scholarly journals Building Energy Management for Passive Cooling Based on Stochastic Occupants Behavior Evaluation

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 138
Author(s):  
Michele Roccotelli ◽  
Alessandro Rinaldi ◽  
Maria Pia Fanti ◽  
Francesco Iannone
Keyword(s):  
Thermal Comfort ◽  
Energy Management ◽  
Natural Ventilation ◽  
Building Energy ◽  
Energy Performance ◽  
Passive Cooling ◽  
Deterministic Models ◽  
Building Energy Management ◽  
Solar Shading ◽  
Automation Systems

The common approach to model occupants behaviors in buildings is deterministic and consists of assumptions based on predefined fixed schedules or rules. In contrast with the deterministic models, stochastic and agent based (AB) models are the most powerful and suitable methods for modeling complex systems as the human behavior. In this paper, a co-simulation architecture is proposed with the aim of modeling the occupant behavior in buildings by a stochastic-AB approach and implementing an intelligent Building Energy Management System (BEMS). In particular, optimized control logics are designed for smart passive cooling by controlling natural ventilation and solar shading systems to guarantee the thermal comfort conditions and maintain energy performance. Moreover, the effects of occupant actions on indoor thermal comfort are also taken into account. This study shows how the integration of automation systems and passive techniques increases the potentialities of passive cooling in buildings, integrating or replacing the conventional efficiency strategies.

scholarly journals Business Processes and Comfort Demand for Energy Flexibility Analysis in Buildings

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6561
Author(s):  
Stylianos K. Karatzas ◽  
Athanasios P. Chassiakos ◽  
Anastasios I. Karameros
Keyword(s):  
Energy Management ◽  
Environmental Conditions ◽  
Business Processes ◽  
Energy Savings ◽  
Organizational Structures ◽  
Building Energy ◽  
Energy Performance ◽  
Behavior Patterns ◽  
Occupant Behavior ◽  
Building Energy Management

Occupant behavior and business processes in a building environment constitute an inseparable set of important factors that drives energy consumption. Existing methodologies for building energy management lag behind in addressing these core parameters by focusing explicitly on the building’s structural components. Additional layers of information regarding indoor and outdoor environmental conditions and occupant behavior patterns, mostly driven by everyday business processes (schedules, loads, and specific business activities related to occupancy patterns and building operations), are necessary for the effective and efficient modeling of building energy performance in order to establish a holistic energy efficiency management framework. The aim of this paper was to develop a context-driven framework in which multiple levels of information regarding occupant behavior patterns resulting from everyday business processes were incorporated for efficient energy management in buildings. A preliminary framework evaluation was performed in a multifaceted university building involving a number of spaces, employees, business processes, and data from sensors and metering devices. The results derived by linking operational aspects and environmental conditions (temperature, humidity, and luminance) to occupant behavior underlying business processes and organizational structures indicated the potential energy savings: a max of 7.08% for Heating, ventilation, and air conditioning (HVAC), 19.46% for lighting and a maximum of 6.34% saving related to office appliances.

scholarly journals Revealing the Impacts of Passive Cooling Techniques on Building Energy Performance: A Residential Case in Hong Kong

2020 ◽  
Vol 10 (12) ◽  
pp. 4188 ◽  
Author(s):  
Chuan-Rui Yu ◽  
Han-Sen Guo ◽  
Qian-Cheng Wang ◽  
Rui-Dong Chang
Keyword(s):  
Hong Kong ◽  
Energy Conservation ◽  
Energy Demand ◽  
Natural Ventilation ◽  
Phase Change Materials ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Passive Cooling ◽  
Total Energy Consumption

Environmental concerns and growing energy costs raise the importance of sustainable development and energy conservation. The building sector accounts for a significant portion of total energy consumption. Passive cooling techniques provide a promising and cost-efficient solution to reducing the energy demand of buildings. Based on a typical residential case in Hong Kong, this study aims to analyze the integration of various passive cooling techniques on annual and hourly building energy demand with whole building simulation. The results indicate that infiltration and insulation improvement are effective in regard to energy conservation in buildings, while the effectiveness of variations in building orientation, increasing natural ventilation rate, and phase change materials (PCM) are less significant. The findings will be helpful in the passive house standard development in Hong Kong and contribute to the further optimization work to realize both energy efficiency and favorably built environments in residential buildings.

scholarly journals Reinforcement Learning-Based School Energy Management System

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6354
Author(s):  
Yassine Chemingui ◽  
Adel Gastli ◽  
Omar Ellabban
Keyword(s):  
Reinforcement Learning ◽  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Management ◽  
Management System ◽  
Learning Algorithm ◽  
Building Energy ◽  
High Energy ◽  
Energy Management System ◽  
Building Energy Management

Energy efficiency is a key to reduced carbon footprint, savings on energy bills, and sustainability for future generations. For instance, in hot climate countries such as Qatar, buildings are high energy consumers due to air conditioning that resulted from high temperatures and humidity. Optimizing the building energy management system will reduce unnecessary energy consumptions, improve indoor environmental conditions, maximize building occupant’s comfort, and limit building greenhouse gas emissions. However, lowering energy consumption cannot be done despite the occupants’ comfort. Solutions must take into account these tradeoffs. Conventional Building Energy Management methods suffer from a high dimensional and complex control environment. In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. In this work, a Deep Reinforcement Learning agent is proposed for controlling and optimizing a school building’s energy consumption. It is designed to search for optimal policies to minimize energy consumption, maintain thermal comfort, and reduce indoor contaminant levels in a challenging 21-zone environment. First, the agent is trained with the baseline in a supervised learning framework. After cloning the baseline strategy, the agent learns with proximal policy optimization in an actor-critic framework. The performance is evaluated on a school model simulated environment considering thermal comfort, CO2 levels, and energy consumption. The proposed methodology can achieve a 21% reduction in energy consumption, a 44% better thermal comfort, and healthier CO2 concentrations over a one-year simulation, with reduced training time thanks to the integration of the behavior cloning learning technique.

scholarly journals Experimental Data and Simulations of Performance and Thermal Comfort in a Typical Mediterranean House

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3311
Author(s):  
Víctor Pérez-Andreu ◽  
Carolina Aparicio-Fernández ◽  
José-Luis Vivancos ◽  
Javier Cárcel-Carrasco
Keyword(s):  
Energy Efficiency ◽  
Thermal Comfort ◽  
Energy Demand ◽  
Natural Ventilation ◽  
Thermal Characterization ◽  
Energy Performance ◽  
Building Stock ◽  
Energy Demands ◽  
Dwelling House ◽  
Account Standard

The number of buildings renovated following the introduction of European energy-efficiency policy represents a small number of buildings in Spain. So, the main Spanish building stock needs an urgent energy renovation. Using passive strategies is essential, and thermal characterization and predictive tests of the energy-efficiency improvements achieving acceptable levels of comfort for their users are urgently necessary. This study analyzes the energy performance and thermal comfort of the users in a typical Mediterranean dwelling house. A transient simulation has been used to acquire the scope of Spanish standards for its energy rehabilitation, taking into account standard comfort conditions. The work is based on thermal monitoring of the building and a numerical validated model developed in TRNSYS. Energy demands for different models have been calculated considering different passive constructive measures combined with real wind site conditions and the behavior of users related to natural ventilation. This methodology has given us the necessary information to decide the best solution in relation to energy demand and facility of implementation. The thermal comfort for different models is not directly related to energy demand and has allowed checking when and where the measures need to be done.

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