Ph. D. Project
Title:
Design of a dynamic co-simulation architecture based on the BIM : application to the coupling of building thermal simulation and occupant behaviour.
Dates:
2020/03/05 - 2022/12/31
Supervisor(s):
Other supervisor(s):
Riad Benelmir
Description:
Most of the urban population spends more than 90% of their time in indoor environments and a large proportion of the time awake is spent in the workplace. Buildings consume more than one third of the total energy resource and induce a major share of the greenhouse gas emission to the environment. France, like other countries in the world, has set targets to optimize the energy consumption and reduce its emission.
Recent advances in BIM (Building Information Modelling) led to accurate and efficient building thermal simulation tools. However, there is still an important performance gap between the predicted (simulated) energy consumption and the real one. To reduce this gap, many research works investigated the influence of occupants on the energy consumption in buildings. They concluded that taking into account occupants' behaviour in building thermal simulation may be one of the most relevant research orientation to reduce the identified gap .
In the framework of the CPER FORBOIS 2, an action was initiated by the CRAN in collaboration with the LERMAB aiming to acquire and install a an operation management system in a set of buildings (the Campus Fibres in Épinal) . This system will be dedicated to energy and air quality management of the campus' buildings. It would include on the one hand the building instrumentation necessary for the measurement and monitoring of energy consumption and air quality, and on the other hand a digital model (BIM Model) of this set of buildings, connected to this instrumentation. The purpose of the research platform is to propose an optimal control of the actuators of the set of buildings (heating, air conditioning, ventilation, occultation, etc.) on the basis of the state of this digital model and the use of the different rooms of the building (number of people, energy profile, weather forecast, etc.) to optimize the energy performance and comfort of users.
Beside the fact that significant progresses have been achieved in building energy modelling, existence of scientific and robust methods to define and model energy consumption related to "occupant behavior" in building are highly demanded. Occupant behaviors include direct or indirect occupants' interactions with buildings, especially with operable windows, lights, blinds, thermostats, and plug-in appliances needed to adapt ambient conditions (source). As a result, occupant behavior has become widely understood to be a leading cause of uncertainty in building performance. The uncertainty of occupants can be mitigate through dynamic analysis of building design but greater knowledge of dynamic human behaviour is needed (source).
There is thus an urgent need for the development of occupant behavior models to be deployed in dynamic building energy simulation programs dealing with environmental indoor air quality and energy efficiency. The main challenge would be to model the complexity and dynamic nature of occupant energy behavior, which is affected by various internal and external factors. This phenomenon has to be studied in a multidisciplinary approach to incorporate those coming from engineering, economics, design and so on.
The general objective will be to investigate occupants' behavior interactions with building indoor environmental quality and thermal comfort. A key objective will be to identify variables with influence on occupants' behavior and its effect; this will be done via measurements in building at different season. Its influence on energy performance will be studied by dynamic co-simulation.
Research questions
How is it possible to:
1. Apply and develop a robust and standardized quantitative description and occupant behavior computational models to analyze and evaluate the impact of occupant behavior on building energy performance and environmental indoor quality through dynamic thermal simulation?
2. Develop occupant behavior data collecting methods, modeling, and validation?
3. Identify the occupant behavior modelling method (Markov, Bernouilli) and data collection methods (in-site, laboratory, survey) in order to be used in dynamic building simulation tools?
4. Integrate the occupant behavior models with thermal dynamic simulation tools (TRNSYS, energy plus, Revit) and used for optimization of a building at different stage like designing, evaluation and operation?
Références :
[1] GiacomoCapizzi, Grazia LoSciuto, GiulianoCammarata, MassimilianoCammarata, Thermal transients simulations of a building by a dynamic model based on thermal-electrical analogy: Evaluation and implementation issue, Applied Energy, Volume 199, 1 August 2017, Pages 323-334
[2] Daniele Testia*, Eva Schitoa, Emidio Tiberia, Paolo Contia, Walter Grassia, Building energy simulation by an in-house full transient model for radiant systems coupled to a modulating heat pump, 6th International Building Physics Conference, IBPC 2015
[3] Clayton Miller, Daren Thomas, Jerôme Henri Kampf, Arno Schlueter, Urban and building multiscale co-simulation: case study implementations on two university campuses, Journal of Building Performance Simulation · July 2017
[4] Andreas Nicolai1Anne Paepcke, Co-Simulation between detailed building energy performance simulation and Modelica HVAC component models, Institut for Building Climatology, Faculty of Architecture, TU Dresden, Germany
Recent advances in BIM (Building Information Modelling) led to accurate and efficient building thermal simulation tools. However, there is still an important performance gap between the predicted (simulated) energy consumption and the real one. To reduce this gap, many research works investigated the influence of occupants on the energy consumption in buildings. They concluded that taking into account occupants' behaviour in building thermal simulation may be one of the most relevant research orientation to reduce the identified gap .
