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Östin, Ronny, UniversitetslektorORCID iD iconorcid.org/0000-0001-6400-7744
Alternative names
Biography [swe]

Fokus för min forskning är energieffektivisering i bostäder och lokaler baserat på omfattande realtids-mätningar och därpå baserade analyser.

Publications (10 of 30) Show all publications
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2022). Modeling and optimization of hybrid ground source heat pump with district heating and cooling. Energy and Buildings, 264, Article ID 112065.
Open this publication in new window or tab >>Modeling and optimization of hybrid ground source heat pump with district heating and cooling
2022 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 264, article id 112065Article in journal (Refereed) Published
Abstract [en]

Hybrid heating systems with ground source heat pumps (GSHP) and district heating and cooling offer flexibility in operation to both building owners and energy providers. The flexibility can be used to make the heating system more economical and environmentally friendly. However, due to the lack of suitable models that can accurately predict the long-term performance of the GSHP, there is uncertainty in their performance and concerns about the long-term stability of the ground temperature, which has limited the utilization of such hybrid heating systems. This work presents a hybrid model of a GSHP system that uses analytical and artificial neural network models to accurately represent a GSHP system's long-term behavior. A method to improve the operation of a hybrid GSHP is also presented. The method was applied to hospital buildings in northern Sweden. It was shown that in the improved case, the cost of providing heating to the building can be reduced by 64 t€, and the CO2 emissions can be reduced by 92 tons while maintaining a stable ground temperature.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Ground source heat pump, district heating and cooling, optimization, borehole heat exchanger, artificial neural network, hybrid model
National Category
Energy Engineering Energy Systems
Identifiers
urn:nbn:se:umu:diva-187767 (URN)10.1016/j.enbuild.2022.112065 (DOI)000800424900007 ()2-s2.0-85127325610 (Scopus ID)
Note

Originally included in thesis in manuscript form. 

Available from: 2021-09-21 Created: 2021-09-21 Last updated: 2023-09-05Bibliographically approved
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2021). Application of Regression and ANN Models for Heat Pumps with Field Measurements. Energies, 14(6), Article ID 1750.
Open this publication in new window or tab >>Application of Regression and ANN Models for Heat Pumps with Field Measurements
2021 (English)In: Energies, E-ISSN 1996-1073, Vol. 14, no 6, article id 1750Article in journal (Refereed) Published
Abstract [en]

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%

Place, publisher, year, edition, pages
MDPI, 2021
Keywords
heat pump, artificial neural network, regression model, modeling, field measurements
National Category
Energy Engineering
Identifiers
urn:nbn:se:umu:diva-181746 (URN)10.3390/en14061750 (DOI)000634408500001 ()2-s2.0-85107949313 (Scopus ID)
Available from: 2021-03-23 Created: 2021-03-23 Last updated: 2023-09-05Bibliographically approved
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2020). A Novel Analytical-ANN Hybrid Model for Borehole Heat Exchanger. Energies, 13(23), Article ID 6213.
Open this publication in new window or tab >>A Novel Analytical-ANN Hybrid Model for Borehole Heat Exchanger
2020 (English)In: Energies, E-ISSN 1996-1073, Vol. 13, no 23, article id 6213Article in journal (Refereed) Published
Abstract [en]

Optimizing the operation of ground source heat pumps requires simulation of both short-term and long-term response of the borehole heat exchanger. However, the current physical and neural network based models are not suited to handle the large range of time scales, especially for large borehole fields. In this study, we present a hybrid model for long-term simulation of BHE with high resolution in time. The model uses an analytical model with low time resolution to guide an artificial neural network model with high time resolution. We trained, tuned, and tested the hybrid model using measured data from a ground source heat pump in real operation. The performance of the hybrid model is compared with an analytical model, a calibrated analytical model, and three different types of neural network models. The hybrid model has a relative RMSE of 6% for the testing period compared to 22%, 14%, and 12% respectively for the analytical model, the calibrated analytical model, and the best of the three investigated neural network models. The hybrid model also has a reasonable computational time and was also found to be robust with regard to the model parameters used by the analytical model.

