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
收藏
页码：302 / 314
页数：13
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