THERMAL SCIENCE

International Scientific Journal

Thermal Science - Online First

online first only

Simulation-based design of solar photovoltaic energy generation system for manufacturing support

ABSTRACT
Having in mind that energy is being regarded as indispensable to the socio-economic progress of developing and developed nations, where the main objective implies replacement and reduction of a major portion of the fossil fuels utilization, implementation of renewable energy technologies where natural phenomena are transformed into beneficial types of energy are becoming more and more appreciated and needed. Among renewable energy resources we know today, solar energy is the most beneficial, relatively limitless, effective, and dependable. Having this in mind, the aim of this paper is primarily to help key decision-makers understand the process when considering integration of solar energy to meet their own manufacturing energy needs, or how it is called today, to become "prosumers". Given the aforementioned, this paper provides an overview of detailed simulation methodology for Photovoltaic (PV) system sizing and design for metal-forming manufacturing system energy needs. The simulation is based on NREL (National Renewable Energy Laboratory) photovoltaic performance model which combines module and inverter sub-models with supplementary code to calculate a photovoltaic power system's hourly AC output is given a weather file and data describing the physical characteristics of the module, inverter, and array. Furthermore, the characteristic losses are calculated and presented for a fixed array PV system and illustratively given in the form of a Sankey diagram. A variety of graphical data representations are available while the most important ones are given in the study. Lastly, future research topics were filtered and briefly summarized.
KEYWORDS
PAPER SUBMITTED: 2019-07-19
PAPER REVISED: 2020-03-23
PAPER ACCEPTED: 2020-03-28
PUBLISHED ONLINE: 2020-05-02
DOI REFERENCE: https://doi.org/10.2298/TSCI190719161M
REFERENCES
  1. Raugei, M., et al., The energy return on energy investment (EROI) of photovoltaics: Methodology and comparisons with fossil fuel life cycles, Energy Policy, vol. 45 (2012), pp. 576-582.
  2. Rekinger, M., et al., Global Market Outlook for Solar Power / 2015 - 2019, Brussels, Belgium, 2015.
  3. Medojevic, M., Medojevic, M., Simulation Based Productivity Forecast of 1 MW PV Power Plant in the Weather Conditions Typical for Belgrade Region, International Journal of Industrial Engineering and Management (IJIEM), Vol. 8, No. 2 (2017), pp. 91-97.
  4. Herrmann, C., "Ganzheitliches Life Cycle Management: Nachhaltigkeit und Lebenszyklusorientierung in Unternehmen", Springer-Verlag, Berlin Heidelberg, p. 423, 2010.
  5. United Nations, "Kyoto Protocol to the United Nations Framework Convention on Climate Change," unfccc.int/resource/docs/convkp/kpeng.pdf (Accessed 10 March 2019)
  6. Duflou, J. R., et al., "Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach," CIRP Annals-Manufacturing Technology, Vol. 61, No. 2 (2012), pp. 587-609.
  7. Medojevic, M., et al., Energy Management in Industry 4.0 Ecosystem: A Review on Possibilities and Concerns, Proceedings of the 29th DAAAM International Symposium, pp.0674-0680, B. Katalinic (Ed.), Published by DAAAM International, ISBN 978-3-902734-20-4, ISSN 1726-9679, Vienna, Austria, DOI: 10.2507/29th.daaam.proceedings.097
  8. Pavlovic, T., et al., Simulation of Photovoltaic Systems Electricity Generation Using HOMER software in specific locations in Serbia, Thermal Science, Vol. 17, No. 2 (2013), pp. 333-347.
  9. Klise, G. T., Stein, J. S., Models Used to Assess the Performance of Photovoltaic Systems, SANDIA REPORT, SAND2009-8258, 2009. Available online at: www.osti.gov/bridge
  10. Lalwani, M., et al., Investigation of Solar Photovoltaic Simulation Softwares, International Journal of Applied Engineering Research, Vol. 1, No. 3 (2010), pp. 585-601.
  11. ***, www.appropedia.org/Solar_photovoltaic_software
  12. Chandrakant, D., et al., Performance simulation of grid-connected rooftop solar PV system for small households: A case study of Ujjain, India, Energy Reports, Vol. 4 (2018), pp. 546-553.
  13. Zeyringer M., et al., Analyzing grid extension and stand-alone photovoltaic systems for the cost-effective electrification of Kenya, Energy for Sustainable Development, Vol. 25 (2015), pp. 75-86.
  14. Shukla A.K., Sudhakar K., Baredar P., Exergetic assessment of BIPV module using parametric and photonic energy methods: A review, Energy and Buildings, Vol. 119 (2016), pp. 62-73.
  15. Gilman, P., Dobos, A., DiOrio, N., Freeman, J., Janzou, S., Ryberg, D., SAM Photovoltaic Model Technical Reference Update. 93 pp., (2018), NREL/TP-6A20-67399.