Place, publisher, year, edition, pages
MDPI, 2020
Keywords
borehole heat exchanger, ground source heat pump, analytical model, artificial neural network, hybrid model, monitored data
National Category
Energy Engineering
Identifiers
urn:nbn:se:umu:diva-177259 (URN)10.3390/en13236213 (DOI)000597739700001 ()2-s2.0-85106429863 (Scopus ID)
Available from: 2020-12-03 Created: 2020-12-03 Last updated: 2023-08-28Bibliographically approved
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2020). Improvement of borehole heat exchanger model performance by calibration using measured data. Journal of Building Performance Simulation, Taylor & Francis, 13(4), 430-442
Open this publication in new window or tab >>Improvement of borehole heat exchanger model performance by calibration using measured data
2020 (English)In: Journal of Building Performance Simulation, Taylor & Francis, ISSN 1940-1493, E-ISSN 1940-1507, Vol. 13, no 4, p. 430-442Article in journal (Refereed) Published
Abstract [en]

Planning the operation of large ground source heat pump (GSHP) systems requires accurate models of borehole heat exchangers (BHEs) that are not computationally intensive. In this paper, we propose parameter estimation using measured data as a method to improve the analytical models of BHE. The method was applied to a GSHP system operating for over 3 years. The deviation between modelled and measured load of the BHE reduced from 22% to 14%. Influence of the calibration data set was tested by changing time resolution and season of the calibration data. We concluded that the time resolution must be high enough to differentiate among the effects of different parameters and that different model parameters must be used for injection and extraction (seasons). The method was also applied to a GSHP that has been monitored for 10 years, which showed that accuracy of the model can be improved by annual updates of parameters.

Place, publisher, year, edition, pages
Taylor & Francis, 2020
Keywords
Parameter estimation, calibration, borehole heat exchanger, analytical models, monitored, ground source heat pump
National Category
Energy Engineering
Identifiers
urn:nbn:se:umu:diva-171501 (URN)10.1080/19401493.2020.1761451 (DOI)000535339500001 ()2-s2.0-85085262854 (Scopus ID)
Available from: 2020-06-03 Created: 2020-06-03 Last updated: 2023-03-24Bibliographically approved
Östin, R. & Nair, G. (2019). Energy performance and lessons learned from detailed measurement of a passive house preschool in cold climate. In: Is efficient sufficient?: eceee 2019 Summer Study on energy efficiency: Abstracts. Paper presented at European Council for an Energy Efficient Economy (ECEEE), France, June 3-8, 2019. (pp. 1433-1442). European Council for an Energy Efficient Economy (ECEEE)
Open this publication in new window or tab >>Energy performance and lessons learned from detailed measurement of a passive house preschool in cold climate
2019 (English)In: Is efficient sufficient?: eceee 2019 Summer Study on energy efficiency: Abstracts, European Council for an Energy Efficient Economy (ECEEE), 2019, p. 1433-1442Conference paper, Published paper (Refereed)
Abstract [en]

Public passive house buildings are rare in high northern latitudes. This study reports on extensive measurements and evaluations of the most northerly (640 N) built passive house preschool in Sweden. The two storied preschool, built in 2014, has a total heated floor area of 1407 m2. The building was certified according to the international passive house standard. The building has several smart solutions such as demand controlled ventilation of individual rooms and automatic solar shading system.

Energy measurements conducted during 2017-2018 showed that the preschool annually uses 44.4 kWhm-2, which is approximately 25 % lower than the passive house requirement for energy demand. However, the annual specific space heating requirement of 15 kWhm-2 and the peak heat power demand of 10 Wm-2 were not fulfilled. This non-compliance was mainly due to excessive ventilation during the heating season which was found to have 2.7 times higher air changes than the requirement in the Swedish building code. Furthermore, the building was found to be over heated from the sun during several occasions in a year. For example, excessive indoor air temperatures in the range 28 – 31°C were found during summer.

The study revealed that the default winter operation by turning off the ventilation system during nights and weekends is continued in other seasons as well. This practice was not a “smart” approach for the air handling units as it was found to be one of the reasons for high indoor temperatures during non-winter months. Also, a mismatch between the operation of the automatic shading device and the ventilation control units was noted.

The investigation shows that smart technical solutions in buildings may not be able to deliver its’ promised results if such systems are not monitored, adjusted and carefully evaluated. The paper identifies areas that need attention to ensure that a public building built to passive house standard actually deliver the energy efficiency it promises.

