Learning Agent for a Heat-Pump Thermostat With a Set-Back Strategy Using Model-Free Reinforcement Learning

The conventional control paradigm for a heat pump with a less efficient auxiliary heating element is to keep its temperature set point constant during the day. This constant temperature set point ensures that the heat pump operates in its more efficient heat-pump mode and minimizes the risk of activating the less efficient auxiliary heating element. As an alternative to a constant set-point strategy, this paper proposes a learning agent for a thermostat with a set-back strategy. This set-back strategy relaxes the set-point temperature during convenient moments, e.g. when the occupants are not at home. Finding an optimal set-back strategy requires solving a sequential decision-making process under uncertainty, which presents two challenges. A first challenge is that for most residential buildings a description of the thermal characteristics of the building is unavailable and challenging to obtain. A second challenge is that the relevant information on the state, i.e. the building envelope, cannot be measured by the learning agent. In order to overcome these two challenges, our paper proposes an auto-encoder coupled with a batch reinforcement learning technique. The proposed approach is validated for two building types with different thermal characteristics for heating in the winter and cooling in the summer. The simulation results indicate that the proposed learning agent can reduce the energy consumption by 4-9% during 100 winter days and by 9-11% during 80 summer days compared to the conventional constant set-point strategyComment: Submitted to Energies - MDPI.co

Computer-supported laboratory for production-oriented electrotechnical systems

At the electrical engineering department of the K.U.Leuven an education research project was started in October 1997. The target is to develop a powerful environment to teach students to solve practice-oriented problems as they will encounter them in industry furtheron in their career. In order to give a wide use to the developed environment, a close collaboration has been established with three polytechnical engineering institutes. Self-dependence has to be stimulated by creating possibilities for real “hands-on experience”. Such an educational environment implicates time-problems, high investment costs and last but not least safety restrictions. The project contributes to the solution of these problems by using simulation- and softwareenvironments, without loosing the real hands-on feeling

A Comprehensive Model of a Doubly Fed Induction Generator for Dynamic Simulations and

Abstract. The doubly fed induction generator (DFIG) is a very suitable generator type for wind turbine applications. However, its operation principles and its control are rather complex. This paper will describe the different steps for modelling and simulating the generator behaviour. A simulation example of the operation of a DFIG in a small power system is presented

Airway deposition of extrafine inhaled triple therapy in patients with copd: A model approach based on functional respiratory imaging computer simulations

Introduction: There is a clear correlation between small airways dysfunction and poor clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), and it is therefore important that inhalation therapy (both bronchodilator and anti-inflammatory) can deposit in the small airways. Two single-inhaler triple therapy (SITT) combinations are currently approved for the maintenance treatment of COPD: extrafine formulation beclomethasone dipropionate/formoterol fumarate/glycopyrronium bromide (BDP/FF/GB), and nonextrafine formulation fluticasone furoate/vilanterol/umeclidinium (FluF/VI/UMEC). This study evaluated the lung deposition of the inhaled corticosteroid (ICS), long-acting β2-agonist (LABA), and long-acting muscarinic antagonist (LAMA) components of these two SITTs. Materials and Methods: Lung deposition was estimated in-silico using functional respiratory imaging, a validated technique that uses aerosol delivery performance profiles, patients’ high-resolution computed tomography (HRCT) lung scans, and patient-derived inhalation profiles to simulate aerosol lung deposition. Results: HRCT scan data from 20 patients with COPD were included in these analyses, who had post-bronchodilator forced expiratory volume in 1 second (FEV1) ranging from 19.3% to 66.0% predicted. For intrathoracic deposition (as a percentage of the emitted dose), deposition of the ICS component was higher from BDP/FF/GB than FluF/VI/UMEC; the two triple therapies had similar performance for both the LABA component and the LAMA component. Peripheral deposition of all three components was higher with BDP/FF/GB than FluF/ VI/UMEC. Furthermore, the ratios of central to peripheral deposition for all three components of BDP/FF/GB were <1, indicating greater peripheral than central deposition (0.48 ±0.13, 0.48±0.13 and 0.49±0.13 for BDP, FF and GB, respectively; 1.96±0.84, 0.97±0.34 and 1.20±0.48 for FluF, VI and UMEC, respectively). Conclusions: Peripheral (small airways) deposition of all three components (ICS, LABA, and LAMA) was higher from BDP/FF/GB than from FluF/VI/UMEC, based on profiles from patients with moderate to very severe COPD. This is consistent with the extrafine formulation of BDP/FF/GB

Dynamic stroma reorganization drives blood vessel dysmorphia during glioma growth

Glioma growth and progression are characterized by abundant development of blood vessels that are highly aberrant and poorly functional, with detrimental consequences for drug delivery efficacy. The mechanisms driving this vessel dysmorphia during tumor progression are poorly understood. Using longitudinal intravital imaging in a mouse glioma model, we identify that dynamic sprouting and functional morphogenesis of a highly branched vessel network characterize the initial tumor growth, dramatically changing to vessel expansion, leakage, and loss of branching complexity in the later stages. This vascular phenotype transition was accompanied by recruitment of predominantly pro-inflammatory M1-like macrophages in the early stages, followed by in situ repolarization to M2-like macrophages, which produced VEGF-A and relocate to perivascular areas. A similar enrichment and perivascular accumulation of M2 versus M1 macrophages correlated with vessel dilation and malignancy in human glioma samples of different WHO malignancy grade. Targeting macrophages using anti-CSF1 treatment restored normal blood vessel patterning and function. Combination treatment with chemotherapy showed survival benefit, suggesting that targeting macrophages as the key driver of blood vessel dysmorphia in glioma progression presents opportunities to improve efficacy of chemotherapeutic agents. We propose that vessel dysfunction is not simply a general feature of tumor vessel formation, but rather an emergent property resulting from a dynamic and functional reorganization of the tumor stroma and its angiogenic influences