scholarly journals Field Measurements of Heating System Efficiency in Nine Electrically-Heated Manufactured Homes.

1996 ◽  
Author(s):  
Bob Davis ◽  
J. Siegel ◽  
L. Palmiter ◽  
D. Baylon
Keyword(s):  
Field Measurements ◽  
Heating System ◽  
System Efficiency ◽  
Manufactured Homes

Indoor hygrothermal loads for the deterministic and stochastic design of the building envelope for dwellings in cold climates

2017 ◽  
Vol 41 (6) ◽  
pp. 547-577 ◽  
Author(s):  
Simo Ilomets ◽  
Targo Kalamees ◽  
Juha Vinha
Keyword(s):  
Field Measurements ◽  
Heating System ◽  
Building Envelope ◽  
Cold Climates ◽  
Outdoor Temperature ◽  
Change Rate ◽  
Levels Of Detail ◽  
Air Change Rate ◽  
Excess Value ◽  
Occupancy Rates

In this study, several years of field measurements of indoor hygrothermal loads in 237 dwelling units are analysed. Moisture excess is calculated from hourly values of temperature, and relative humidity measured both indoors and outdoors. Air change rate and moisture production in bedrooms are calculated on the basis of carbon dioxide measurements. It is found that indoor temperature profiles differ depending on whether a building has central heating, a stove or combined heating system. The determined average moisture excess value, 2.8 g/m3 with a standard deviation of 1.6 g/m3 for cold periods, can be used in stochastic calculations. Critical values for moisture excess at the 90th percentile, ranging from 3–8 g/m3, depending upon occupancy rates, can be used in the deterministic analysis. Averages and weekly maxima of moisture excess in the study are reported at different percentiles. Considerable deviations from the EN ISO 13788 standard are discovered, concerning the breaking point depending on outdoor temperature and moisture excess during the summer. The average and critical moisture production in bedroom is presented and insufficient ventilation determined based on measurements. During the heating period, the air change rate is relatively stable while moisture production levels increase along with the dropping outdoor temperature. Two indoor temperatures and three humidity models with different levels of detail and influencing factors are proposed. Temperature and humidity loads derived using the proposed models can be used to determine the indoor hygrothermal boundary conditions for the building envelope of dwellings in cold climates.

Analysis of Operating Condition on a Solar Direct Heating

2013 ◽  
Vol 838-841 ◽  
pp. 1959-1962
Author(s):  
Xi Ming Zhang ◽  
Xue Li
Keyword(s):  
Room Temperature ◽  
Rapid Development ◽  
Clean Energy ◽  
Heating System ◽  
Development Research ◽  
System Efficiency ◽  
Average Amount ◽  
Operation Conditions ◽  
Direct Operation ◽  
The Mean

Solar energy is a clean energy, nowadays promoting environmental protection and energy conservation. Solar technology has been rapid development. Research group develop solar heat pump heating system. Solar heating was carried out in direct operation conditions. During the test, the average amount of solar radiation during the day is 47.7kWh and the average of the heat collection is 22.41kWh. Power consumption of system changes between 8.46kWh and 8.52kWh and the mean is 8.49kWh. The average of system efficiency is 0.35. During the test, room temperature meets the requirements.

scholarly journals Assessment of Using Heat Pumps for Heating in Mobile Homes: A Case Study from North Carolina

2009 ◽  
Vol 4 (3) ◽  
pp. 135-142
Author(s):  
Hussein Abaza
Keyword(s):  
North Carolina ◽  
Thermal Comfort ◽  
Low Income ◽  
Field Measurements ◽  
Heating System ◽  
Heat Pumps ◽  
Mobile Homes ◽  
Indoor Thermal Comfort ◽  
The North ◽  
Low Income Families

This paper presents the results of “Upgrade and Save”, a program to upgrade the standard electric furnaces and air-conditioning units in Mobile Homes for energy-efficient heat pumps. This program is implemented in North Carolina, USA and pays about $700 through a rebate provided by the North Carolina State Energy Office to the Mobile Homes' owners. The goal of this project is to subsidize low-income families by lowering their heating cost in the winter as well as improving their homes' indoor thermal comfort. More than 300 mobile homes have participated in this program. Field measurements, meter readings of the actual electrical consumption, and annual building energy simulation were used to measure the dollar saving and the indoor thermal comfort improvement in the mobile homes after the heating system upgrade. This research proved that the dollar saving of using the heat pump for heating in mobile homes ranges from $51 to $128 annually.

