首页> 外文会议>AES-vol.46; American Society of Mechanical Engineers(ASME) International Mechanical Engineering Congress and Exposition; 20061105-10; Chicago,IL(US) >OPTIMIZATION OF THE DESIGN OF COMPLEX ENERGY CONVERSION SYSTEMS USING MATHEMATICAL PROGRAMMING AND GENETIC ALGORITHMS
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OPTIMIZATION OF THE DESIGN OF COMPLEX ENERGY CONVERSION SYSTEMS USING MATHEMATICAL PROGRAMMING AND GENETIC ALGORITHMS

机译:基于数学规划和遗传算法的复杂能量转换系统设计优化

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摘要

The paper presents two different optimization methods for the cost-effective design of energy conversion systems. Starting point of the optimization is a complex superstructure that allows several alternative design specifications for a combined-cycle-based cogeneration plant to be studied. Depending on the user specified demands for electricity and process steam, the optimization algorithm performs a simultaneous structural and process variable optimization of the design, to minimize the levelized total costs of the plant products. Mathematical programming and specialized genetic algorithms are used as optimization algorithms. These do not only differ largely in their optimization approach but also have different requirements for the modeling of the superstructure. Several optimization cases are presented to examine the applicability of both algorithms on the present optimization problem. A concluding comparison reveals the advantages and disadvantages of each optimization method.
机译:本文提出了两种不同的优化方法,用于能量转换系统的高性价比设计。优化的起点是一个复杂的上部结构,该结构允许研究基于联合循环的热电联产厂的几种替代设计规范。根据用户指定的电力和过程蒸汽需求,优化算法会同时进行设计的结构和过程变量优化,以使工厂产品的总成本最小化。数学编程和专门的遗传算法被用作优化算法。这些不仅在优化方法上有很大不同,而且对上部结构的建模也有不同的要求。提出了几种优化案例,以检验两种算法在当前优化问题上的适用性。最后的比较揭示了每种优化方法的优缺点。

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