Standardised methods for the determination of key performance indicators for thermal energy storage heat exchangers

• Published in: Renewable & sustainable energy reviews 2023-04, Vol.176, p.113139, Article 113139
• Main Authors: Beyne, W., T'Jollyn, I., Lecompte, S., Cabeza, L.F., De Paepe, M.
• Format: Article
• Language: English
• Subjects: (dis)charging time; Charging time energy fraction; Effectiveness-number of transfer units; Heat exchanger; Latent thermal energy storage; Solidification/melting time
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2022.113139

Latent thermal energy storage (LTES) heat exchangers can provide energy storage in a broad range of energy systems. Implementing LTES heat exchangers requires an assessment of their performance in a given system. The performance of a LTES heat exchanger is described by its performance indicators which are classified as technical, economical, and life-cycle indicators. The current paper focusses on the technical performance indicator and specifically on predictive methods which aid the assessment of the performance of a LTES heat exchanger in a system. To structure the analysis, a thermodynamic framework is provided which allows to clearly define LTES heat exchangers and classify the technical performance indicators. In a second step, the literature is reviewed for reported technical performance indicators with a specific focus on predictive methods for these indicators. The averaged effectiveness-number of transfer units (ε-NTU) and phase change time method are identified as important predictive models, analyzed, and compared based on their theoretical derivation. The relation between the averaged effectiveness and phase change time is investigated both theoretically and based on data available in literature which results in recommendations for standardizing the characterization of LTES heat exchangers. By standardizing characterization of LTES heat exchangers, researcher can assess their performance in different energy systems without additional experiments or CFD calculations. •A thermodynamic framework is developed.•Based on the framework, reported performance indicators are categorized.•Predictive models for phase change time and effectiveness are derived.