Calibration of building thermal models using an optimal control approach

Nassiopoulos, Alexandre; Kuate, Raphaël; Bourquin, Frédéric

doi:10.1016/j.enbuild.2014.02.052

Cited by 14 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally in yet another recent study, and in order to calibrate two small but different size and orientation offices on the same floor, with similar envelop properties, Nassiopoulos et al [24] alter initial physical values differently for each of those offices. In the current study, EDSL TAS allows constructing one unique model that includes all the required zones to be studied, using the exact same physical properties throughout; hence the open balcony could not have been fine tuned separately to get better calibrated results.…”

Section: Calibration Review In Recent Studiesmentioning

confidence: 97%

Thermal performance of glazed balconies within heavy weight/thermal mass buildings in Beirut, Lebanon's hot climate

Saleh

2015

Energy and Buildings

View full text Add to dashboard Cite

Section: Calibration Review In Recent Studiesmentioning

confidence: 97%

Thermal performance of glazed balconies within heavy weight/thermal mass buildings in Beirut, Lebanon's hot climate

Saleh

2015

Energy and Buildings

View full text Add to dashboard Cite

“…The coefficient of variation of root mean square (CV) as given in (19) has the ability to test the average deviation between the predicted value and the actual value, which is not affected by the sample data size. For this reason, the CV value is adopted to test the model performance for estimating the solar heat gain:…”

Section: Solar Radiation On Envelop Surfacesmentioning

confidence: 99%

“…O'Neill et al [17] adopted EnergyPlus [18] to test the forecast model consisting of 3R2C and Extended Kalman Filter. Similarly, a cost-effective building thermal model was verified by EnergyPlus [19]. What is more, EnergyPlus and MATLAB were integrated by BCVTB [20] to develop a cooling load prediction model for optimizing HVAC control, and the model parameters were recognized using the data calculated by simulation tool [21,22].…”

Section: Introductionmentioning

confidence: 99%

Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System

Lei

et al. 2016

Mathematical Problems in Engineering

View full text Add to dashboard Cite

MPC has the ability to optimize the system operation parameters for energy conservation. Recently, it has been used in HVAC systems for saving energy, but there are very few applications in radiant cooling systems. To implement MPC in buildings with radiant terminals, the predictions of cooling load and thermal environment are indispensable. In this paper, a simplified thermal model is proposed for predicting cooling load and thermal environment in buildings with radiant floor. In this thermal model, the black-box model is introduced to derive the incident solar radiation, while the genetic algorithm is utilized to identify the parameters of the thermal model. In order to further validate this simplified thermal model, simulated results from TRNSYS are compared with those from this model and the deviation is evaluated based on coefficient of variation of root mean square (CV). The results show that the simplified model can predict the operative temperature with a CV lower than 1% and predict cooling loads with a CV lower than 10%. For the purpose of supervisory control in HVAC systems, this simplified RC thermal model has an acceptable accuracy and can be used for further MPC in buildings with radiation terminals.

show abstract

“…Leakage through ventilations can occur in different ways such as leakage through windows, wall gaps, and deliberate ventilations (Rogers, Maleki, Ghosh et al, 2011). The effect of solar heat depends on the orientation of outside facade and the position of sun (Nassiopoulos, Kuate, & Bourquin, 2014). Besides this, some other parameters, such as thermal capacity of room air and heat power generated by internal sources can be also considered in thermal models.…”

Section: Introductionmentioning

confidence: 99%

“…Besides this, some other parameters, such as thermal capacity of room air and heat power generated by internal sources can be also considered in thermal models. Internal sources include heating provided by cooking and other energy use, as well as the heat generated by people (Guo, Li, Poulton et al, 2008;Nassiopoulos, Kuate, & Bourquin, 2014). Here, the thermal models are categorized on the basis of parameters involved in modeling formula.…”

Section: Introductionmentioning

confidence: 99%

Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia

Malibari

Gamlo²

2016

CIS

View full text Add to dashboard Cite

Objectives: The consumption of electricity and its costs are expected to be increased in Saudi Arabia due to its rapid growth in population. As the Kingdom is characterized by extreme hot climate, a massive amount of electricity consumed by the residential sector goes to power air conditioners. To control this huge amount of energyconsumedin homes, thermal models have been generated with two or more parameters. Methodology: The households' surveys have been conducted in order to collect the data. The Non-linear regression analysis has been carried out to obtain the outcomes of study. Moreover, household surveys have been conducted for data collection. The grid algorithm and the non-linear regression have been used to learn the parameters in the model to simulate the weather in Saudi Arabia. The temperature loggers have been placed in the houses to observe the behavior of residents of using cooling system. The web forecast has been used to analyze the temperature of cities on hourly basis. Results: Simple thermal model has been built using two parameters by applying the grid and non-linear regression methods for data fitting. Then the thermal model with envelope has also been created using four parameters by applying non-linear regression method for data fitting. Conclusion: It has been evaluated through outcomes that thermal model with envelope is better as compared to simple thermal model. Moreover, the data fitting by non-linear regression method has also been observed to perform better than data fitting by grid method.

show abstract

Calibration of building thermal models using an optimal control approach

Cited by 14 publications

References 21 publications

Thermal performance of glazed balconies within heavy weight/thermal mass buildings in Beirut, Lebanon's hot climate

Thermal performance of glazed balconies within heavy weight/thermal mass buildings in Beirut, Lebanon's hot climate

Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System

Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia

Contact Info

Product

Resources

About