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  • 1.
    Brembilla, Christian
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Lacoursiere, Claude
    High Performance Compting Center North (HPC2N), Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Investigations of thermal parameters addressed to a building simulation model2015In: Proceedings of BS2015: 14th Conference of International Building Performance Simulation Association, Hyderabad, India, Dec. 7-9, 2015, India, Hyderabad: International Building Performance Simulation Association (IBPSA) , 2015, p. 2741-2748Conference paper (Refereed)
    Abstract [en]

    This paper shows the tolerance of thermal parameters addressed to a building simulation model in relation to the local control of the HVAC system. This work is suitable for a modeler that has to set up a building simulation model. The modeler has to know which parameter needs to be considered carefully and vice-versa which does not need deep investigations. Local differential sensitivity analysis of thermal parameters generates the uncertainty bands for the indoor air. The latter operation is repeated with P, PI and PID local control of the heating system. In conclusion, the local control of a room has a deterministic impact on the tolerance of thermal parameters.

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  • 2.
    Brembilla, Christian
    et al.
    Umeå University, Umeå, Sweden.
    Renman, Ronny
    Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Umeå University, Umeå, Sweden.
    Östin, Ronny
    Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Umeå University, Umeå, Sweden.
    The impact of control strategies on space heating system efficiency in low-energy buildings2019In: Building Services Engineering Research & Technology, ISSN 0143-6244, E-ISSN 1477-0849, Vol. 40, no 6, p. 714-731Article in journal (Refereed)
    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. © The Chartered Institution of Building Services Engineers 2019

  • 3.
    Brembilla, Christian
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Hybrid heating system for open-space office/laboratory2015In: Energy, Science and Technology 2015: The energy conference for scientists and researchers. Book of Abstracts, EST, Energy Science Technology, International Conference & Exhibition, 20-22 May 2015, Karlsruhe, Germany / [ed] Karlsruher Institut für Technologie (KIT), Karlsruhe: Karlsruher Institut für Technologie (KIT) , 2015, p. 315-315Conference paper (Refereed)
    Abstract [en]

    Open-space office/laboratory are quite common in Scandinavia and they are usually designed for multipurpose work. There are office area where is possible to work standing up and in the same time to work at the desk. For this purpose a hybrid heating system made by electric convectors and panel radiators is investigated. Two step response tests of the hybrid heating system are performed at the laboratory of Umeå University. The first test is executed during the week, disturbances from heat sources degrading the quality of the results. The second test is performed during week-end. The error analysis shows a maximum discrepancies of +0.6 °C between measured and simulated data. However, a thermal time constant of the room can be deducted and use it for controlling purposes.

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  • 4.
    Brembilla, Christian
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Transient model of a panel radiator2015In: Proceedings of BS2015: 14th Conference of International Building Performance Simulation Association, Hyderabad, India, Dec. 7-9, 2015, India, Hyderabad: International Building Performance Simulation Association (IBPSA) , 2015, p. 2749-2756Conference paper (Refereed)
    Abstract [en]

    This paper shows a transient model of a hydronic panel radiator modelled as a system of multiple storage elements. The experiment´s results suggest the more suitable technique for modelling this technology. The panel radiator is modelled numerically with eight thermal capacitance connected in series by keeping a memory of the heat injected in the thermal unit. The comparison of the performance among lumped steadystate models and transient model, in terms of heat emission and temperature of exhaust flow, shows the potential of the latter approach. To conclude, (1) the transient phase is essential for modelling stocky panels, and (2) this type of modelling has to be addressed for evaluating the performance of low energy buildings.

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  • 5.
    Brembilla, Christian
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Transient model of a panel radiator2015In: Energy, Science and Technology 2015: The energy conference for scientists and researchers. Book of Abstracts, EST, Energy Science Technology, International Conference & Exhibition, 20-22 May 2015, Karlsruhe, Germany / [ed] Karlsruher Institut für Technologie (KIT), Karlsruhe: Karlsruher Institut für Technologie (KIT) , 2015, p. 321-321Conference paper (Refereed)
    Abstract [en]

    This paper shows a detailed transient model of a panel radiator considered as a system of multiple storage elements. The experiment records the temperature surface of the panel in the process of heating up. The qualitative results of the experiment suggest the more appropriate technique for modelling this technology. The transient model performs the modelling with horizontal thermal capacitances connected in series. This model calculates the temperature of exhaust flow, heat emission towards indoor environment, temperature gradient on panel surface, dead and balancing time identified numerically on the chart.

