Modeling and Simulation of Multi-Room Buildings

Perera, Degurunnehalage Wathsala U.; Skeie, Nils-Olav

doi:10.4173/mic.2016.2.2

Cited by 7 publications

(7 citation statements)

References 17 publications

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“…A linear physical model is developed for the abovementioned test building, and it is inherited from the models presented in Perera et al (2014a) and Perera et al (2014b). The energy balance equation for inside air is derived and presented by the equation (1).…”

Section: Physical Models Of Buildingsmentioning

confidence: 99%

Structural observability analysis and EKF based parameter estimation of building heating models

Perera¹,

Perera²,

Pfeiffer³

et al. 2016

MIC

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Research for enhanced energy-efficient buildings has been given much recognition in the recent years owing to their high energy consumptions. Increasing energy needs can be precisely controlled by practicing advanced controllers for building Heating, Ventilation, and Air-Conditioning (HVAC) systems. Advanced controllers require a mathematical building heating model to operate, and these models need to be accurate and computationally efficient. One main concern associated with such models is the accurate estimation of the unknown model parameters.This paper presents the feasibility of implementing a simplified building heating model and the computation of physical parameters using an off-line approach. Structural observability analysis is conducted using graph-theoretic techniques to analyze the observability of the developed system model. Then Extended Kalman Filter (EKF) algorithm is utilized for parameter estimates using the real measurements of a single-zone building. The simulation-based results confirm that even with a simple model, the EKF follows the state variables accurately. The predicted parameters vary depending on the inputs and disturbances.

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Section: Physical Models Of Buildingsmentioning

confidence: 99%

Structural observability analysis and EKF based parameter estimation of building heating models

Perera¹,

Perera²,

Pfeiffer³

et al. 2016

MIC

Self Cite

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“…where c d.a is a specific heat capacity of the drying agent; ℓ is specific consumption of dry air required to evaporate 1 kg of water. According to equation (16), it is necessary to define specific consumption of heat for heating the drying agent from the initial to the final temperature. Then according to equation ( 17) minimum acceptable values of specific consumption of heat for evaporation (q).…”

Section: Optimal Operation Of Peat Dryermentioning

confidence: 99%

Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56), October, 7-9, 2015, Linköping University, Sweden

Pop¹,

Thiele²

2015

Linköping Electronic Conference Proceedings

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WELCOME he 56th Conference on Simulation andModelling will be held in Linköping, Sweden. Linköping is one of Sweden's fastest growing cities. The population is constantly increasing and will soon surpass 150 000 inhabitants. It is currently Sweden's fifth largest city and a part of the expansive region Twin Cities of Sweden. Linköping has long been characterized by world-class high technology in the fields of aviation, IT and the environment. There is a strong force of innovation especially in Mjärdevi Science Park-one of Europe's leading technology parks, and at the highly ranked university, which stands for excellence and entrepreneurship. SIMS is the Scandinavian Simulation Society with members from the five Nordic countries Denmark, Finland, Norway, Sweden and Iceland. The SIMS history goes back to 1959. The goal of SIMS is to further the science and practice of modeling and simulation in all application areas and be a Scandinavian forum for information interchange among modeling and simulation professionals and non-professionals in Denmark, Finland, Norway and Sweden as well as a channel for information exchange between the Scandinavian modeling and simulation community and the international modeling and simulation communities.

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“…in [7], see also [8], [2], and [19]. Software libraries with detailed building models are available, but for control studies, the discussion in [15], [16] is particularly relevant. Disturbances are important in building models.…”

Section: Introductionmentioning

confidence: 99%

Improved Model for Solar Heating of Buildings

Lie

2015

Linköping Electronic Conference Proceedings

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A considerable future increase in the global energy use is expected, and the effects of energy conversion on the climate are already observed. Future energy conversion should thus be based on resources that have negligible climate effects; solar energy is perhaps the most important of such resources.The presented work builds on a previous complete model for solar heating of a house; here the aim to introduce ventilation heat recovery and improve on the hot water storage model. Ventilation heat recovery reduces the heat loss due to ventilation, as expected. Here, a recovery efficiency of 0:5 is used, although a more realistic number is perhaps 0:7. The improved hot water storage model increases the exergy of the storage tank by assuming a vertical temperature distribution. Further improvements are possible by introducing a simple thermocline tracking algorithm, effectively allowing for variable volumes of the temperature zones in the hot water storage tank. Currently, the model does not allow for very good temperature control; this is due to a lack of freedom in the control inputs.

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Modeling and Simulation of Multi-Room Buildings

Cited by 7 publications

References 17 publications

Structural observability analysis and EKF based parameter estimation of building heating models

Structural observability analysis and EKF based parameter estimation of building heating models

Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56), October, 7-9, 2015, Linköping University, Sweden

Improved Model for Solar Heating of Buildings

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