Place, publisher, year, edition, pages
European Council for an Energy Efficient Economy (ECEEE), 2019
Series
Ecee Summer Study Proceedings, ISSN 1653-7025, E-ISSN 2001-7960
Keywords
passive houses, energy measurement, building energy certification, energy efficiency action plans
National Category
Energy Systems
Identifiers
urn:nbn:se:umu:diva-159707 (URN)978-91-983878-0-3 (ISBN)978-91-983878-1-0 (ISBN)
Conference
European Council for an Energy Efficient Economy (ECEEE), France, June 3-8, 2019.
Available from: 2019-06-04 Created: 2019-06-04 Last updated: 2019-06-13Bibliographically approved
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2019). Method to estimate the ground loads for missing periods in a monitored GSHP. In: EUROPEAN GEOTHERMAL CONGRESS 2019: THE HAGUE, 11-14 JUNE 2019. Paper presented at European Geothermal Congress, The Hague, The Netherlands, June 11-14, 2019.
Open this publication in new window or tab >>Method to estimate the ground loads for missing periods in a monitored GSHP
2019 (English)In: EUROPEAN GEOTHERMAL CONGRESS 2019: THE HAGUE, 11-14 JUNE 2019, 2019Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Monitoring a ground source heat pump can provide important insights into its working, but to study the behaviour of the borehole heat exchanger (BHE) we require monitored data for the whole period of operation. In practice, the monitored data often has periods of missing data. We propose a method to estimate the load during the periods of missing data based on the fluid temperature after that period. The method determined the missing load with negligible error, for the case of a BHE that behaves exactly like the model describing it. A sensitivity analysis showed that the estimated load is highly sensitive to errors in measured load and fluid temperature. The method was applied to a real monitored BHE, the magnitude of estimated loads were unreasonably high, but the overall deviation between the measured and simulated values of fluid temperature decreased. Therefore, the high magnitude of missing load compensates for the lack of agreement between the model and the measured data.

Keywords
ground source heat pump, borehole heat exchanger, monitored, missing loads.
National Category
Energy Engineering
Identifiers
urn:nbn:se:umu:diva-160966 (URN)
Conference
European Geothermal Congress, The Hague, The Netherlands, June 11-14, 2019
Available from: 2019-06-26 Created: 2019-06-26 Last updated: 2019-06-27Bibliographically approved
Puttige, A. R., Andersson, S., Östin, R. & Olofsson, T. (2019). Method to estimate the ground loads for missing periods in a monitored GSHP. In: European Geothermal Congress 2019: . Paper presented at European Geothermal Congress 2019 Den Haag, The Netherlands, June 11-14, 2019.
Open this publication in new window or tab >>Method to estimate the ground loads for missing periods in a monitored GSHP
2019 (English)In: European Geothermal Congress 2019, 2019Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Monitoring a ground source heat pump can provide important insights into its working, but to study the behaviour of the borehole heat exchanger (BHE) we require monitored data for the whole period of operation. In practice, the monitored data often has periods of missing data. We propose a method to estimate the load during the periods of missing data based on the fluid temperature after that period. The method determined the missing load with negligible error, for the case of a BHE that behaves exactly like the model describing it. A sensitivity analysis showed that the estimated load is highly sensitive to errors in measured load and fluid temperature. The method was applied to a real monitored BHE, the magnitude of estimated loads were unreasonably high, but the overall deviation between the measured and simulated values of fluid temperature decreased. Therefore, the high magnitude of missing load compensates for the lack of agreement between the model and the measured data.

Keywords
ground source heat pump, borehole heat exchanger, monitored, missing loads
National Category
Energy Engineering
Identifiers
urn:nbn:se:umu:diva-161118 (URN)
Conference
European Geothermal Congress 2019 Den Haag, The Netherlands, June 11-14, 2019
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-28Bibliographically approved
Brembilla, C., Östin, R., Soleimani-Mohseni, M. & Olofsson, T. (2019). Paradoxes in understanding the Efficiency Factors of Space Heating. Energy Efficiency, 12(3), 777-786
Open this publication in new window or tab >>Paradoxes in understanding the Efficiency Factors of Space Heating
2019 (English)In: Energy Efficiency, ISSN 1570-646X, E-ISSN 1570-6478, Vol. 12, no 3, p. 777-786Article in journal (Refereed) Published
Abstract [en]

