International Journal of Industrial Engineering and Management

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Vol. 8 No. 2 (2017)
Original Research Article

Simulation Based Productivity Forecast of 1 MW PV Power Plant in the Weather Conditions Typical for Belgrade Region

Milovan Medojević
Faculty of Technical Sciences, University of Novi Sad
Bio
Milana Medojević
Faculty of Technical Sciences, University of Novi Sad
Bio

Published 2017-06-30

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Keywords

  • Simulation,
  • photovoltaic power plant,
  • typical losses

How to Cite

Medojević, M., & Medojević, M. (2017). 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, 8(2), 91–97. https://doi.org/10.24867/IJIEM-2017-2-110

Abstract

Having in mind that energy is being regarded as indispensable to the socioeconomic progress of developing and developed nations, where the main objective implies replacement and reduction of 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. Given the aforementioned this paper provide an overview of 1 MW PV power plant forecast productivity generated by simulation, in the weather conditions typical for the Belgrade city region. 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 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 fixed array power plant and illustratively given in the form of Sankey diagram. Lastly, a variety of graphical data representations are available while the most important ones are given in the study.

 

Article history: Received (01.02.2017); Revised (15.03.2017); Accepted (23.05.2017)  

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