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

被引:56
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
相关论文
共 68 条
[1]   Connectionist intelligent model estimates output power and torque of stirling engine [J].
Ahmadi, Mohammad H. ;
Ahmadi, Mohammad Ali ;
Sadatsakkak, Seyed Abbas ;
Feidt, Michel .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 50 :871-883
[2]   Using GMDH Neural Networks to Model the Power and Torque of a Stirling Engine [J].
Ahmadi, Mohammad Hossein ;
Ahmadi, Mohammad-Ali ;
Mehrpooya, Mehdi ;
Rosen, Marc A. .
SUSTAINABILITY, 2015, 7 (02) :2243-2255
[3]   Prediction of power in solar stirling heat engine by using neural network based on hybrid genetic algorithm and particle swarm optimization [J].
Ahmadi, Mohammad Hossien ;
Aghaj, Saman Sorouri Ghare ;
Nazeri, Alireza .
NEURAL COMPUTING & APPLICATIONS, 2013, 22 (06) :1141-1150
[4]   A comparative study on exergetic assessment of two ground-source (geothermal) heat pump systems for residential applications [J].
Akpinar, Ebru Kavak ;
Hepbasli, Arif .
BUILDING AND ENVIRONMENT, 2007, 42 (05) :2004-2013
[5]  
[Anonymous], 2015 UN EL CONS PRIC
[6]  
[Anonymous], FEASIBILITY REPORT A
[7]  
[Anonymous], OV INT RAT
[8]  
[Anonymous], ORAL PRESENTATION UN
[9]  
[Anonymous], NEURAL NETWORKS COMP
[10]  
[Anonymous], INFL REP 2015 LAST Q