scholarly journals Support Vector Regression and Genetic Algorithm for HVAC Optimal Operation

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Ching-Wei Chen ◽  
Yung-Chung Chang
Keyword(s):  
Genetic Algorithm ◽  
Power Consumption ◽  
Air Conditioning ◽  
Support Vector ◽  
Operating Parameters ◽  
Cooling Load ◽  
Unit Load ◽  
Air Handling Unit ◽  
Consumption Model ◽  
Air Conditioning Systems

This study covers records of various parameters affecting the power consumption of air-conditioning systems. Using the Support Vector Machine (SVM), the chiller power consumption model, secondary chilled water pump power consumption model, air handling unit fan power consumption model, and air handling unit load model were established. In addition, it was found thatR2of the models all reached 0.998, and the training time was far shorter than that of the neural network. Through genetic programming, a combination of operating parameters with the least power consumption of air conditioning operation was searched. Moreover, the air handling unit load in line with the air conditioning cooling load was predicted. The experimental results show that for the combination of operating parameters with the least power consumption in line with the cooling load obtained through genetic algorithm search, the power consumption of the air conditioning systems under said combination of operating parameters was reduced by 22% compared to the fixed operating parameters, thus indicating significant energy efficiency.

scholarly journals Power Consumption: Base Stations of Telecommunication in Sahel Zone of Cameroon: Typology Based on the Power Consumption—Model and Energy Savings

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Albert Ayang ◽  
Paul-Salomon Ngohe-Ekam ◽  
Bossou Videme ◽  
Jean Temga
Keyword(s):  
Power Consumption ◽  
Air Conditioning ◽  
Energy Savings ◽  
Base Station ◽  
Energy Model ◽  
Base Stations ◽  
Consumption Model ◽  
Lighting Systems ◽  
Energy Audits ◽  
Air Conditioning Systems

In this paper, the work consists of categorizing telecommunication base stations (BTS) for the Sahel area of Cameroon according to their power consumption per month. It consists also of proposing a model of a power consumption and finally proceeding to energy audits in each type of base station in order to outline the possibilities of realizing energy savings. Three types of telecommunication base stations (BTS) are found in the Sahel area of Cameroon. The energy model takes into account power consumption of all equipment located in base stations (BTS). The energy audits showed that mismanagement of lighting systems, and of air-conditioning systems, and the type of buildings increased the power consumption of the base station. By applying energy savings techniques proposed for base stations (BTS) in the Sahel zone, up to 17% of energy savings are realized in CRTV base stations, approximately 24.4% of energy are realized in the base station of Missinguileo, and approximately 14.5% of energy savings are realized in the base station of Maroua market.

scholarly journals Fault Detection and Diagnosis of Air Handling Unit: A Review

2019 ◽  
Vol 255 ◽  
pp. 06001 ◽  
Author(s):  
Cheng Yew Leong
Keyword(s):  
Fault Detection ◽  
Air Conditioning ◽  
Early Stage ◽  
Fault Detection And Diagnosis ◽  
Commercial Building ◽  
Air Handling Unit ◽  
Operations And Maintenance ◽  
Detection And Diagnosis ◽  
Air Conditioning Systems ◽  
And Control

Air-conditioning systems consumed the most energy usage nearly 45% of the total energy used in commercial-building. Where AHU is one of the most extensively operated equipment and this device is typical customize and complex which can results in hardwire failure and controller errors. The efficiency of the system is very much depending on the proper functioning of sensors. Faults arising from the sensors and control systems are a major contribution to the energy wastage. As such faults often go unnoticed for extended periods of time until the deterioration in performance becomes great enough to trigger comfort complaints or total equipment failure. Energy could be reduced if those faults can be detected and identified at early stage. This paper aims to review of various existing automated fault detection and diagnosis (AFDD) methods for an Air Handling Unit. The background of AHU system, general fault detection and diagnosis framework and typical faults in AHU is described. Comparison and evaluation of the various methodologies will be reviewed in this paper. This comparative study also reveals the strengths and weaknesses of the different approaches. The important role of fault diagnosis in the broader context of air- conditioning is also outlined. By identifying and diagnosing faults to be repaired, these techniques can benefits building owners by reducing energy consumption, improving indoor air quality and operations and maintenance.

