Optimisation de la consommation énergétique de bâtiment à l'aide de modèles simplifiés et des nouvelles méthodes de contrôle

L'inquiétude croissante concernant le futur des ressources énergétique a fait de l'optimisation énergétique une priorité dans tous les secteurs. De nombreux sujets de recherche se sont focalisés sur celui du bâtiment étant le principal consommateur d'énergie, en particulier à cause de ses besoins en chauffage. Beaucoup de propositions pour réduire la consommations ont été faites. Ceux-ci vont de l'amélioration de l'isolation au changement du système de gestion du thermostat en passant par la formation des occupants à une meilleure gestion de leur bâtiment. Cette thèse propose une nouvelle méthode de contrôle qui permet de minimiser la consommation énergétique et dépenses budgétaires. La méthode génère un planning énergétique sur une période de temps pré-définie, ceci en prenant compte du confort thermique des occupants. Elle est basée sur l'application de la méthode de Monte Carlo, un générateur aléatoire appliqué au système de chauffage. L'objectif est de déterminer le planning de chauffage optimal, qui respecte les trois contraintes suivantes: - Le confort thermique des résidents; - La minimisation de l'énergie consommée / du budget; - Le déplacement de la charge. De plus, pour tester cette méthode, l'identification du comportement thermique du bâtiment a été requise. De ce fait, un modèle thermique du bâtiment a été développé. Ce modèle a été volontairement simplifié afin de l'intégrer plus simplement dans le processus de contrôle. De plus, une nouvelle approche d'identification thermique du bâtiment aussi bien qu'une nouvelle méthode de contrôle en temps réel ont été présentées.With the highly developing concerns about the future of energy resources, the optimization of energy consumption becomes a must in all sectors. A lot of research was dedicated to buildings regarding that they constitute the highest energy consuming sector mainly because of their heating needs. Many proposals of new strategies to minimize building consumption were done. These proposals vary between recommending better insulation, advising change in occupants' behavior and changing the heating control management. This thesis proposes a new control method that helps minimizing the heating consumption and expenses. This method generates an energy plan over a defined prediction horizon respecting the occupants’ thermal comfort. It is based on the application of Monte Carlo method, i.e., a random generator for the heating system scenarios. The aim is to determine the optimal heating plan for the prediction horizon that fulfills the constraints regarding the following three factors: • The thermal comfort of occupants; • The minimization of the energy consumption/expenses; • Load shifting. However, to test this method, an identification of the building thermal behavior was needed. Thus, a building thermal model to simulate the building behavior was developed. This model was meant to be simplified in order to better integrate it in the control process. Furthermore, a new parameter estimation approach as well as a real time temperature control method are presented to ensure the implementation of the optimal predicted plan

The role of new technologies in understanding the building energy performance: A comparative study

International audienc

A simplified building thermal model for the optimization of energy consumption: Use of a random number generator

International audienc

On-line fast parametric estimation of building thermal behavior using algebraic methods

International audienc

Building energy consumption flatness-based control using algebraic on-line estimation

International audienc

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

International audienceThe model-based control of building heating systems for energy saving encounters severe physical, mathematical and calibration difficulties in the numerous attempts that has been published until now. This topic is addressed here via a new model-free control setting, where the need of any mathematical description disappears. Several convincing computer simulations are presented. Comparisons with classic PI controllers and flatness-based predictive control are provided

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

International audienceThe model-based control of building heating systems for energy saving encounters severe physical, mathematical and calibration difficulties in the numerous attempts that has been published until now. This topic is addressed here via a new model-free control setting, where the need of any mathematical description disappears. Several convincing computer simulations are presented. Comparisons with classic PI controllers and flatness-based predictive control are provided

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research