Transient optimization of annual performance of a photovoltaic thermal system based on accurate estimation of coolant water temperature: A comparison with conventional methods

One of the most critical parameters affecting the performance of a hybrid Photovoltaic Thermal (PV/T) panel is the coolant inlet fluid temperature. There are several approaches to estimate the water inlet temperature. This paper discusses the effects of an accurate evaluation of the actual temperatu...

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Bibliographic Details
Main Authors: Yaser Maleki, Fathollah Pourfayaz, Mehdi Mehrpooya
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Case Studies in Thermal Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X2100558X
Description
Summary:One of the most critical parameters affecting the performance of a hybrid Photovoltaic Thermal (PV/T) panel is the coolant inlet fluid temperature. There are several approaches to estimate the water inlet temperature. This paper discusses the effects of an accurate evaluation of the actual temperature of the tap water that enters the system on the electrical efficiency and the optimal design of panels to maximize the electrical performance through a year. To accurately approximate the coolant water temperature, an approach based on the soil temperature at a depth of 1 m and theoretical and experimental data through a year in the city of Tehran, Iran, had been used. Eight design parameters had been selected to perform a sensitivity analysis; seven of them found to be effective on the electrical efficiency. Afterward, an optimization task utilizing genetic algorithm had been done. Finally, the performance of the design optimized based on the more accurate temperature of the water was compared with the performances of designs optimized based on the conventional temperatures of water. The annual results show up to 4.02% more electrical power generation versus models that approximate the inlet water temperature based on the ambient temperature.
ISSN:2214-157X