Simulation Research About Air Conditioning Load Calculation

2012 ◽  
Vol 433-440 ◽  
pp. 6023-6027
Author(s):  
Hui Fan Zheng ◽  
Ting Ting Xiao
Keyword(s):  
Air Conditioning ◽  
Cooling Load ◽  
Theory Analysis ◽  
Simulation Research ◽  
New Period ◽  
Simulation Calculation ◽  
Load Calculation ◽  
Calculation Point ◽  
History Of ◽  
Air Conditioning Systems

Theory analysis method is adopted in this paper to review the development history of air-conditioning loads calculation, point out that the air-conditioning loads calculation went through from steady calculation to periodic unsteady calculation and then to new period of dynamic load calculation. Simulation calculation of air-conditioning cooling load have been developed deeply, and many software can be used to calculate the hourly cooling load about building. At last, The application of neutral network for prediction of cooling load in air conditioning systems have been introduced.

scholarly journals Experimental Investigation of a Split Air Conditioning Using Condensate as Direct Evaporative Cooling

2021 ◽  
Vol 86 (1) ◽  
pp. 140-153
Author(s):  
Azridjal Aziz ◽  
Muhammad Rif’at Syahnan ◽  
Afdhal Kurniawan Mainil ◽  
Rahmat Iman Mainil
Keyword(s):  
Air Conditioning ◽  
Evaporative Cooling ◽  
Cooling Capacity ◽  
Coefficient Of Performance ◽  
Cooling Load ◽  
Air Conditioner ◽  
Direct Evaporative Cooling ◽  
Compressor Power ◽  
Discharge Pressure ◽  
Air Conditioning Systems

Split air conditioning systems produce reasonable amount of condensate which is usually not utilized and thrown away to the environment. On the other hand, it consumes a lot of energy during operation. The aim of this study is to investigate the improvement of air conditioning systems performance utilizing condensate. A direct evaporative cooling using condensate is incorporated on a 0.74 ton-cooling capacity of split air conditioning to decrease the air temperature before entering the condenser. Performances of the split air conditioning with and without direct evaporative cooling are compared and presented in this paper. The results show that the use of direct evaporative cooling using condensate into the air before passing through the condenser reduces the compressor discharge pressure. The decrease of the condenser pressure led to 4.7% and 7% reduction of power consumption for air conditioner without cooling load and air conditioner with 2000 W cooling load, respectively. The cooling effect and coefficient of performance (COP) increase with the decrease of compressor power. The use of direct evaporative cooling with condensate into the air before entering the condensing system can enhance the system performance and protect the environment.

Application of Genetic Programming Method Combined with Neural Network in HVAC Optimal Operation

2014 ◽  
Vol 548-549 ◽  
pp. 1030-1034 ◽  
Author(s):  
Ching Wei Chen ◽  
Yung Chung Chang ◽  
Wei Ting Liao ◽  
Cheng Wen Lee
Keyword(s):  
Genetic Programming ◽  
Power Consumption ◽  
Air Conditioning ◽  
Optimal Parameter ◽  
Optimal Operation ◽  
Cooling Load ◽  
Air Conditioning System ◽  
Minimum Power ◽  
Iterative Computation ◽  
Minimum Power Consumption

This study records the various air conditioning system parameters that affect power consumption and establishes system power consumption models for the chiller, the secondary chilled water pump, the air handling unit (AHU), and the cooling load of the AHU using artificial neural networks. The R2 for each of the models are as high as 0.996. Estimations for the AHU loads in the spaces where the cooling load for the AHU are satisfied and genetic programming is used to find the optimal air conditioning system parameter set for achieving minimum power consumption. These power consumption values are then set as genetic programming end points, and the mathematical symbol (+) is used as the functional ends. Finally, the computational elements of genetic programming are used to perform iterative computation. It may be concluded from the results of the experiment that the optimal parameter set obtained from the genetic programming-based search result in a minimum power consumption that complies with the loading requirements of the location of installation result in a 22% savings in term of power consumption and an average COP increase of approximately 28%, which represent very significant improvements.

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