Multi-objective optimization in a finite time thermodynamic method for dish-Stirling by branch and bound method and MOPS
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RESEARCH ARTICLE
Mohammad Reza NAZEMZADEGAN, Alibakhsh KASAEIAN, Somayeh TOGHYANI, Mohammad Hossein AHMADI, R. SAIDUR, Tingzhen MING
Multi-objective optimization in a finite time thermodynamic method for dish-Stirling by branch and bound method and MOPSO algorithm
© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract There are various analyses for a solar system with the dish-Stirling technology. One of those analyses is the finite time thermodynamic analysis by which the total power of the system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders, and cold side heat exchanger have been considered. During this investigation, four objective functions have been optimized simultaneously, including power, efficiency, entropy, and economic factors. In addition to the fourobjective optimization, three-objective, two-objective, and single-objective optimizations have been done on the dishStirling model. The algorithm of multi-objective particle swarm optimization (MOPSO) with post-expression of preferences is used for multi-objective optimizations while the branch and bound algorithm with pre-expression of preferences is used for single-objective and multi-objective optimizations. In the case of multi-objective optimizations with post-expression of preferences, Pareto optimal front Received Mar. 3, 2017; accepted Jun. 1, 2017; online Apr. 6, 2018 Mohammad Reza NAZEMZADEGAN, Alibakhsh KASAEIAN, Somayeh TOGHYANI Department of Renewable Energies, Faculty of New Science and Technologies, University of Tehran, Tehran, 1417466191, Iran
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Mohammad Hossein AHMADI ( ) Faculty of Mechanical Engineering and Mechatronic, Shahrood University of Technology, Shahrood 3619995161, Iran E-mail: [email protected] R. SAIDUR Faculty of Science and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500 Petaling Jaya, Malaysia; Department of Engineering, Lancaster University, Lancaster, LA1 4YW, UK Tingzhen MING School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China
are obtained, afterward by implementing the fuzzy, LINMAP, and TOPSIS decision making algorithms, the single optimum results can be achieved. The comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite time thermodynamic equations. Keywords dish-Stirling, finite time model, branch and bound algorithm, multi-objective particle swarm optimization (MOPSO)
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Introduction
The energy crisis and environmental concerns at the late 20th century drew the attention of worldwide societies to fossil fuels replacements. One of the most important replacements of fossil fuels is solar energy [1]. DishStirling systems by implementing solar energy in the Stirling cycle are one of the most-known solar systems. There are various analyses for a solar system with the dishStirling technology. One of those
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