IDIEEE:8861039
Published Date2019-01-01
JournalIEEE Access, 2019-01-01, Volume 7 Find other publications in this journal
Author Info
  • Department of Electrical and Electronic Engineering, Khulna University of Engineering and Technology
  • School of Engineering and Information Technology, The University of New South Wales
  • Department of Electrical Engineering and Renewable Energy, Oregon Institute of Technology
  • Oregon Renewable Energy Center (OREC)

Abstract

This paper presents a feasibility and sensitivity analysis of renewable energy-based off-grid and grid-connected microgrids by investigating the potentials of wind and solar energy at different areas, namely, Kuakata, Sitakunda, Magnama, Dinajpur and Rangpur in Bangladesh - a country that experiences a tropical climate. A specialized neural network algorithm has been employed to track the wind speed and solar irradiance all year round in two salient regions and the promising results have been analyzed for making the decision whether the data are reliable for forecasting or not. Four different types of models including PV-Grid, Wind-Grid, Wind-PV-Grid, and off-grid hybrid renewables are designed using the Hybrid Optimization of Multiple Energy Resources (HOMER Pro) software. By considering the key factors: net present cost, cost of energy, renewable fraction, local load demand, availability of renewable energy resources, system economics and greenhouse gas emissions, the optimal hybrid renewable energy system (HRES) configurations (Wind/PV/Grid/Battery) for the mentioned regions are determined. Various sensitivity and optimization variables, such as RE resources, local load demand, grid energy price, nominal discount rate, the life-time of wind turbine, the capacity of wind turbine, PV arrays, converter, and battery are used to make the decision. Detailed sensitivity analyses are performed to investigate how the optimal system configurations change with a tiny variation in input variables and results show output results are more sensitive on the variations in long-term average wind speed and solar irradiance, nominal discount rate, and the lifetime of wind turbines than the other inputs which is definitely a vital finding of this investigation. Finally, considering several decision making factors, a detailed feasibility chart is presented for two distinct nominal discount rates, i.e., 9% and 10%, which depicts the economically viable renewable energy based plant size in the mentioned regions. Although the crux of this paper is based on providing low-cost electricity to people living in rural areas of Bangladesh, our propositions carry with them certain concomitant benefits, not least of which are environmental and social benefits.