Job description

Joining LINEACT at CESI for a research internship would be a fantastic opportunity to contribute to innovative projects while deepening my skills in a cutting-edge environment

Abstract

The Mediterranean climate in southern France is characterized by long and hot summers and mild winters. Under these conditions, understanding the impact of HVAC systems on the comfort of office occupants and their adaptive behaviors is important to create a comfortable indoor thermal environment. The objective of this study is to understand the effects of occupants’ airconditioning/heating switching behavior on thermal satisfaction in two-person offices of buildings located in Montpellier in southern France and equipped with an air-water heat pump HVAC system. Indoor temperature and indoor relative humidity were collected (10-min intervals), occupancy and weather (outdoor temperature, relative humidity, and wind speed) data were collected over one year. Moreover, the air-conditioning/heating status (off or on) will be determined. The airconditioning/heating usage schedule, comfort temperatures, and factors affecting the switching on or not of air conditioning/heating will be analyzed. The thermal tolerance of occupants before and after switching on the air conditioning/heating will be studied using measurements and a questionnaire survey. Furthermore, air-conditioning switch-on models will be using logistic regression.

Keywords

Air conditioning, Behavior model, Heating, Logistic regression, Mediterranean climate, Occupant behavior, Probabilistic model, Tertiary sector buildings 

Research Work

Scientific context

The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings, the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models express the probability of the occurrence of a specific behavior and are usually derived from statistical data. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed models for office buildings in a Mediterranean climate.

Subject

Therefore, in this study, occupant behavior toward heating and cooling system settings will be modeled as a probabilistic process. Occupant behavior related to the turn-on heating and collecting system will be studied through experimental measurements collected in offices. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point will be determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. Logistic regression will be adopted to calculate the probability of an occupant turning on the heating and collecting system. The results yielded a proposed model that can be used in building simulation software to predict the energy consumption of office buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the cooling system is mainly affected by the indoor air temperature

Context

Lab presentation

CESI LINEACT (UR 7527), Laboratory for Digital Innovation for Businesses and Learning to Support the Competitiveness of Territories, anticipates and accompanies the technological mutations of sectors and services related to industry and construction. The historical proximity of CESI with companies is a determining element for our research activities. It has led us to focus our efforts on applied research close to companies and in partnership with them. A human-centered approach coupled with the use of technologies, as well as territorial networking and links with training, have enabled the construction of cross-cutting research; it puts humans, their needs and their uses, at the center of its issues and addresses the technological angle through these contributions. Its research is organized according to two interdisciplinary scientific teams and several application areas.

• Team 1 "Learning and Innovating" mainly concerns Cognitive Sciences, Social Sciences and Management Sciences, Training Techniques and those of Innovation. The main scientific objectives are the understanding of the effects of the environment, and more particularly of situations instrumented by technical objects (platforms, prototyping workshops, immersive systems...) on learning, creativity and innovation processes.
• Team 2 "Engineering and Digital Tools" mainly concerns Digital Sciences and Engineering. The main scientific objectives focus on modeling, simulation, optimization and data analysis of cyber physical systems. Research work also focuses on decision support tools and on the study of human-system interactions in particular through digital twins coupled with virtual or augmented environments.

These two teams develop and cross their research in application areas such as - Industry 5.0, - Construction 4.0 and Sustainable City, - Digital Services. Areas supported by research platforms, mainly that in Rouen dedicated to Factory 5.0 and those in Nanterre dedicated to Factory 5.0 and Construction 4.0. Links to the research axes of the research team involved Energy management – Comfort and health in buildings

Desired profile

Required Skills

Scientific, technical, and soft skills:

• Student in the field of HVAC and Thermal environment of a building
• Statistical analysis
• Team Collaboration
• Communication
• Critical Thinking

Work program

Literature review

The objective of this first step is to collect information on studies on the behavior of the occupants toward the HVAC system. Information on the type of building, geographical area, methods of data collection (qualitative and qualitative), methods of analysis and modeling, and practical applications of these studies will be identified.

Experimental study and analysis

The objective is to analyze the data collected on the behavior of the occupants on the HVAC system and to perform a statistical analysis of the various factors that affect the start-up of the HVAC system

Logistic Regression Modelin

Organisation

Location: CESI LINEACT Campus CESI Montpellier

Starting date: 7/04/2025 Duration: 6 months

Supervisor(s): Abderrahmane SOUFI/ Researcher-lecturer

Bibliography:

[1] A.Soufi, A.Boodi. Investigation of Input Feature Combinations Considering Occupant Behavior for Modeling Indoor Air Temperature in a Classroom. Proceedings of the 18th IBPSA Conference Shanghai, China, Sept. 4-6, 2023.

https://doi.org/10.26868/25222708.2023.1500

[2] J. Mahecha Zambrano, U.F.Oberegger, G. Salvalai, Towards integrating occupant behaviour modelling in simulation-aided building design: Reasons, challenges and solutions, Energy & Buildings. 253 (2021) 111498. 

https://doi.org/10.1016/j.enbuild.2021.111498

[3] E. Azar, W. O’Brien, S. Carlucci, T. Hong, A. Sonta, J. Kim, M. S. Andargie, T. Abuimara, M. El Asmar, and R. K. Jain. Simulation-aided occupant-centric building design: A critical review of tools, methods and applications. Energy and Buildings 224 (2020) 110292.

https://doi.org/10.1016/j.enbuild.2020.110292

[4] S. Carlucci, M. De Simone, S-K. Firth, M-B. Kjærgaard, R. Markovic, M. Saiedur Rahaman, M-K Annaqeeb, S. Biandrate, A.Das, J.Wladyslaw Dziedzic, G.Fajilla, M.Favero, M.Ferrando, J. Hahn, M. Han, Y.Peng, F. Salim, A. Schlüter, C. Van Treeck. Modeling occupant behavior in buildings. Building and Environment 174 (2020) 106768.

https://doi.org/10.1016/j.buildenv.2020.106768

[5] D.Xia, S.Lou, Y.Huang, Y.Zhao , D. H.W. Li, X. Zhou. A study on occupant behaviour related to air-conditioning usage in residential buildings. Energy & Buildings 203 (2019) 109446

https://doi.org/10.1016/j.enbuild.2019.109446

[6] J. Yao. Modelling and simulating occupant behaviour on air conditioning in residential buildings. Energy & Buildings 175 (2018) 1-10

https://doi.org/10.1016/j.enbuild.2018.07.013

 [7] L.Yan, M.Liu. Predicting household air conditioners’ on/off state considering occupants’preference diversity: A study in Chongqing, China. Energy & Buildings 253 (2021) 111516

https://doi.org/10.1016/j.enbuild.2021.111516