Modeling and Thermal Analysis of Solar Pond Efficiency in the Urmia Lake Region

  • سال انتشار: 1403
  • محل انتشار: سومین کنفرانس بین المللی پیشرفت های اخیر در مهندسی، نوآوری و تکنولوژی
  • کد COI اختصاصی: EITCONF03_100
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 103
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نویسندگان

Mohamad Reza Aghazadeh

M.Sc. graduate, Department of Energy, Islamic Azad University Science and Research Branch, Tehran, Iran

Hamed Gharedaghi

M.Sc. graduate, School of Mechanical Engineering, University of Tehran, P.O. Box: ۱۱۱۵۵-۴۵۶۳, Tehran, Iran

Mir Esmail Abdollahi

M.Sc. graduate, Department of Agronomy, Khoy Science and Research Branch, Islamic Azad University, Khoy, Iran

چکیده

This study investigates the thermal performance optimization of salinity gradient solar ponds in the Urmia Lake region, a location with significant potential for renewable energy exploitation due to its high solar radiation and abundant salt resources. The declining state of Urmia Lake, exacerbated by unsustainable human activities, presents severe environmental challenges, including the accumulation of residual salts. This research proposes the implementation of solar ponds as a dual solution to both energy generation and the mitigation of salt accumulation in the region. To assess the feasibility and optimize the design of solar ponds in Urmia, a comprehensive numerical simulation was conducted using the Crank-Nicolson method, implemented in MATLAB. The simulation incorporated local meteorological data and theoretical models validated by experimental results. The study focused on maximizing the temperature of the lower convective zone, with simulations revealing that a temperature of ۱۱۵°C could be achieved under optimal conditions, despite the small scale of the modeled pond. The findings suggest that with appropriate design adjustments, solar ponds in Urmia could serve as an effective renewable energy source while also addressing environmental concerns related to the lake's salinity.

کلیدواژه ها

Salinity Gradient Solar Pond, Renewable Energy, Thermal Performance Optimization, MATLAB Simulation, Crank-Nicolson Method

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