scholarly journals Influence of the Improvement in Thermal Expectation Levels with Adaptive Setpoint Temperatures on Energy Consumption

2020 ◽  
Vol 10 (15) ◽  
pp. 5282
Author(s):  
David Bienvenido-Huertas ◽  
Daniel Sánchez-García ◽  
Carlos Rubio-Bellido ◽  
Jesús A. Pulido-Arcas

A sustainable use of active heating, ventilation, and air conditioning (HVAC) systems is crucial for minimum energy consumption. Currently, research studies are increasingly applying adaptive setpoint temperatures, thus reducing considerably the energy consumption without influencing comfort levels excessively. Most of them, however, are focused on the limit values of adaptive comfort standards without considering the tolerance in users’ adaptation capacity. This research study analyzed various tolerance ranges in the recent adaptive thermal comfort model from EN 16798-1:2019 used in setpoint temperatures. The study focused on the south of Europe, considering 47 cities in Spain, 18 cities in Portugal, 13 cities in Greece, and 20 cities in Italy. In addition, such cities were analyzed in three climate scenarios: present time, 2050, and 2100. The results showed that values prefixed by EN 16798-1:2019 for new buildings (tolerance of 0.00 °C) produced significant savings with respect to the static model and that each progressive improvement in users’ thermal expectations in 0.25 °C increased the energy consumption between 6.57 and 9.31% in all scenarios analyzed. Even applying a thermal tolerance of 1.50 °C, energy savings are currently produced with respect to the static model. This tendency increases in future scenarios until a thermal tolerance of 1.75 °C. The results of this paper provide greater knowledge about the possible energy increase that the improvement in users’ expectations would produce.

2008 ◽  
Vol 3 (1) ◽  
Author(s):  
Erick Yair Miranda-Galindo ◽  
Juan Gabriel Segovia - Hernández

Thermally coupled distillation sequences can provide significant energy savings with respect to the operation of conventional distillation columns. Coupled sequences exhibit a complex structure, with recycle streams, that appear to affect their controllability properties. One potential solution to this problem has been suggested through the operation of complex schemes under conditions that do not provide minimum energy consumption. The basic idea is that if one changes the value of the interconnection flowrate, the control properties might change as well. In this work, we analyze the dynamic behavior of two coupled structures under different operating points, including the one with minimum energy consumption. The control analysis properties are analyzed with the application of the singular value decomposition technique in all frequency domains. The results show that the controllability properties of distillation sequences may change significantly depending on the selected value of interconnection flowrate.


Author(s):  
Hadi Abbas ◽  
Youngki Kim ◽  
Jason B. Siegel ◽  
Denise M. Rizzo

This paper presents a study of energy-efficient operation of vehicles with electrified powertrains leveraging route information, such as road grades, to adjust the speed trajectory. First, Pontryagin’s Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible operating modes. The analysis shows that only 5 modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full regeneration with conventional braking. The minimum energy consumption problem is reformulated and solved in the distance domain using Dynamic Programming to optimize speed profiles. A case study is shown for a light weight military robot including road grades. For this system, a tradeoff between energy consumption and trip time was found. The optimal cycle uses 20% less energy for the same trip duration, or could reduce the travel time by 14% with the same energy consumption compared to the baseline operation.


2021 ◽  
Vol 13 (23) ◽  
pp. 13016
Author(s):  
Rami Naimi ◽  
Maroua Nouiri ◽  
Olivier Cardin

The flexible job shop problem (FJSP) has been studied in recent decades due to its dynamic and uncertain nature. Responding to a system’s perturbation in an intelligent way and with minimum energy consumption variation is an important matter. Fortunately, thanks to the development of artificial intelligence and machine learning, a lot of researchers are using these new techniques to solve the rescheduling problem in a flexible job shop. Reinforcement learning, which is a popular approach in artificial intelligence, is often used in rescheduling. This article presents a Q-learning rescheduling approach to the flexible job shop problem combining energy and productivity objectives in a context of machine failure. First, a genetic algorithm was adopted to generate the initial predictive schedule, and then rescheduling strategies were developed to handle machine failures. As the system should be capable of reacting quickly to unexpected events, a multi-objective Q-learning algorithm is proposed and trained to select the optimal rescheduling methods that minimize the makespan and the energy consumption variation at the same time. This approach was conducted on benchmark instances to evaluate its performance.


2013 ◽  
Vol 689 ◽  
pp. 250-253 ◽  
Author(s):  
Mohamed M. Mahdy ◽  
Marialena Nikolopoulou

The objective of this research is to study the effect of using different material specifications for the external walls on the cost of the energy consumption for achieving internal thermal comfort. We refer to this as operation running cost, which in turn is compared to initial construction cost for each type of the used external walls. In order to achieve this objective, dynamic thermal simulation were carried out for four different types of external walls – commonly used in Egypt – in two different sets of cooling: natural ventilation and mechanical means. Experiments recommend that using the Egyptian Residential Energy Code (EREC) to achieve inner thermal comfort with the minimum energy consumption (consequently the minimum CO2 emissions) and the minimum running cost as well.


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