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  • 6.
    Brembilla, Christian
    et al.
    Department of Applied Physics and Electronics (TFE), Umeå University, Umeå, Sweden.
    Östin, Ronny
    Department of Applied Physics and Electronics (TFE), Umeå University, Umeå, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Applied Physics and Electronics (TFE), Umeå University, Umeå, Sweden.
    Olofsson, Thomas
    Department of Applied Physics and Electronics (TFE), Umeå University, Umeå, Sweden.
    Paradoxes in understanding the Efficiency Factors of Space Heating2019In: Energy Efficiency, ISSN 1570-646X, E-ISSN 1570-6478, Vol. 12, no 3, p. 777-786Article in journal (Refereed)
    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.

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  • 7.
    Gustafsson, Anders
    et al.
    RISE, Göteborg, Sverige.
    Östman, Leif
    Yrkeshögskolan Novia, Vasa, Finland.
    Andersson, Allan
    RISE, Göteborg, Sverige.
    Dahlbäck, Yvonne
    Yrkeshögskolan Novia, Vasa, Finland.
    Borg, Anders
    RISE, Göteborg, Sverige.
    Soleimani-Mohseni, Mohsen
    Umeå universitet, Umeå, Sverige.
    Trä på betong2015In: Bygg och Teknik, ISSN 0281-658X, E-ISSN 2002-8350, no 2, p. 62-67Article in journal (Other academic)
  • 8.
    Jardeby, Åsa
    et al.
    Sveriges forskningsinstitut och innovationspartner (RISE), Göteborg, Sverige.
    Soleimani-Mohseni, Mohsen
    Sveriges forskningsinstitut och innovationspartner (RISE), Göteborg, Sverige.
    Axell, Monica
    Sveriges forskningsinstitut och innovationspartner (RISE), Göteborg, Sverige.
    Distribution av kyla och värme i bostäder och lokaler2009Report (Other academic)
  • 9.
    Sandberg, Karin
    et al.
    RISE, Skellefteå, Sweden.
    Gustafsson, Anders
    RISE, Skellefteå, Sweden.
    Pousetté, Anna
    RISE, Skellefteå, Sweden.
    Norén, Joakim
    RISE, Stockholm, Sweden.
    Soleimani-Mohseni, Mohsen
    Umeå universitet, Umeå, Sweden.
    Renovation of an office building with prefabricated wooden element – case Hedensbyn2018In: Cold Climate HVAC 2018: Sustainable Buildings in Cold Climates / [ed] Dennis Johansson; Hans Bagge; Åsa Wahlström, Cham: Springer, 2018, p. 587-598Conference paper (Refereed)
    Abstract [en]

    There is a major need of cost-effective renovation that leads to lower energy consumption and better environment. This article shows the results from a pilot case of a newly developed prefabricatedbuilding system. It is an industrially prefabricated insulated wooden element adapted to renovationand upgrading of building envelopes. The renovated building is a one-story office building located in Skellefted in the north of Sweden. Energy performance, thermal bridges, risk of moisture problems, LCA, applicability of the renovation method and assembly time were evaluated during the planning and execution of the renovation. Results from this case show that the elements were very light and easy for one person to handle at the building site. There is a great potential to reduce assembly time with improved joints and element sizes adapted to the building as well as improved batch packaging from the factory. With 100 mm insulation, the renovation gives a certain energy savings, and LCA calculations show that the reduction of climate impact due to reduced heating energy used during a service life 50 years corresponds to the climate impact of the renovation measures. The risk ofmicrobial growth can be regarded as small.

