Predicting of the Geothermal Heat Pump System Coefficient of Performance using Artificial Neural Network

2017 ◽  
Vol 24 (5) ◽  
pp. 562-567 ◽  
Author(s):  
Ji-Hyun Shin ◽  
Young-Hum Cho
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Heat Pump ◽  
Coefficient Of Performance ◽  
Geothermal Heat ◽  
Pump System ◽  
Heat Pump System ◽  
Geothermal Heat Pump ◽  
Artificial Neural

scholarly journals Machine-Learning-Based Coefficient of Performance Prediction Model for Heat Pump Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 362
Author(s):  
Ji-Hyun Shin ◽  
Young-Hum Cho
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Artificial Neural Network ◽  
Prediction Model ◽  
Heat Pump ◽  
Nearest Neighbor ◽  
K Nearest Neighbor ◽  
Pump System ◽  
Heat Pump System ◽  
Artificial Neural

In a heat pump system, performance is an important indicator that should be monitored for system optimization, fault diagnosis, and operational efficiency improvement. Real-time performance measurement and monitoring during heat pump operation is difficult because expensive performance measurement devices or additional installation of various monitoring sensors required for performance calculation are required. When using a data-based machine-learning model, it is possible to predict and monitor performance by finding the relationship between input and output values through an existing sensor. In this study, the performance prediction model of the air-cooled heat pump system was developed and verified using artificial neural network, support vector machine, random forest, and K-nearest neighbor model. The operation data of the heat pump system installed in the university laboratory was measured and a prediction model for each machine-learning stage was developed. The mean bias error analysis is −3.6 for artificial neural network, −5 for artificial neural network, −7.7 for random forest, and −8.3 for K-nearest neighbor. The artificial neural network model with the highest accuracy and the shortest calculation time among the developed prediction models was applied to the Building Automation System to enable real-time performance monitoring and to confirm the field applicability of the developed model.

The design of a seasonal heat storage system with a geothermal heat pump for a residential building in Tehran

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Akbar Alidadi Shamsabadi ◽  
Mehdi Jahangiri ◽  
Tayebeh Rezaei ◽  
Rouhollah Yadollahi Farsani ◽  
Ali Seryani ◽  
...  
Keyword(s):  
Heat Pump ◽  
Heating System ◽  
Coefficient Of Performance ◽  
Maximum Temperature ◽  
Software Environment ◽  
Geothermal Heat ◽  
Pump System ◽  
Matlab Software ◽  
Content Type ◽  
Heat Pump System

Purpose In this study, a solar water heating system along with a seasonal thermal energy storage and a heat pump is designed for a villa with an area of 192 m2 in Tehran, the capital of Iran. Design/methodology/approach According to the material and the area of the residential space, the required heating of the building was calculated manually and then the thermodynamic analysis of the system and simulation was done in MATLAB software. Finally, regarding the waste of system, an efficient solar heating system, providing all the required energy to heat the building, was obtained. Findings The surface area of the solar collector is equal to 46 m2, the capacity of the tank is about 2,850 m3, insulation thickness stands at 55 cm and the coefficient of performance in required heat pump is accounted to about 9.02. Also, according to the assessments, the maximum level of received energy by the collector in this system occurs at a maximum temperature of 68ºC. Originality/value To the best of the authors’ knowledge, in the present work, for the first time, using mathematical modeling and analyzing of the first and second laws of thermodynamics, as well as using of computational code in MATLAB software environment, the solar-assisted ground source heat pump system is simulated in a residential unit located in Tehran.

Optimization and energy-economic assessment of a geothermal heat pump system

2020 ◽  
Vol 133 ◽  
pp. 110282 ◽  
Author(s):  
Pooya Farzanehkhameneh ◽  
M. Soltani ◽  
Farshad Moradi Kashkooli ◽  
Masoud Ziabasharhagh
Keyword(s):  
Heat Pump ◽  
Economic Assessment ◽  
Geothermal Heat ◽  
Pump System ◽  
Heat Pump System ◽  
Geothermal Heat Pump

An Economical Analysis on a Solar Greenhouse Integrated Solar Assisted Geothermal Heat Pump System

2005 ◽  
Vol 128 (1) ◽  
pp. 28-34 ◽  
Author(s):  
Onder Ozgener ◽  
Arif Hepbasli
Keyword(s):  
Heat Pump ◽  
Cooling System ◽  
Heat Pumps ◽  
Renewable Energy Resources ◽  
Ahp Method ◽  
Geothermal Heat ◽  
Pump System ◽  
Heat Pump System ◽  
Economical Analysis ◽  
Geothermal Heat Pump

The main objective in doing the present study is twofold, namely (i) to review briefly the utilization of geothermally heated greenhouses and geothermal heat pumps in Turkey, since the system studied utilizes both renewable energy resources and (ii) to present the Analytical Hierarchy Process (AHP) as a potential decision making method for use in a greenhouse integrated solar assisted geothermal heat pump system (GISAGHPS), which was installed in the Solar Energy Institute of Ege University, Izmir, Turkey. This investigation may also be regarded as the one of the limited studies on the application of the AHP method to GISAGHPs, as no studies on the GISAGHPS have appeared in the literature. In this context, an economic analysis is performed based on the life cycle costing technique first. The results are then evaluated by applying the AHP method to a study, which is a comparative study on the GISAGHPS and split system. The results indicated that the GISAGHPS is economically preferable to the conventional split heating/cooling system under Turkey’s conditions.

scholarly journals Development of Optimal Design Method for Ground-Source Heat-Pump System Using Particle Swarm Optimization

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4850
Author(s):  
Hyeongjin Moon ◽  
Jae-Young Jeon ◽  
Yujin Nam
Keyword(s):  
Renewable Energy ◽  
Heat Pump ◽  
Optimization Design ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Geothermal Heat ◽  
Pump System ◽  
Heat Pump System ◽  
Geothermal Heat Pump ◽  
Building Load

The building sector is an energy-consuming sector, and the development of zero-energy buildings (ZEBs) is necessary to address this. A ZEB’s active components include a system that utilizes renewable energy. There is a heat-pump system using geothermal energy. The system is available regardless of weather conditions and time, and it has attracted attention as a high-performance energy system due to its stability and efficiency. However, initial investment costs are higher than other renewable energy sources. To solve this problem, design optimization for the capacity of geothermal heat-pump systems should be performed. In this study, a capacity optimization design of a geothermal heat-pump system was carried out according to building load pattern, and emphasis was placed on cost aspects. Building load patterns were modeled into hospitals, schools, and apartments, and, as a result of optimization, the total cost over 20 years in all building load patterns was reduced.

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