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Your search keyword '"Lafta, Alaa M."' showing total 3 results
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3 results on '"Lafta, Alaa M."'

1. Conduction and convection cooling of micro-chip device (electrophoresis device).

Author

Lafta, Alaa M., Jebuer, Hussein M., and Obaid, Maithm A.

Subjects
*HEAT transfer, *SEEBECK coefficient, *THERMAL resistance, *ELECTRIC resistance, *ELECTRONIC equipment, *HEAT flux, *NANOFLUIDS
Abstract

Recently, thermo-electric cooling technology (TECT) had developed as one of the most low-energy-consumption and effective approaches of electronic cooling. The present research gave detailed survey regarding TECT in order to provide a thorough understanding of thermo-electric applications in the electronic cooling. The thermo-electric physical parameters, which include the thermal conductivity K, Seebeck coefficient S, and electric resistance R, are highly influenced by the temperature degrees of the thermo-electric cooling and heating sides and were simplified to constants in a case when the thermo-electric cooling model has been established theoretically. In addition, a total of two systematical solution techniques, namely, effectiveness-number of the transfer units and thermal resistance network, were developed to explain coefficient of performance (COP). The impacts of air temperature, cooling load, and all of the thermal conductance in the heating side on performance of the cooling were investigated, with surface temperature of the electronic devices and COP serving as assessment indices. According to our findings, thermal control for the high heat flux electronics might be accomplished through improving heat transfer in hot side of thermo-electric system and increasing the number of the thermo-electric coolers. Regulating parameters and modelling for the practical applications were provided, and cooling capability of thermo-electric technology for electrical devices has the potential to be developed further. [ABSTRACT FROM AUTHOR]

Published
2023
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2. A Novel MPPT Method Based on PSO and ABC Algorithms for Solar Cell.

Author

Sathasivam, Karthikeyan, Garip, Ilhan, Saeed, Saeed Hassan, Yais, Yaser, Alanssari, Ali Ihsan, Hussein, Ali Adhab, Hammoode, Jenan Ali, and Lafta, Alaa M.

Subjects
*SOLAR cells, *PARTICLE swarm optimization, *MAXIMUM power point trackers, *SOLAR panels, *ALGORITHMS
Abstract

The maximum power point tracking (MPPT) system ensures that the solar cell operates at its maximum power point, which is the point at which it produces the most power for a given set of conditions. This study uses an artificial bee colony (ABC) algorithm and particle swarm optimization (PSO) algorithms to optimize the boost converter. The ABC and PSO algorithms help to optimize the boost converter by finding the best possible duty cycle and other parameters that maximize efficiency. The resulting duty cycle of 20% produced the highest efficiency of 78.26% obtained from the boost converter. A system-wide test was conducted between 9:00 and 11:10 WIB. In MPPT systems using boost converters with the PSO algorithm, the average power is 16.80 W, while in MPPT systems using boost converters with the ABC algorithm, the average power is 14.53 W. The novelty of the study discusses a system designed to optimize power by using a boost converter in order to increase power output from solar panels. The algorithms PSO and ABC are used to analyze the data from the PV and adjust the converter parameters to optimize the output in order to increase the efficiency of the system. [ABSTRACT FROM AUTHOR]

Published
2024
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3. Economic Optimization of Combination of Wind, Solar, and Battery Storage for Grid-Independent Power Supply using Cuckoo Optimization Algorithm.

Author

Al-Azzawi, Waleed Khalid, Althahabi, Ahmed Majed, Al-Majdi, Kadhum, Hammoode, Jenan Ali, Adhab, Ali Hussein, Lafta, Alaa M., Zhazira, Julayeva, and Sadratdin, Аbdukarimov

Subjects
*OPTIMIZATION algorithms, *POWER resources, *METAHEURISTIC algorithms, *RENEWABLE energy sources, *HYBRID systems, *SUSTAINABLE design, *GRIDS (Cartography), *HYBRID power systems
Abstract

Renewable energy sources, such as wind and solar, are becoming increasingly popular due to their environmentally friendly and sustainable nature. However, one major challenge associated with these systems is their intermittent nature, which makes it difficult to rely on them as a consistent source of energy. To address this challenge, researchers have developed a combined system that incorporates wind and solar resources with a battery as a storage device, which can provide a sample load pattern independent of the grid. The primary objective of this system is to determine the optimal economic combination of these resources, which can ensure a reliable and consistent supply of electricity. To achieve this objective, the Cuckoo Optimization Algorithm (COA), a metaheuristic optimization algorithm, has been used to optimize the system. The objective function has been implemented in accordance with the constraints, and the results provide insight into the optimal combination of resources. This paper provides a comprehensive analysis of the design and optimization of a wind-solar hybrid energy system with battery storage, using the COA, as well as the results of this analysis. The outcomes indicated that the optimal hybrid system model may be able to reduce system costs by 10–25%. This research's findings can be used to inform the design of sustainable and dependable renewable energy systems. [ABSTRACT FROM AUTHOR]

Published
2023
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