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In buildings, HVAC systems consume a high amount of energy to provide thermal comfort for occupants. A methodology is presented in this paper to control thermostat operation of the buildings considering the effects of indoor and outdoor boundary conditions and phase change material (PCM) characteristics. EnergyPlus v8.1 building energy simulation software was used to analyze the energy performance of the PCM incorporated building models and to implement Fanger model to control HVAC thermostat operation according to BS EN 15251:2007 thermal comfort categories. Three types of building HVAC schedule, PCM with different melting points and layer thicknesses were studied for Madrid climate zone. Moreover, the impact of occupants clothing on the energy consumption was investigated. Furthermore, payback analysis was conducted to find out the economic benefits of PCM integration into the building envelopes. Application of PCM improved the cooling and heating energy performances except for the office model in winter (heating period). Additionally, higher energy savings and lower payback periods were observed when PCM with higher melting point was applied to the buildings. Eventually, energy savings in PCM incorporated models were found to improve further when occupants changed their clothing behavior in winter. [ABSTRACT FROM AUTHOR]

In order to reduce energy consumption in buildings, a solution using phase change materials (PCMs) as thermal energy storage (TES) is presented. During summer nights, cold is stored and delivered during the day to reduce cooling load, whereas in winter, heat from solar air collector is stored for heating during morning and evening hours. Proposed is a stand-alone unit suitable for offices, which consists of plates filled with paraffin RT22HC. The objective of the paper is to examine the functioning of the suggested TES system on an annual basis and to explore the feasibility of using it for both, cooling and heating. First numerical model is set up, which assumes 2D geometry and evaluates thermal response, calculations are carried out in Fluent. Then validation of simulations with experimental results is established. Finally the feasibility of storage unit on an annual basis is demonstrated. [ABSTRACT FROM AUTHOR]

Phase Change Materials (PCM) technology can be used for thermal storage and peak load shaving. This paper presents the optimization study of a PCM-Air heat exchanger as well as the development of load shifting solutions which take into account the thermal comfort of the occupants and the indoor air quality. The exchanger contains macroencapsumated PCM (paraffin) and is conceived in a way that facilitates its integration in a ventilation system. It is aimed to shift space heating electrical consumption from peak to off-peak period. The study is performed using an experimentally validated numerical model based on the heat balance approach and the apparent heat capacity method. Several parameters were investigated during the optimization processes, including heat exchanger dimensions, PCM quantity and properties, seeking the configuration with the optimal compromise between stored heat and the time needed for the charging/discharging process. The numerical model was coupled to a building simulation model with several control strategies investigating different scenarios over a one- month winter period. The scenarios vary with increasing complexity, first considering load shifting and thermal comfort, then adding the final price of electricity consumption and finally taking into account the indoor air quality. [ABSTRACT FROM AUTHOR]

Artificial intelligence techniques have been successfully applied to control dynamic systems looking for an optimal control. Among those techniques, reinforcement learning has been shown as particularly effective at reducing the dimensionality of some real problems and solving control problems by learning from experience. The use of thermal energy storage active systems in the building sector is identified as suitable option to reduce their energy demand for heating and cooling. However, these systems might be expensive and require appropriate control strategies in order to improve the performance of the building. In this paper a ventilated facade with PCM is controlled using a reinforcement learning algorithm. The ventilated facade uses mechanical ventilation during nighttime to solidify the PCM and releases this cold stored to the inner environment during the peak demand period. It is crucial to decide correctly the schedule of charge and discharge process of the PCM according to the weather and indoor conditions. An experimentally validated numerical model is used to test the performance of the control algorithm under different weather conditions. Important improvements on the energy savings due to the use of control strategies were found and supported by the data under the different tested climatic conditions. [ABSTRACT FROM AUTHOR]