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首页> 外文期刊>Expert Systems with Application >Modified differential evolution approaches applied in exergoeconomic analysis and optimization of a cogeneration system
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Modified differential evolution approaches applied in exergoeconomic analysis and optimization of a cogeneration system

机译：改进的差异进化方法应用于热电经济分析和热电联产系统的优化

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摘要

Exergoeconomic analysis and optimization technique combine second law analysis with economics for cost effective thermal systems design. Most of the conventional exergoeconomic optimization methods are iterative in nature and require the interpretation of the designer. On the other hand, as an alternative to the conventional mathematical approaches, modern stochastic optimization techniques based on evolutionary algorithms (EAs) have been given attention by researchers due to their ability to find potential solutions. A powerful EA is the differential evolution (DE) algorithm. The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. In this work, a cogeneration system is optimized using exergoeconomic principles and modified DE (MDE) approaches. Results shows that the minimum cost was obtained with MDE(3) having the minimum cost of 1272.23 ($/h) while MDE(5) presents the minor CPU mean time (s). It is possible to note that the properties obtained in this study are better than that obtained in previous study, exception that the increase in capital investment cost is higher at 14.9% in comparison to 10% in the previous study, nevertheless additional investment can be paid back in approximately 3 years.
机译：能效经济学分析和优化技术将第二定律分析与经济学相结合，可实现经济高效的热力系统设计。大多数传统的能效经济优化方法本质上都是迭代的，需要设计者的解释。另一方面，作为传统数学方法的替代方法，基于进化算法（EA）的现代随机优化技术因其发现潜在解决方案的能力而受到研究人员的关注。强大的EA是差分进化（DE）算法。 DE算法已在许多实际情况下使用，并显示出良好的收敛性。在这项工作中，利用能效经济学原理和改进的DE（MDE）方法对热电联产系统进行了优化。结果表明，使用MDE（3）获得的最低成本为1272.23（$ / h），而MDE（5）给出了次要的CPU平均时间。可能需要注意的是，本研究中获得的性能要优于先前研究中获得的性能，但与之前研究中的10％相比，资本投资成本的增幅更高，为14.9％，但是仍然可以支付额外的投资大约3年后

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