Mass Flow Control Strategy for Maximum Energy Extraction in Thermal Energy Storage Tanks

Abstract This paper introduces an experimental approach to enhance thermal energy storage (TES) tank performance by employing a novel control strategy and an automatic flow valve. The valve adjusts mass flow to minimize heat loss and maximize useful heat within a specified input–output temperature range. Experiments were conducted indoors, simulating input heat via an electric heating element, and adhering to ANSI/ASHRAE 93-2010 standards. In the proposed control strategy, the set point is self-regulated based on an input value which in this case is the heat introduced into the TES system. In this way, when there is more input heat available, the mass flow will increase to obtain more useful heat at the output and, on the contrary, when there is less heat available, the mass flow will be reduced to obtain greater exergy. A comparison between this strategy and conventional on–off control systems was conducted, evaluating their performance based on useful heat obtained over an 8-h period with varying input heat levels. Results demonstrate that the proposed flow control methodology consistently outperforms on–off control, achieving a maximum 13.56% increase in useful heat under optimal conditions. This underscores the effectiveness of the novel control strategy in maximizing thermal energy storage tank efficiency.

Authors

Institutions

Publication Details

Journal
Journal of Solar Energy Engineering
Published
2024-11-18
DOI
https://doi.org/10.1115/1.4067196
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mass Flow Control Strategy for Maximum Energy Extraction in Thermal Energy Storage Tanks

Orlando Montoya-Márquez, Leonardo Jesus Valdivia, Hector Acevedo
Journal of Solar Energy Engineering
Hybrid Renewable Energy Systems
article

Mass Flow Control Strategy for Maximum Energy Extraction in Thermal Energy Storage Tanks

Orlando Montoya-Márquez, Leonardo Jesus Valdivia, Hector Acevedo
article en

Abstract

Abstract This paper introduces an experimental approach to enhance thermal energy storage (TES) tank performance by employing a novel control strategy and an automatic flow valve. The valve adjusts mass flow to minimize heat loss and maximize useful heat within a specified input–output temperature range. Experiments were conducted indoors, simulating input heat via an electric heating element, and adhering to ANSI/ASHRAE 93-2010 standards. In the proposed control strategy, the set point is self-regulated based on an input value which in this case is the heat introduced into the TES system. In this way, when there is more input heat available, the mass flow will increase to obtain more useful heat at the output and, on the contrary, when there is less heat available, the mass flow will be reduced to obtain greater exergy. A comparison between this strategy and conventional on–off control systems was conducted, evaluating their performance based on useful heat obtained over an 8-h period with varying input heat levels. Results demonstrate that the proposed flow control methodology consistently outperforms on–off control, achieving a maximum 13.56% increase in useful heat under optimal conditions. This underscores the effectiveness of the novel control strategy in maximizing thermal energy storage tank efficiency.

Journal of Solar Energy EngineeringVol. 147(3)
Centro de Investigación y Proyectos en Ambiente y Desarrollo (MX), Universidad Panamericana (MX)
Affordable and clean energy
Openalex Percentile: Top 80%
Hybrid Renewable Energy Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.