Optimization of district heating system aided by geothermal heat pump: A novel multistage with multilevel ANN modelling

被引:52
|
作者
Arat, Halit [1 ]
Arslan, Oguz [1 ]
机构
[1] Dumlupinar Univ, Fac Engn, Dept Mech Engn, TR-43270 Kutahya, Turkey
关键词
ANN; District heating; Geothermal heat pump; LCC; ARTIFICIAL NEURAL-NETWORKS; PERFORMANCE ANALYSIS; EXERGY ANALYSIS; POWER; ENERGY; PREDICTION; CYCLE; PARAMETERS; WORKING; TORQUE;
D O I
10.1016/j.applthermaleng.2016.09.150
中图分类号
O414.1 [热力学];
学科分类号
摘要
The aim of this study is to obtain the optimum design of geothermal heat pump aided district heating system (GHPDHS) by using a novel ANN model that composed of multistage with multilevel. For this purpose, the acquiring of the best design were performed by utilizing the back-propagation learning algorithm with three different variants which were Levenberg-Marquardt (LM), Pola-Ribiere Conjugate Gradient (CGP), and Scaled Conjugate Gradient (SCG). In this aim, the proposed ANN model was mainly formed from two stages. The first one has a single level whereas the second one composed of three levels in this new ANN model. According to results, the maximum rate of the error occurred in the Pump 2 as % 3.0092 and the minimum of that was obtained from COPsys with % 0.0018. The best R-2 value of the third level of the second stage network structure was calculated as 1 for LM-20. As a consequent, this study showed that the multistage with multi-level ANN model could be easily applied to other energy systems in order to save more time and simplicity. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:608 / 623
页数:16
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