  • 10.
    Soleimani Mohseni, Mohsen
    Chalmers University of technology.
    Modelling and Intelligent Climate Control of Buildings2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The main purpose of the work presented in this thesis is to examine the possibilities of different control techniques together with intelligent building technology to improve the indoor climate and/or the energy efficiency of buildings. In particular, the possibilities of measuring more variables and using them as input to the controllers are examined. The first part of the thesis deals with different ways to obtain dynamic models for climate systems in buildings. A large part of the thesis then deals with the feed-forward control strategy and how it affects the indoor climate and the energy use. The main conclusion, drawn from the simulations in this part is that a more extensive use of feed-forward from internal disturbances could be very advantageous in many temperature-control applications. It gives better controller performance, and, at the same time, it will often reduce the energy use. Different controllers (P, PI, PID and ON/OFF with and without dead-band) used for indoor climate control are also investigated in this thesis. The results show that simple controllers like an ON/OFF controller with dead-band or a P-controller often performs better than more advanced controllers in many temperature-control applications. Similar types of controllers have also been investigated when they are used in a demand-control ventilation (DCV) system. The results show that there is a large potential of reducing the outdoor air flow rate by using a DCV-system instead of a base/forced ventilation system. However, the differences between different controllers in a DCV-system are of less importance in these systems. A large part of this thesis is about the problem how to develop mathematical models for prediction of the indoor temperature using linear models as well as non-linear artificial neural network (ANN) models. The results show that neural network models give more accurate predictions of indoor temperature than linear models. ANN-models have also been used for estimation of the operative temperature in buildings. It is shown that the operative temperature can be estimated fairly well by using variables which are more easily measured and that ANN-models give better estimations than linear models. Finally, neural networks have also been used in a new method for (self) tuning of PI and PID controllers. By measuring a number of points at the step-response of a process and using them as input to a successfully trained neural network, the network can estimate the PI and PID parameters with good accuracy for the same process according to well-known tuning rules for PI and PID controllers.

  • 11.
    Soleimani-Mohseni, Mohsen
    Chalmers University of Technology, Gothenburg, Sweden.
    A study of demand-control ventilation (DCV) and constant air volume (CAV) systems2003In: Healthy Buildings 2003: energy-efficient healthy buildings: proceedings of ISIAQ, 7th International Conference, 7th-11th December 2003, Singapore / [ed] Tham Kwok Wai; Chandra Sekhar; David Cheong, Singapore: National University of Singapore , 2003, p. 392-397Conference paper (Refereed)
  • 12.
    Soleimani-Mohseni, Mohsen
    Chalmers University of Technology, Göteborg, Sweden.
    Feed-forward Control and Dynamic Modelling in Temperature Control of Buildings2002Licentiate thesis, comprehensive summary (Other academic)
  • 13.
    Soleimani-Mohseni, Mohsen
    et al.
    Umeå universitet, Umeå, Sverige.
    Bäckström, Lars
    Eklund, Robert
    Formelsamling i energiteknik2018 (ed. 2)Book (Other academic)
  • 14.
    Soleimani-Mohseni, Mohsen
    et al.
    Umeå Universitet, Umeå, Sweden.
    Gotthardsson, David
    Hållbuss, Rickard
    Vallmark, Hanna
    Analysis of the Thermal Performance of Hydronic Radiators and Building Envelop: Developing Experimental (Step Response) and Theoretical Models and Using Simulink to Investigate Different Control Strategies2017In: Civil Engineering Research Journal, ISSN 2575-8950, Vol. 2, no 4, p. 97-103Article in journal (Refereed)
    Abstract [en]

    A common component of many building heating systems is a thermostat that controls the power on the radiators by changing the mass flow and/or temperature of the feed water. In some cases, these old thermostats malfunction or do not work quite as they should. This can contribute to large indoor-temperature fluctuations, which in turn can lead to unnecessary energy use and poor thermal indoor climate.

    The goal of this paper is to develop a thermal dynamic model of hydronic radiators as well as a thermal dynamic building model to build Simulink models and investigate different control strategies to control the indoor temperature. By adapting better control strategies, one can reduce indoor-temperature fluctuations and reduce energy use.

    The results of simulations in this paper suggest new ways of thinking concerning building a model of hydronic radiators and controlling them and that the temperature control of the studied building will be improved by using a well-functioning thermostatic radiator valve (TRV) instead of a poor-functioning TRV. The smaller fluctuation of the indoor temperature when using a well-functioning TRV compared to a poor-functioning TRV results in better indoor climate. Different types of TRV failures might give rise to large indoor-temperature oscillations, very high/very low indoor temperature and/or high energy use. In some cases, a poor-functioning TRV results in unreasonably high indoor temperatures and high energy use, and in other cases it might result in very low indoor temperatures, whereas the difference in performance when using well- functioning controllers (P and PI) is marginal. © 2015 juniper publishers,