Efficiency factors are here defined as the thermal energy performance indicators of the space heating. Until recently, the efficiency factors were assumed as one value for space heating located in any climate. This study addresses the problem of how the outdoor climate affects the efficiency factors of a space heating equipped with 1D model of hydronic floor heating. The findings show how the efficiency factors, computed with two numerical methods, are correlated with the solar radiation. This study highlights the paradoxes in understanding the results of efficiency factors analysis. This work suggests how to interpret and use the efficiency factors as a benchmark performance indicator.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Efficiency factors, Space heating, Accuracy 1D model of hydronic floor heating, Outdoor climate, Performance indicator, Solar radiation, Benchmark, Linear regression model
National Category
Building Technologies
Research subject
engineering science with specialization in microsystems technology
Identifiers
urn:nbn:se:umu:diva-149931 (URN)10.1007/s12053-018-9692-y (DOI)000461106400015 ()2-s2.0-85049553312 (Scopus ID)
Projects
Reliability and robustness of efficiency factors theory of the space heating equipped with hydronic technologies
Available from: 2018-06-29 Created: 2018-06-29 Last updated: 2019-04-04Bibliographically approved
Brembilla, C., Renman, R., Soleimani-Mohseni, M., Östin, R. & Olofsson, T. (2019). The impact of control strategies on space heating system efficiency in low-energy buildings. Building Services Engineering Research & Technology, 40(6), 714-731
Open this publication in new window or tab >>The impact of control strategies on space heating system efficiency in low-energy buildings
Show others...
2019 (English)In: Building Services Engineering Research & Technology, ISSN 0143-6244, E-ISSN 1477-0849, Vol. 40, no 6, p. 714-731Article in journal (Refereed) Published
Abstract [en]

In this study efficiency factors measures the thermal energy performance for space heating. This study deals with the influence of control strategies on the effriciency factors of space heating and its distribution system. An adaptive control is developed and applied to two types of heating curves (linear and non-linear) for a low-energy building equipped with renewable energy sources. The building is modelled with a hybrid approach (law driven + data driven model). The design of the floor heating is calibrated and validated by assessing the uncertainty bands for low temperatures and mass flow rate. advantages and disavantages of linear and non-linear heating curves are highlighted to illustrate their impact on space heating thermodynamic behaviour and on the efficiency factors of the space heating system.

Practical application: The study reveals that applying commercial building energy simulation software  is worthwhile to determine reliable performance predictions. Oversimplified building models, in particular when considering building thermal mass, are not capable of simulating the thermodynamic response of a building subjected to different control strategies. The application of different heating cuirves (linear and non-linear) to massless building models leaves the amount of mass flow rate delivered to the space heating unchanged when the building is subjected to sharp variations of the outdoor temperature.

Place, publisher, year, edition, pages
London: Sage Publications, 2019
Keywords
Efficiency factors of space heating and distribution system, Calibration through uncertainty bands, Hybrid model of low-energy building: law-driven + data-driven model, Outdoor temperature compensation or heating curve, Feedback and feed-forward control loop + adaptive control, Solar radiation model
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-151980 (URN)10.1177/0143624418822454 (DOI)000491440700005 ()2-s2.0-85060767454 (Scopus ID)
Available from: 2018-09-21 Created: 2018-09-21 Last updated: 2019-12-19Bibliographically approved
Brembilla, C., Östin, R. & Olofsson, T. (2018). Predictions' robustness of one-dimensional model of hydronic floor heating: novel validation methodology using a thermostatic booth simulator and uncertainty analysis. Journal of Building Physics, 41(5), 418-444
Open this publication in new window or tab >>Predictions' robustness of one-dimensional model of hydronic floor heating: novel validation methodology using a thermostatic booth simulator and uncertainty analysis
2018 (English)In: Journal of Building Physics, ISSN 1744-2591, E-ISSN 1744-2583, Vol. 41, no 5, p. 418-444Article in journal, Editorial material (Refereed) Published
Abstract [en]

Hydronic floor heating models provide predictions in estimating heat transfer rates and floor surface temperature. Information on the model performance and range of validity of its results are often lacking in literature. Researchers have to know the accuracy and robustness of the model outcomes for performing energy and climate comfort calculations. This article proposes a novel validation methodology based on the uncertainty analysis of input data/parameters of one-dimensional model of hydronic floor heating tested in a thermostatic booth simulator and compared with experimental measurements. The main results are: (1) prediction accuracy between 0.4% and 2.9% for Tf and between 0.7% and 7.8% for qup when the serpentine has tube spacing (p) of 0.30 m, (2) prediction accuracy between 0.5% and 1.4% for Tf and between 8.7% and 12.9% for qup with p = 0.15m and (3) Tfld mostly affects predictions with oscillations between 6.2% and 2.2% for qup. This model provides robust and reliable predictions exclusively for qup when p = 0.30m.

Place, publisher, year, edition, pages
Sage Publications, 2018
Keywords
One-Dimensional model of hydronic floor heating, thermostatic booth simulator, validation methodology, uncertainty bands, differential sensitivity analysis, robustness of model's predictions
National Category
Building Technologies
Research subject
Physics
Identifiers
urn:nbn:se:umu:diva-136486 (URN)10.1177/1744259117721002 (DOI)000429862600002 ()2-s2.0-85043324831 (Scopus ID)
Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2023-03-24Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6400-7744

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