Techno-Economic Investigation of Wind Energy Potential in Selected Sites with Uncertainty Factors

Varadharajan Sankaralingam Sriraja Balaguru, Nesamony Jothi Swaroopan, Kannadasan Raju, Mohammed H. Alsharif and Mun-Kyeom Kim
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Varadharajan Sankaralingam Sriraja Balaguru: Electronics and Instrumentation Engineering, RMK Engineering College, Gummidipoondi, Kavaraipettai 6012061, India
Nesamony Jothi Swaroopan: Electronics and Instrumentation Engineering, RMK Engineering College, Gummidipoondi, Kavaraipettai 6012061, India
Kannadasan Raju: Department of Electrical and Electronics Engineering, Sri Venkateswara College of Engineering, Sriprumbudur, Chennai 602117, India
Mohammed H. Alsharif: Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
Mun-Kyeom Kim: Department of Energy System Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Korea

Sustainability, 2021, vol. 13, issue 4, 1-31

Abstract: This work demonstrates a techno-economical assessment of wind energy potential for four passes of Tamil Nadu (Aralvaimozhi, Shencottah, Palghat, and Cumbum) with uncertainty factors. First, a potential assessment was carried out with time-series data, and the Weibull parameters, such as c (scale) and k (shape), were determined using the modern-era retrospective analysis for research and applications (MEERA) data set. Using these parameters, the mean speed, most probable speed, power density, maximum energy-carrying speed of wind power were determined. From the analysis, it was observed that all four passes had better wind parameters; notably, the Aralvaimozhi pass attained a better range of about 6.563 m/s (mean wind speed), 226 W/m 2 (wind power density), 6.403 m/s (most probable wind speed), and 8.699 m/s (max wind speed). Further, uncertainty factors, such as the probability of exceedance (PoE), wind shear co-efficient (WSC), surface roughness, and wake loss effect (WLE), were evaluated. The value of PoE was found to be within the bound for all the locations, i.e., below 15%. In addition, the ranged of WSC showed a good trend between 0.05 and 0.5. Moreover, the surface length of the passes was evaluated and recorded to be 0.0024 m with a 73% energy index. Further, output power, annual energy production (AEP), capacity factor (CF), and cost of wind energy of all four passes were computed using different wind turbine ratings in two cases, i.e., with and without WLE. It was observed that there was a huge profit in loss from all the four locations due to WLE that was estimated to be Rupees (Rs.) 10.07 crores without considering interest components and Rs. 13.66 crores with interest component at a 10% annual rate of interest.

Keywords: techno-economic; probability distribution function (PDF); uncertainty factors; wake loss effect (WLE); Weibull distribution; wind speed; wind power density (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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