  • 15.
    Soleimani-Mohseni, Mohsen
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Nair, Gireesh
    Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Hasselrot, Rasmus
    Energy simulation for a high-rise building using IDA ICE: Investigations in different climates2016In: Building Simulation, ISSN 1996-3599, E-ISSN 1996-8744, Vol. 9, no 6, p. 629-640Article in journal (Refereed)
    Abstract [en]

    In this paper a model of a high-rise building is constructed in the simulation program IDA ICE. The model is based on an IFC-model of a demonstration building constructed in Ljubljana, Slovenia, as part of an EU-project, EE-high-rise. The model's energy performance was simulated for four cities: Umeå (Scandinavia), Ljubljana (Central Europe), Sibenik (Mediterranean) and Dubai (The Persian Gulf). Furthermore, the climate envelope of the building was modified with the aim to improve the model's energy performance in each of the regions. The results were evaluated according to the energy requirements of passive house standard by the German Passive House Institute. The analysis suggests that the reference building model, which itself incorporates several energy efficient components, was unable to meet the German passive house standard in none of the four cities (Umeå, Ljubljana, Sibenik and Dubai) studied. By providing a combination of energy saving measures, such as modifications of thermal resistance of building envelope, the building may be able to meet the passive house standard in Ljubljana. The analysis concludes that the reduction in window area results in reduction of both heating and cooling demand. Increase in the thickness of the insulation and the thermal resistance of windows reduces the space heating demand for Umeå, Ljubljana and Sibenik (not applied for Dubai) while increasing the cooling demand for these cities. Increased airtightness has marginal effect on heating and cooling demand for all investigated cities. Reduced thermal resistance of windows will decrease cooling demand for Ljubljana, Sibenik and Dubai (not applied for Umeå). Reduced insulation thickness (not applied for Umeå) will decrease cooling demand for Ljubljana and Sibenik but not for Dubai. Reducing the insulation thickness may often result in reduced cooling demand for moderately warm countries since the average outdoor temperature could be lower than the indoor temperature during part of the cooling season. In those situations a reduced insulation thickness can cause heat flow from the relatively hot inside to the colder outside. However, for hot climates like in Dubai where outdoor temperature is higher than the indoor temperature for most of the year, reducing the insulation thickness will increase the cooling demand. This result suggests that the insulation thickness must be chosen and optimized based on heating and cooling demand, internal heat gain, and outdoor climate. © 2016, Tsinghua University Press and Springer-Verlag Berlin Heidelberg.

  • 16.
    Soleimani-Mohseni, Mohsen
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Thomas, Bertil
    Chalmers Lindholmen University, Gothenburg, Sweden.
    A Study of Static and Dynamic Feed Forward in Temperature Control of Buildings2003In: / [ed] Tham Kwok Wai; Chandra Sekhar; David Cheong, Singapore: National University of Singapore , 2003, p. 562-567Conference paper (Refereed)
  • 17.
    Soleimani-Mohseni, Mohsen
    et al.
    Chalmers technical university, Gothenburg, Sweden.
    Thomas, Bertil
    Chalmers Lindholmen University College, Gothenburg, Sweden.
    Neural networks for self-tuning of PI- and PID controllers2004Conference paper (Refereed)
  • 18.
    Soleimani-Mohseni, Mohsen
    et al.
    Department of Building Services Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Thomas, Bertil
    Department of Signals and Systems, Chalmers Lindholmen University College, Gothenburg, Sweden.
    Fahlén, Per
    Department of Building Services Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Estimation of operative temperature in buildings using artificial neural networks2006In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 38, no 6, p. 635-640Article in journal (Refereed)
    Abstract [en]

    In this article, the problem how to obtain models for estimation of the operative temperature in rooms and buildings is discussed. Identification experiments have been carried out in two different buildings and different linear and non-linear estimation models have been identified based on these experiments. For the buildings studied, it is shown that the operative temperature can be estimated fairly well by using variables, which are more easily measured, such as the indoor and outdoor temperatures, the electrical power use in the room, the wall temperatures, the ventilation flow rates and the time of day. It is also shown that non-linear artificial neural network models (ANN-models), in general, give better estimations than linear ARX-models. The most accurate estimation models were obtained using feed-forward ANN-models with one hidden layer of neurons and using Levenberg-Marquardts training algorithms. In one of the buildings, it is shown that for non-linear models but not for linear, the estimations are improved much when using the time of day as an input signal. This shows that the time of day affects the operative temperature in a non-linear manner. © 2005 Elsevier B.V. All rights reserved.

