4.8 Article

On enhancing energy harvesting performance of the photovoltaic modules using an automatic cooling system and assessing its economic benefits of mitigating greenhouse effects on the environment

Journal

JOURNAL OF POWER SOURCES
Volume 376, Issue -, Pages 55-65

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2017.11.051

Keywords

Automatic cooling system; Energy harvesting; Module temperature; Photovoltaic (PV) modules; p-n semiconductor; Wireless sensor network

Funding

  1. Pan-Co International Company of Limited
  2. Yaude Information Ltd.
  3. Ministry of Science and Technology, Executive Yuan, Taiwan [MOST 103-2622-E-002-023-CC2, MOST 104-2622-E-002-010-CC2, MOST 105-2622-E-002-004-CC2, MOST 105-2221-E-002-132-MY3, MOST 106-3113-E-002-012]

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The performance of photovoltaic (PV) modules under outdoor operation is greatly affected by their location and environmental conditions. The temperature of a PV module gradually increases as it is exposed to solar irradiation, resulting in degradation of its electrical characteristics and power generation efficiency. This study adopts wireless sensor network (WSN) technology to develop an automatic water-cooling system for PV modules in order to improve their PV power generation efficiency. A temperature estimation method is developed to quickly and accurately estimate the PV module temperatures based on weather data provided from the WSN monitoring system. Further, an estimation method is also proposed for evaluation of the electrical characteristics and output power of the PV modules, which is performed remotely via a control platform. The automatic WSN-based water-cooling mechanism is designed to avoid the PV module temperature from reaching saturation. Equipping each PV module with the WSN-based cooling system, the ambient conditions are monitored automatically so that the temperature of the PV module is controlled by sprinkling water on the panel surface. The field-test experiment results show an increase in the energy harvested by the PV modules of approximately 17.75% when using the proposed WSN-based cooling system.

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