Multi-objective particle swarm optimization of binary geothermal power plants

被引：41

作者：

Clarke, Joshua ^{[1
]}

McLeskey, James T., Jr. ^{[1
]}

机构：

[1] Virginia Commonwealth Univ, Dept Mech & Nucl Engn, Richmond, VA USA

来源：

APPLIED ENERGY | 2015年 / 138卷

关键词：

Geothermal electric; Binary geothermal; Particle swarm optimization; Multi-objective optimization; CYCLE; PERFORMANCE;

D O I：

10.1016/j.apenergy.2014.10.072

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this paper, a method for determining the optimum use of a superheater and/or recuperator in a binary geothermal power plant is developed. Additionally, a multi-objective optimization algorithm is developed to intelligently explore the trade-off between specific work output and specific heat exchanger area and allow visualization of the entire Pareto-optimal set of designs for a wide range of geothermal brine temperatures and dry-bulb temperatures. Selected data is tabulated to show representative optimal designs for each combination of dry-bulb temperature and brine temperature. This work illustrates the development and use of a sophisticated analysis tool utilizing multi-objective particle swarm optimization to allow calculation of the Pareto-optimal set of designs under any combination of dry-bulb temperature and brine temperature while accounting for necessary real-world constraints. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：302 / 314

页数：13

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