  • 19.
    Thomas, Bertil
    et al.
    Chalmers tekniska högskola, Gothenburg, Sweden.
    Soleimani-Mohseni, Mohsen
    Chalmers tekniska högskola, Gothenburg, Sweden.
    A Simulink Model Environment for evaluation of Control-Strategies in Intelligent Buildings2001In: Program and proceedings for the Nordic MATLAB Conference: Oslo, 17-18, 2001 / [ed] Tore I. Björnarå, Trondheim: COMSOL, 2001Conference paper (Refereed)
  • 20.
    Thomas, Bertil
    et al.
    Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden.
    Soleimani-Mohseni, Mohsen
    Department of Building Services Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Artificial Neural Network Models for Indoor Temperature Prediction: investigations in two buildings2007In: Neural Computing & Applications, ISSN 0941-0643, E-ISSN 1433-3058, Vol. 16, no 1, p. 81-89Article in journal (Refereed)
    Abstract [en]

    The problem how to identify prediction models of the indoor climate in buildings is discussed. Identification experiments have been carried out in two buildings and different models, such as linear ARX-, ARMAX- and BJ-models as well as non-linear artificial neural network models (ANN-models) of different orders, have been identified based on these experiments. In the models, many different input signals have been used, such as the outdoor and indoor temperature, heating power, wall temperatures, ventilation flow rate, time of day and sun radiation. For both buildings, it is shown that ANN-models give more accurate temperature predictions than linear models. For the first building, it is shown that a non-linear combination of sun radiation and time of day is important when predicting the indoor temperature. For the second building, it is shown that the indoor temperature is non-linearly dependent on the ventilation flow rate. © Springer-Verlag London Limited 2006.

  • 21.
    Thomas, Bertil
    et al.
    Chalmers Lindholmen University, Gothenburg, Sweden.
    Soleimani-Mohseni, Mohsen
    Chalmers University of Technology, Gothenburg, Sweden.
    Intelligent thermostats save energy and give improved control performances2002In: ACEEE Buildings: proceedings from ACEEE Summer Study on energy efficiency in buildings, Washington: American Council for an Energy Efficient Economy, 2002, p. 245-257Conference paper (Refereed)
    Abstract [en]

    A common component in many temperature control systems is the thermostat that controls the power of the heating radiators and convectors. Often, the control strategy of these thermostats is proportional or nearly proportional, which means that the control signal (for example the opening of a control valve) is proportional to the control error.

    In this paper, the possibility of saving energy and improving control performance by thermostats that use signals from measurable indoor disturbances, so called feedforward control, is discussed. By means of a number of computer simulations based on an identified state space model of a small building, it is shown that such a thermostat often reduces energy consumption as well as improves control performance (smaller temperature variations). It is also shown that the performance of the new thermostat depends on the frequency of disturbances. It is also discussed what hardware is needed for the implementation of the thermostat, how to measure the indoor disturbances, and how to calculate the transfer function of the dynamic feed-forward compensator.

  • 22.
    Thomas, Bertil
    et al.
    Chalmers Lindholmen University College, Gothenburg, Sweden.
    Soleimani-Mohseni, Mohsen
    Chalmers University of Technology, Gothenburg, Sweden.
    Neural Network Models for Predictive Climate Control in Intelligent Buildings2004Conference paper (Refereed)
  • 23.
    Thomas, Bertil
    et al.
    Chalmers Lindholmen University College, Gothenburg, Sweden.
    Soleimani-Mohseni, Mohsen
    Building Services Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Per, Fahlén
    Building Services Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Feed-forward in temperature control of buildings2005In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 37, no 7, p. 755-761Article in journal (Refereed)
    Abstract [en]

    In most temperature control systems for buildings and rooms, the control strategy is based on feedback of the measured indoor temperature. In this paper, however, control strategies with both feedback and feed-forward are investigated and discussed. In particular, we discuss feed-forward from internal disturbances, such as lighting and electrical machines. By means of a number of computer simulations based on an identified state-space model of a small building, it is shown that such a control strategy reduce the energy use as well as improve the control performance (smaller temperature variations). Furthermore, it is shown that dynamic feed-forward gives better performance than static feed-forward and that static feed-forward gives better performance than no feed-forward at all. It is also shown how the improvement of using feed-forward controller strategies in the building studied depends on the frequencies of the disturbances. © 2004 Elsevier B.V. All rights reserved.

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