Estimating the Effects of Environmental Conditions on Active Solar Wall Air Heating System Efficiency

2015 ◽  
Vol 141 (3) ◽  
pp. 04014008
Author(s):  
Snezana M. Dragicevic ◽  
Miroslav R. Lambic ◽  
Jasmina M. Radosavljevic ◽  
Miomir T. Raos
Keyword(s):  
Environmental Conditions ◽  
Heating System ◽  
System Efficiency ◽  
Air Heating ◽  
Solar Wall

scholarly journals Numerical Analysis for Performance Evaluation of a Multi-Functional CO2 Heat Pump Water Heating System

2018 ◽  
Vol 8 (10) ◽  
pp. 1829 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Masashi Ohkura ◽  
Takuya Nakamata ◽  
Tetsuya Wakui
Keyword(s):  
Heat Pump ◽  
System Performance ◽  
Storage Tank ◽  
Heating System ◽  
Functional System ◽  
Hot Water ◽  
System Efficiency ◽  
Water Heating ◽  
Perfect Mixing ◽  
Component Models

In recent years, CO2 heat pump water heating systems have been developed, and their performances have been enhanced while their functions have been expanded. In a multi-functional system, used for both hot water supply and bath heating, hot water retrieved from the top of a storage tank is returned to its bottom or side after heat exchange for bath heating, which destroys the stratified temperature distribution in the storage tank and degrades the system performance. In this paper, the performance of a multi-functional CO2 heat pump water heating system has been evaluated by numerical simulation. A system model was created by combining component models for a CO2 heat pump, mixing valves, a storage tank, a heat exchanger, and a bathtub. Partly, perfect mixing by hot water return was assumed in the component model for the storage tank, and its validity was verified through experiments. A performance analysis has been conducted under daily repeated hot water and bath heating demands, and the system performance was evaluated at a periodically steady state. As a result, the system efficiency and the volume of unused hot water in the multi-functional system decreased by 4.9% and 16.3%, respectively, as compared to those in the uni-functional system, when hot water returned to the bottom of the storage tank. When the position for hot water return is heightened, the system efficiency becomes higher than that in the uni-functional system, while the volume of unused hot water decreases furthermore.

scholarly journals Application of Regression and ANN Models for Heat Pumps with Field Measurements

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1750
Author(s):  
Anjan Rao Puttige ◽  
Staffan Andersson ◽  
Ronny Östin ◽  
Thomas Olofsson
Keyword(s):  
Field Measurements ◽  
Heating System ◽  
Heat Pumps ◽  
Measured Data ◽  
Ann Model ◽  
Heating Systems ◽  
Ann Models ◽  
Using Data ◽  
Artificial Neural Network Ann ◽  
Relative Root

Developing accurate models is necessary to optimize the operation of heating systems. A large number of field measurements from monitored heat pumps have made it possible to evaluate different heat pump models and improve their accuracy. This study used measured data from a heating system consisting of three heat pumps to compare five regression and two artificial neural network (ANN) models. The models’ performance was compared to determine which model was suitable during the design and operation stage by calibrating them using data provided by the manufacturer and the measured data. A method to refine the ANN model was also presented. The results indicate that simple regression models are more suitable when only manufacturers’ data are available, while ANN models are more suited to utilize a large amount of measured data. The method to refine the ANN model is effective at increasing the accuracy of the model. The refined models have a relative root mean square error (RMSE) of less than 5%.

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