Air–PCM heat exchanger for peak load management: Experimental and simulation. (July 2016)

• Record Type: Journal Article
• Authors: Stathopoulos, N.; El Mankibi, M.; Issoglio, R.; Michel, P.; Haghighat, F.
• Is Part Of: Solar energy. Volume 132(2016)
• Page Start: 453
• Page End: 466
• Publication Date: 2016-07
• Subjects: Thermal storage -- PCM -- Heat exchanger -- Peak load shifting; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2016.03.030
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: Elaboration of air–PCM heat exchanger for peak load shifting purposes. Integration in the ventilation system and coupling with an experimental test cell. Characterization of the heat exchanger for different airflow rates. Development of a numerical model for heat exchanger and building simulation. Validation of the model and preliminary control strategies. Abstract: Peak power consumption is becoming an increasing problem worldwide and particularly in France during the late afternoon winter periods. This paper describes the experimental and numerical studies carried out to investigate the potential of a PCM (phase change material) – Air heat exchanger, conceived for load shifting purposes. The objective is to possess the necessary tools for the development of advanced control strategies taking into account various factors: peak power reduction, thermal comfort and indoor air quality. The experimental approach involved the construction of a heat exchanger coupled to an experimental cell. The heat storage system is composed of a set of PCM (paraffin) plates, embedded in the exchanger and integrated in a ventilation system. In parallel, a numerical model was developed using the apparent heat capacity approach and the finite differences method. Furthermore, a series of characterization tests was conducted and the experimental data were used for model calibration and validation. The model was then coupled with a building simulation program, presenting good agreement between the integrated model prediction and the experimental data. Finally, a preliminary control strategy of the test cell is presented along with results demonstrating the capabilities of such system for peak load management.