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Chunxia Gong , Guanghua Li , Lixu Lei (2014). Effect of Active Mass in Electrode Disc on Performance of Li1.06ni0.313co0.313mn0.313o2cathode. Asian Journal of Energy Transformation and Conservation, 1(2): 115-125. DOI: 10.18488/journal.81/2014.1.2/22.214.171.124
Li1.06Ni0.313Co0.313Mn0.313O2 sample has been synthesized by calcination of co-precipitated precursors. Scanning electron microscopy shows that sample powders are aggregated microplates with average sizes of 200 nm. Electrochemical tests show that Cell-2.0 which has the least mass in cathode disc presents initially a much higher discharge capacity under a current density of 135 mA•g-1, 270 mA•g-1, 540 mA•g-1, 810 mA•g-1, 1080 mA•g-1and 1350 mA•g-1 than the other cells. And Cell-2.0 exhibits better cycling performance with capacity retention of 95.58 % after 40 cycles at 270 mA•g-1 current densities than Cell-2.6(77.18 %), Cell-3.0(74.54 %), Cell-3.2(74.79 %) and Cell-3.6(77.56 %). The cells with a regression equation: DC(mAh•g-1)=a×m(mg) +b, regression coefficient: r≧ 0.75216; a = 7.16984I(C)– 61.50523, regression coefficient: r = 0.95522;b= -39.75258I(C) + 297.48985, regression coefficient: r = 0.9508. Therefore, decreasing the mass in each cathode disc can improve the performance of Li1.06Ni0.313Co0.313Mn0.313O2 cells.
The paper contributes the first example to establishment the regression equation about discharged capacity and the mass in each cathode disc.
A Model of Optimal Time-of-Day Pricing of Electricity under Diverse Welfare Assumptions
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Vijayamohanan Pillai N. (2014). A Model of Optimal Time-of-Day Pricing of Electricity under Diverse Welfare Assumptions. Asian Journal of Energy Transformation and Conservation, 1(2): 87-114. DOI: 10.18488/journal.81/2014.1.2/126.96.36.199
An important feature of an electric power system is that its customer’s load varies greatly at random according to time of day, and day of season. Time-of-day pricing of electricity is an indirect load management against such variable demand according to which electricity is charged in relation to the time-differential cost of supply. The present study is an attempt at modeling seasonal time-differential pricing of electricity. The static, deterministic model that we present incorporates diverse technology, as well as soft deterministic equivalents of chance constraints representing stochastic demand and inflows. The model is solved for two types of power systems – pure hydro and hydro-thermal – under the umbrellas of four structural assumptions – first best, second-best, monopoly and constrained monopoly.
The present study models seasonal time-differential pricing of electricity under diverse welfare assumptions of first best, second best, monopoly and regulated monopoly pricing, in the case of two typical power systems – hydro and hydro-thermal.
UPFC Integrated With Battery Energy Storage Systems for Stability Improvement
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K. Saravanan , Dawit Leykuen Berhanu , Getnet Zewde Somano (2014). UPFC Integrated With Battery Energy Storage Systems for Stability Improvement. Asian Journal of Energy Transformation and Conservation, 1(2): 76-86. DOI: 10.18488/journal.81/2014.1.2/188.8.131.52
In Electrical Power network, consumer loads are time to time variation in existing transmission system. Loads will not constant means, power quality issues there such as voltage have been flickering and deviations in power supply which make some of the electronic equipments and domestic devices highly sensitive to it . Unified Power Flow Controller (UPFC) is most promising new technologies among the many FACTS devices which can improve the power system operation and power quality problems. To avoid such problems need to find out devices that can provide a backup during the time of voltage sags and such deviations. UPFC joined with batteries through dc-dc chopper have been introduced to improve their ability to exchange real power. The active power injected into the DC-bus is controlled by varying the duty cycle of the switches in the dc-dc chopper while the battery is discharging.
Energy storage devices in power systems can be added to existed FACTS devices to increase their stability of the power system. This paper concentrated in integrating UPFC with battery energy storage system which helps to improving the reliable operation of the power systems.
Modeling and Optimization of Phenylacetyylcarbinol Synthesis via Benzaldehyde: A Case of Artificial Neural Network vs. Response Surface Methodology
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Adepoju Tunde. F , Olawale O (2014). Modeling and Optimization of Phenylacetyylcarbinol Synthesis via Benzaldehyde: A Case of Artificial Neural Network vs. Response Surface Methodology. Asian Journal of Energy Transformation and Conservation, 1(2): 56-75. DOI: 10.18488/journal.81/2014.1.2/184.108.40.206
In this study, a comparative optimization of biotransformation of benzaldehyde to L-Phenylacetylcarbinol via free cells of Saccharomyces cerevisae using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) was done. A polynomial regression model was developed and RSM optimum process was determined. In developing ANN model, performance of ANN is heavily influenced by its network structure, five-level-five-factors design was applied, which generated 50 experimental runs from CCD design of RSM. The inputs for the ANN were cell mass (wet. wt), incubation duration (min), concentration of acetaldehyde (mg/100 ml), concentration of benzaldehyde (mg/100 ml), and β-cyclodextrin level (%): X5. The learning algorithms used was QP with MNFF and the transfer function was Tanh. The RMSE, R2, AAD and predicted values were used to compare the performance of the RSM and ANN models. The extrapolative fitness of ANN model was found to be higher than RSM extrapolative fitness model. Thus, it can be concluded that even though RSM is mostly used method for experimental optimization, the ANN methodology present a better alternative.
This study contributes in the existing literature to science and engineering. This study uses new estimation methodology for the conversion of benzaldehyde to L-PAC. This study originates new formula to enhance the concentration of L-PAC. This study is one of very few studies which have investigated the use of β-CD to improve the L-PAC formation. The paper contributes the first logical analysis in modeling and optimization of L-PAC formation. The paper’s primary contribution is finding that L-PAC production can be enhanced using statistical software. This study documents the superiority of artificial neural network over response surface methodology.