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Measurement of meteorological data based on wireless data acquisition system monitoring

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  • Benghanem, M.

Abstract

Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a wireless data acquisition system (WDAS) would help to estimate solar energy potential considering the remote region's energy requirement. This article explains the design and implementation of WDAS for assessment of solar energy. The proposed system consists of a set of sensors for measuring meteorological parameters. The collected data are first conditioned using precision electronic circuits and then interfaced to a PC using RS232 connection via wireless unit. The LabVIEW program is used to further process, display and store the collected data in the PC disk. The proposed architecture permits the rapid system development and has the advantage of flexibility and it can be easily extended for controlling the renewable energy systems like photovoltaic system. The WDAS with executive information systems and reporting tools helps to tap vast data resources and deliver information.

Suggested Citation

  • Benghanem, M., 2009. "Measurement of meteorological data based on wireless data acquisition system monitoring," Applied Energy, Elsevier, vol. 86(12), pages 2651-2660, December.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:12:p:2651-2660
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    1. Ammar Mahjoubi & Ridha Fethi Mechlouch & Ammar Ben Brahim, 2011. "A Low Cost Wireless Data Acquisition System for a Remote Photovoltaic (PV) Water Pumping System," Energies, MDPI, vol. 4(1), pages 1-22, January.
    2. Benghanem, M. & Al-Mashraqi, A.A. & Daffallah, K.O., 2016. "Performance of solar cells using thermoelectric module in hot sites," Renewable Energy, Elsevier, vol. 89(C), pages 51-59.
    3. Qiao, Guofu & Sun, Guodong & Li, Hui & Ou, Jinping, 2014. "Heterogeneous tiny energy: An appealing opportunity to power wireless sensor motes in a corrosive environment," Applied Energy, Elsevier, vol. 131(C), pages 87-96.
    4. Gad, H.E. & Gad, Hisham E., 2015. "Development of a new temperature data acquisition system for solar energy applications," Renewable Energy, Elsevier, vol. 74(C), pages 337-343.
    5. Madeti, Siva Ramakrishna & Singh, S.N., 2017. "Monitoring system for photovoltaic plants: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1180-1207.
    6. BahooToroody, Ahmad & De Carlo, Filippo & Paltrinieri, Nicola & Tucci, Mario & Van Gelder, P.H.A.J.M., 2020. "Bayesian regression based condition monitoring approach for effective reliability prediction of random processes in autonomous energy supply operation," Reliability Engineering and System Safety, Elsevier, vol. 201(C).

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