Design, experimental validation, and economic assessment of a hybrid parabolic trough collector – photovoltaic system with water-gravity solar tracking

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Authors: Aakash Kumar Nimesh, Tangellapalli Srinivas
Cited by: 0

Abstract

Solar energy continues to play a central role in meeting the growing demand for clean power, yet challenges remain in improving system efficiency and reducing cost. Hybrid configurations that combine photovoltaic (PV) and thermal technologies offer a pathway toward better utilization of solar input; however, most parabolic trough collectors (PTCs) rely on torque-motor tracking, which increases mechanical complexity and operating expenses. To make such systems more accessible and economical, a simpler and more robust tracking method is needed. This study examines a water-gravity tracking approach as an alternative to motorized systems. A 5.93 m2 PTC integrated with PV panels was built and tested to evaluate this concept. The work introduces a counterweight-free tracking arrangement in which the system’s mass is positioned below its center of gravity, enabling tilt to be achieved by transferring water between two tanks. The collector’s motion was analyzed using a mathematical model for the optimum tilt angle and validated experimentally. Testing at a flow rate of 200 LPH yielded an average tracking error of 1.55°, a thermal efficiency of 11.94%, a PV efficiency of 11.24%, and an overall efficiency of 11.91%. Analytical modeling supported these results, while economic assessment indicated a heating cost of INR 2.31 per kilogram of water heated and a payback period of 2.97 years with subsidy support. These findings demonstrate that the proposed water-gravity tracking mechanism provides a practical, low-cost, and energy-autonomous option for hybrid PTC-PV systems, improving their suitability for decentralized solar-thermal applications.

Fields of Study & Subjects

Solar Thermal and Photovoltaic Systems Solar Energy Systems and Technologies Photovoltaic System Optimization Techniques

Publication details

Journal / source
Figshare
Publication date
1 January 2026
Language
EN
Document type
Dataset