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Andersson, Staffan
Publications (10 of 37) Show all publications
Feng, K., Lu, W., Penaka, S. R., Eklund, E., Andersson, S. & Olofsson, T. (2022). Energy-efficient retrofitting with incomplete building information: a data-driven approach. In: A. Li, T. Olofsson; R. Kosonen (Ed.), E3S web of conferences: . Paper presented at 16th ROOMVENT Conference (ROOMVENT 2022), Xi'an, China, 16-19 september, 2022.. EDP Sciences, 356, Article ID 01003.
Open this publication in new window or tab >>Energy-efficient retrofitting with incomplete building information: a data-driven approach
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2022 (English)In: E3S web of conferences / [ed] A. Li, T. Olofsson; R. Kosonen, EDP Sciences, 2022, Vol. 356, article id 01003Conference paper, Published paper (Refereed)
Abstract [en]

The high-performance insulations and energy-efficient HVAC have been widely employed as energy-efficient retrofitting for building renovation. Building performance simulation (BPS) based on physical models is a popular method to estimate expected energy savings for building retrofitting. However, many buildings, especially the older building constructed several decades ago, do not have full access to complete information for a BPS method. To address this challenge, this paper proposes a data-driven approach to support the decision-making of building retrofitting under incomplete information. The data-driven approach is constructed by integrating backpropagation neural networks (BRBNN), fuzzy C-means clustering (FCM), principal component analysis (PCA), and trimmed scores regression (TSR). It is motivated by the available big data sources from real-life building performance datasets to directly model the retrofitting performances without generally missing information, and simultaneously impute the case-specific incomplete information. This empirical study is conducted on real-life buildings in Sweden. The result indicates that the approach can model the performance ranges of energy-efficient retrofitting for family houses with more than 90% confidence. The developed approach provides a tool to predict the performance of individual buildings from different retrofitting measures, enabling supportive decision-making for building owners with inaccessible complete building information, to compare alternative retrofitting measures.

Place, publisher, year, edition, pages
EDP Sciences, 2022
Series
ROOMVENT Conference, ISSN 25550403, E-ISSN 22671242
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-204512 (URN)10.1051/e3sconf/202235601003 (DOI)2-s2.0-85146829162 (Scopus ID)
Conference
16th ROOMVENT Conference (ROOMVENT 2022), Xi'an, China, 16-19 september, 2022.
Funder
Swedish Research Council FormasEU, Horizon 2020
Available from: 2023-02-07 Created: 2023-02-07 Last updated: 2023-02-07Bibliographically approved
Nydahl, H., Andersson, S., Åstrand, A. P. & Olofsson, T. (2022). Extended building life cycle cost assessment with the inclusion of monetary evaluation of climate risk and opportunities. Sustainable cities and society, 76, Article ID 103451.
Open this publication in new window or tab >>Extended building life cycle cost assessment with the inclusion of monetary evaluation of climate risk and opportunities
2022 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 76, article id 103451Article in journal (Refereed) Published
Abstract [en]

The buildings and construction sector account for a significant part of the total energy use and related greenhouse gas emissions. However, climate change mitigation often becomes secondary or completely disregarded in building design assessment as the primary concern of building owners are economic tenability. Therefore, this study introduces an Extended Life Cycle Cost Assessment that include monetary evaluation of climate risk and opportunities in terms of Social Cost of Carbon (SCC). SCC could function as a tax to promote climate change mitigation within e.g. the construction industry. The purpose is to provide a more holistic assessment approach that is easy to relate to if economic tenability is of primary concern in decision making, which can be used to assess building design. Return on invested greenhouse gas emissions is used as an additional or standalone indicator for climate change mitigation. The introduced approach is exemplified by a case study where renovation and new construction are compared with keeping buildings in its original design. The case study show that with or without a flat greenhouse gas tax, renovation is the most climate and cost efficient alternative.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Transportation, Renewable Energy, Sustainability and the Environment, Civil and Structural Engineering, Geography, Planning and Development, Life cycle assessment, Greenhouse gas emission, Climate change mitigation, Social cost of carbon, Return on investment, Renovation, New construction
National Category
Engineering and Technology
Identifiers
urn:nbn:se:umu:diva-189854 (URN)10.1016/j.scs.2021.103451 (DOI)000723670200005 ()2-s2.0-85117806629 (Scopus ID)
Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2023-09-05Bibliographically approved
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
Nydahl, H., Andersson, S., Åstrand, A. P. & Olofsson, T. (2019). Environmental Performance Measures to Assess Building Refurbishment from a Life Cycle Perspective. Energies, 12(2), Article ID 299.
Open this publication in new window or tab >>Environmental Performance Measures to Assess Building Refurbishment from a Life Cycle Perspective
2019 (English)In: Energies, E-ISSN 1996-1073, Vol. 12, no 2, article id 299Article in journal (Refereed) Published
Abstract [en]