In the framework of the CPER FORBOIS 2, an action was initiated by the CRAN in collaboration with the LERMAB aiming to acquire and install a an operation management system in a set of buildings (the Campus Fibres in Épinal) . This system will be dedicated to energy and air quality management of the campus' buildings. It would include on the one hand the building instrumentation necessary for the measurement and monitoring of energy consumption and air quality, and on the other hand a digital model (BIM Model) of this set of buildings, connected to this instrumentation. The purpose of the research platform is to propose an optimal control of the actuators of the set of buildings (heating, air conditioning, ventilation, occultation, etc.) on the basis of the state of this digital model and the use of the different rooms of the building (number of people, energy profile, weather forecast, etc.) to optimize the energy performance and comfort of users.
Beside the fact that significant progresses have been achieved in building energy modelling, existence of scientific and robust methods to define and model energy consumption related to "occupant behavior" in building are highly demanded. Occupant behaviors include direct or indirect occupants' interactions with buildings, especially with operable windows, lights, blinds, thermostats, and plug-in appliances needed to adapt ambient conditions (source). As a result, occupant behavior has become widely understood to be a leading cause of uncertainty in building performance. The uncertainty of occupants can be mitigate through dynamic analysis of building design but greater knowledge of dynamic human behaviour is needed (source).
There is thus an urgent need for the development of occupant behavior models to be deployed in dynamic building energy simulation programs dealing with environmental indoor air quality and energy efficiency. The main challenge would be to model the complexity and dynamic nature of occupant energy behavior, which is affected by various internal and external factors. This phenomenon has to be studied in a multidisciplinary approach to incorporate those coming from engineering, economics, design and so on.
The general objective will be to investigate occupants' behavior interactions with building indoor environmental quality and thermal comfort. A key objective will be to identify variables with influence on occupants' behavior and its effect; this will be done via measurements in building at different season. Its influence on energy performance will be studied by dynamic co-simulation.
Research questions
How is it possible to:
1. Apply and develop a robust and standardized quantitative description and occupant behavior computational models to analyze and evaluate the impact of occupant behavior on building energy performance and environmental indoor quality through dynamic thermal simulation?
2. Develop occupant behavior data collecting methods, modeling, and validation?
3. Identify the occupant behavior modelling method (Markov, Bernouilli) and data collection methods (in-site, laboratory, survey) in order to be used in dynamic building simulation tools?
4. Integrate the occupant behavior models with thermal dynamic simulation tools (TRNSYS, energy plus, Revit) and used for optimization of a building at different stage like designing, evaluation and operation?
Références :
[1] GiacomoCapizzi, Grazia LoSciuto, GiulianoCammarata, MassimilianoCammarata, Thermal transients simulations of a building by a dynamic model based on thermal-electrical analogy: Evaluation and implementation issue, Applied Energy, Volume 199, 1 August 2017, Pages 323-334
[2] Daniele Testia*, Eva Schitoa, Emidio Tiberia, Paolo Contia, Walter Grassia, Building energy simulation by an in-house full transient model for radiant systems coupled to a modulating heat pump, 6th International Building Physics Conference, IBPC 2015
[3] Clayton Miller, Daren Thomas, Jerôme Henri Kampf, Arno Schlueter, Urban and building multiscale co-simulation: case study implementations on two university campuses, Journal of Building Performance Simulation · July 2017
[4] Andreas Nicolai1Anne Paepcke, Co-Simulation between detailed building energy performance simulation and Modelica HVAC component models, Institut for Building Climatology, Faculty of Architecture, TU Dresden, Germany
Department(s):
| Eco-Technic systems engineering |
