scholarly journals Pretreatments of lignocellulosic feedstock for bioethanol production

2010 ◽  
Vol 64 (4) ◽  
pp. 283-293 ◽  
Author(s):  
Zlatica Predojevic
Keyword(s):  
Renewable Energy ◽  
Co2 Emission ◽  
Fossil Fuels ◽  
Low Cost ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Bioethanol Production ◽  
Environment Protection ◽  
Lignocellulosic Feedstock ◽  
Lignocellulosic Feedstocks

The use of renewable energy sources (biofuels), either as a component in the conventional fossil fuels, gasoline and diesel, or as a pure biofuel, contributes to energy saving and decrease of total CO2 emission. The use of bioethanol mixed with gasoline significantly decreases gasoline consumption and contributes to environment protection. One of the problems in the production of bioethanol is the availability of sugar and starch based feedstock used for its production. However, lignocellulosic feedstocks are becoming more significant in the production of bioethanol due to their availability and low cost. The aim of this study is to point out the advantages and shortcomings of pretreatment processes and hydrolyses of lignocellulosic feedstocks that precede their fermentation to bioethanol.

scholarly journals Solar and Wind Energy Based Microgrid : Study of Architecture's Potential at Coastal Areas in Bangladesh

2018 ◽  
Vol 17 (2) ◽  
pp. 31-36
Author(s):  
Abir Muhtadi ◽  
Ahmed Mortuza Saleque ◽  
Mohammad Abdul Mannan
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Fossil Fuel ◽  
Renewable Energy Sources ◽  
Coastal Areas ◽  
Real Case ◽  
Extension Study ◽  
Energy Sources ◽  
Case Scenario ◽  
Geographical Locations

Due to sheer dependency upon fossil fuel sources, Bangladesh as a country is not free from numerous negative aspects. Country’s requirement for a certain portion of power be generated from renewable energy sources is due and required renewable energy target (RET) needs to be fulfilled. In this study, potential of distinguished coastal sites for entirely renewable energy such as solar and wind sources based microgrid for chosen community is explored. Microgrid architecture is appropriate considering the coastal areas’ geographical locations and due to the inconvenience in grid extension. Study suggests, potential of coastal sites are found to be feasible for such structures based on real case scenario data and modelled technical scheme.

scholarly journals A Review of the Use of Artificial Neural Network Models for Energy and Reliability Prediction. A Study of the Solar PV, Hydraulic and Wind Energy Sources

2019 ◽  
Vol 9 (9) ◽  
pp. 1844 ◽  
Author(s):  
Jesús Ferrero Bermejo ◽  
Juan F. Gómez Fernández ◽  
Fernando Olivencia Polo ◽  
Adolfo Crespo Márquez
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Renewable Energy ◽  
Energy Production ◽  
Renewable Energy Sources ◽  
Operating Conditions ◽  
Energy Sources ◽  
Solar Pv ◽  
Ann Models ◽  
Artificial Neural

The generation of energy from renewable sources is subjected to very dynamic changes in environmental parameters and asset operating conditions. This is a very relevant issue to be considered when developing reliability studies, modeling asset degradation and projecting renewable energy production. To that end, Artificial Neural Network (ANN) models have proven to be a very interesting tool, and there are many relevant and interesting contributions using ANN models, with different purposes, but somehow related to real-time estimation of asset reliability and energy generation. This document provides a precise review of the literature related to the use of ANN when predicting behaviors in energy production for the referred renewable energy sources. Special attention is paid to describe the scope of the different case studies, the specific approaches that were used over time, and the main variables that were considered. Among all contributions, this paper highlights those incorporating intelligence to anticipate reliability problems and to develop ad-hoc advanced maintenance policies. The purpose is to offer the readers an overall picture per energy source, estimating the significance that this tool has achieved over the last years, and identifying the potential of these techniques for future dependability analysis.

scholarly journals Bioethanol Production from Indigenous Algae

2015 ◽  
Vol 4 (1) ◽  
pp. 112-120 ◽  
Author(s):  
Madhuka Roy ◽  
Krishnendu Kundu ◽  
V. R. Dahake
Keyword(s):  
Fossil Fuel ◽  
Anaerobic Fermentation ◽  
Biofuel Production ◽  
Bioethanol Production ◽  
Short Period ◽  
Treatment Stage ◽  
Fuel Characterization ◽  
Complex Carbohydrates ◽  
Pre Treatment

Enhanced rate of fossil fuel extraction is likely to deplete limited natural resources over short period of time. So search for alternative fuel is only the way to overcome this problem of upcoming energy crisis. In this aspect biofuel is a sustainable option. Agricultural lands cannot be compromised for biofuel production due to the requirement of food for the increasing population. Certain species of algae can produce ethanol during anaerobic fermentation and thus serve as a direct source for bioethanol production. The high content of complex carbohydrates entrapped in the cell wall of the microalgae makes it essential to incorporate a pre-treatment stage to release and convert these complex carbohydrates into simple sugars prior to the fermentation process. There have been researches on production of bioethanol from a particular species of algae, but this work was an attempt to produce bioethanol from easily available indigenous algae. Acid hydrolysis was carried out as pre-treatment. Gas Chromatographic analysis showed that 5 days’ fermentation by baker’s yeast had yielded 93% pure bioethanol. The fuel characterization of the bioethanol with respect to gasoline showed comparable and quite satisfactory results for its use as an alternative fuel.DOI: http://dx.doi.org/10.3126/ije.v4i1.12182International Journal of Environment Volume-4, Issue-1, Dec-Feb 2014/15, page: 112-120  

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