Energy efficiency investments in existing buildings are an effective way of reducing the environmental impact of the building stock. Even though policies in the European Union and elsewhere promote a unilateral focus on operational energy reduction, scientific studies highlight the importance of applying a life cycle perspective to energy refurbishment. However, life cycle assessment is often perceived as being complicated and the results difficult to interpret by the construction sector. There is also a lack of guidelines regarding the sustainable ratio between the embodied and accumulated operational impact. The scope of this study is to introduce a life cycle assessment method for building refurbishment that utilizes familiar economic performance tools, namely return on investment and annual yield. The aim is to use the introduced method to analyze a case building with a sustainability profile. The building was refurbished in order to reduce its operational energy use. The introduced method is compatible with a theory of minimum sustainable environmental performance that may be developed through backcasting from defined energy and GHG emissions objectives. The proposed approach will hopefully allow development of sustainable refurbishment objectives that can support the choice of refurbishment investments.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
building refurbishment; Life Cycle Assessment (LCA); Return on Investment (ROI); Annual Yield (AY); Environmental Performance Measure (EPM); Greenhouse Gas (GHG) reduction
National Category
Building Technologies
Research subject
sustainability
Identifiers
urn:nbn:se:umu:diva-155666 (URN)10.3390/en12020299 (DOI)000459743700100 ()2-s2.0-85060557787 (Scopus ID)
Available from: 2019-01-25 Created: 2019-01-25 Last updated: 2023-08-28Bibliographically approved
Nydahl, H., Andersson, S., Åstrand, A. P. & Olofsson, T. (2019). Including future climate induced cost when assessing building refurbishment performance. Energy and Buildings, 203, Article ID 109428.
Open this publication in new window or tab >>Including future climate induced cost when assessing building refurbishment performance
2019 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 203, article id 109428Article in journal (Refereed) Published
Abstract [en]

Improving energy efficiency in the existing buildings stock is essential to limit climate change and the economic assessment of measures are traditionally only based on the reduction of energy costs: However, future financial benefits of limiting climate change are rarely included in the evaluation of refurbishment investments. Although, the costs associated with global warming are expected to be extensive. This study introduces a method for the financial evaluation of energy efficiency investments that merge the reduction of life cycle energy costs with the reduction of future climate induced costs. A case study is used to exemplify the method. The case study shows that when reduced future costs due to mitigated life cycle greenhouse gas emissions are included in the analysis, the ranking between different measures can change and traditionally non-profitable measures may become financially sound investments. The introduced Economy+ indicator is shown to be an accessible performance measure to assess building refurbishment and may also be used in the design stage of new construction. (C) 2019 The Authors. Published by Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Life cycle assessment, Building refurbishment, Global warming, Climate induced damage cost, Climate impact discount rate
National Category
Environmental Analysis and Construction Information Technology
Identifiers
urn:nbn:se:umu:diva-165739 (URN)10.1016/j.enbuild.2019.109428 (DOI)000496335500025 ()2-s2.0-85072858941 (Scopus ID)
Available from: 2019-12-10 Created: 2019-12-10 Last updated: 2023-03-24Bibliographically 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
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