  16. Michalsky, J., The Astronomical Almanac's Algorithm for Approximate Solar Position (1950-2050), Solar Energy, Vol.40, No. 3 (1988), pp. 227-235.
  17. Iqbal, M., An Introduction to Solar Radiation, New York, NY: Academic Press, (1983).
  18. O'Brien, J., Position of the sun given time of day, latitude and longitude, (2012), stack-overflow.com.stackoverflow.com/questions/8708048/position-of-the-sun-given-time-of-day-latitude-and-longitude
  19. Duffie, J., Beckman, W., Solar Engineering of Thermal Processes, 4th ed., NY: Wiley, New York, 2013.
  20. Dunlap, J., Photovoltaic Systems, IL: American Technical Publishers, Homewood, 2007.
  21. Freeman, J., et al., Using Measured Plane-of-Array Data Directly in Photo-voltaic Modeling: Methodology and Validation, 43rd IEEE Photovoltaic Specialists Conference, 5-10 June 2016, Portland, Oregon, (2016), NREL/PO-6A20-66524.www.nrel.gov/docs/fy16osti/66524.pdf
  22. Dobos, A., PVWatts Version 1 Technical Reference, TP-6A20-60272. Golden, CO: National RenewableEnergy Laboratory, (2013), www.nrel.gov/docs/fy14osti/60272.pdf
  23. Perez, R., et al., The Development and Verification of the Perez Diffuse Radiation Model, SAN88-7030. Albuquerque, NM: Sandia National Laboratories, (1988), prod.sandia.gov/techlib/access-control.cgi/1988/887030.pdf
  24. Perez, R., et al., Modeling Daylight Availability and Irradiance Components from Direct and Global Irradiance, Solar Energy Vol.44, No.5 (1990), pp. 271-289.
  25. "Perez Sky Diffuse Model", Modeling Steps. PV Performance Modeling Collaborative. Al-buquerque, NM: Sandia National Laboratories, (2014), pvpmc.sandia.gov/modeling-steps/1-weather-design-inputs/plane-of-array-poa-irradiance/calculating-poa-irradiance/poa-sky-diffuse/perez-sky-diffuse-model/
  26. Liu, B., Jordan, R., A Rational Procedure for Predicting The Long-term Average Performance of Flat plate Solar energy Collectors, Solar Energy, Vol.7, No. 2 (1963), pp. 53-74.
  27. Appelbaum, J., Bany, J., Shadow effect of adjacent solar collectors in large scale systems, Solar Energy, Vol.23 (1979), pp. 497-507.
  28. Deline, C., et al., A Simplified Model of Uniform Shading in Large Photovoltaic Arrays, Solar Energy, Vol. 96 (2013), pp. 274-282.
  29. De Soto, W., et al., Improvement and Validation of a Model for Photovoltaic Array Performance, Solar Energy, Vol. 80, No.1 (2004), pp. 78-88.
  30. De Soto, W., Improvement and Validation of a Model for Photovoltaic Array Performance, University of Wisconsin-Madison, (2004), sel.me.wisc.edu/publications/theses/desoto04.zip
  31. Marion, W., Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations, Solar Energy, Vol.97 (2013), pp. 112-121.
  32. Ryberg, D., Freeman, J., Integration, Validation and Application of a PV Snow Coverage Model in SAM, TP-6A20-64260. Golden, CO: National Renewable Energy Laboratory, (2015). www.nrel.gov/docs/fy15osti/64260.pdf
  33. King, D., et al., Performance Model for Grid-Connected Photovoltaic Inverters, 47 pp.; Albuquerque, NM: Sandia National Laboratories. SAND2007-5036, (2007). prod.sandia.gov/techlib/access-control.cgi/2007/075036.pdf
  34. Ceylan, I., et al., Cooling of a photovoltaic module with temperature controlled solar collector, Energy and Buildings, Vol. 72 (2014), 96-101.
  35. Moharram, K.A., et al., Enhancing the performance of photovoltaic panels by water cooling. Ain Shams Engineering Journal, Vol. 4, No.4 (2013), pp. 869-877.
  36. Bahaidarah, H., et al., Performance evaluation of a PV (photovoltaic) module by back surface water cooling for hot climatic conditions. Energy, Vol. 59 (2013), pp. 445-453.
  37. Alami, A.H., Effects of evaporative cooling on efficiency of photovoltaic modules, Energy Conversion and Management, Vol. 77 (2014), pp. 668-679.
  38. Irwan, Y.M., et al., A new technique of photovoltaic/wind hybrid system in Perlis. Energy Procedia, Vol. 36 (2013), pp. 492-501.
  39. Teo, H.G., et al., An active cooling system for photovoltaic modules. Applied Energy, Vol. 90, No.1 (2012), pp. 309-315.
  40. Du, B., et al., Performance analysis of water cooled concentrated photovoltaic (CPV) system, Renewable & Sustainable Energy Reviews, Vol. 16, No.9 (2012), pp. 6732-6736.
  41. Dorobanţu, L., et al., Experimental assessment of PV Panels front water cooling strategy, International Conference on Renewable Energies and Power Quality (ICREPQ'13), Bilbao (Spain), 20th to 22th March, pp. 1-4, (2013).
  42. Rahimi, M., et al., Design of a self-adjusted jet impingement system for cooling of photovoltaic cells, Energy Conversion and Management, Vol. 83 (2014), pp. 48-57.
  43. Al-shamani, A.N., et al., Nanofluids for improved efficiency in cooling solar collectors -A review, Renewable & Sustainable Energy Reviews, Vol. 38 (2014), pp. 348-367.
  44. Aurora, The ultimate guide to PV system losses - A Solar Designer's Guide for More Accurate Energy Production Estimates, (2018), pp. 22.