# Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data

^{1}

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Wind Data Collection

_{h}is wind speed at any desired height h, v

_{R}is wind speed at the reference height h

_{R}(10 m in current case) and “a” is called the wind shear exponent. Typical value of the wind shear exponent is 1/7 for on-shore sites, and the same value is used in the current study, unless otherwise specified.

#### 2.2. Analyses of Wind Characteristic at Deokjeok-Do, Baengnyeong-Do and Seo-San

_{i}and v

_{ave}are the specific and average values of a particular variable x, respectively and n is the total number of values of variable x.

^{2}), $R$ is the universal gas constant of dry air (287.05 J/kg·K), and ${T}_{ave}$ is average ambient temperature (°K) as listed in Table 2.

#### 2.3. Wind Turbine Selection

#### 2.3.1. Wind Turbine Class

#### 2.3.2. Extreme Wind Speed (EWS) and Turbulence Intensity (TI)

_{1}) to the largest (x

_{N}), and calculating an empirical value of F(x

_{m}) from the ranked position of x

_{m}. For every value of x there is one value of F(x), hence for each value of x there is one value of GRV as well.

#### 2.4. Selected Wind Turbines for Each Site

^{3}. Five of the same wind turbines were selected for Deokjeok-do and Baengnyeong-do, whereas wind turbines for Seo-San were selected separately because of its higher wind potential.

#### 2.5. Methodology for Technical and Economic Analysis

_{t}(v) is the power curve of selected wind turbine. The following expression is used in the present study to estimate the average power output of each wind turbine [23]:

_{B}is number of wind speed bins. AEP and CF can be estimated using the following two equations, respectively:

_{R}is the rated power of the wind turbine. While estimating the AEP of each wind turbine, transformer losses were considered as 1%, grid losses as 3%, wake losses as 6%, and turbine availability as 95% [3].

_{wT}(k€) can be estimated using Equation (20) [24]:

_{t}are all the benefits during a particular year t, for instance incomes from selling electricity, depreciation credits, production tax credits (PTC) and investment tax credits (ITC). Similarly, C

_{t}are costs, which are basically of two types, initial investment and annually occurring costs. Initial investment includes turbine’s price (blades and nacelle with gear box and generator, as estimated from Equation (20)), tower price, transportation, and installation cost. The last two costs are assumed as 30% of the wind turbine’s price [5]. All other types of initial investments like cables cost, grid connection, etc. are ignored for the sake of simplifying the calculations. On the other hand, annually recurring costs considered in this study include; tax on income and the annual O&M cost, whereas the later one is assumed as 5% of the wind turbine’s price [5]. A project with a relatively higher value (must be greater than zero) of NPV is the most economically feasible project. Another important parameter is internal rate of return (IRR), which is the value of the discount rate at which project’s NPV becomes zero, i.e., the present worth of all costs becomes equal to the present worth of all benefits. Setting Equation (21) equal to zero results in Equation (22), in which the discount rate is IRR:

## 3. Results and Discussion

#### 3.1. Analysis of Wind Turbines for Deokjeok-Do

_{min}and H

_{max}). H

_{min}is constrained by the “minimum ground clearance” whereas H

_{max}should be bounded by the technology available to install and operate turbines on tall towers. The ground clearance of a commercial turbine is the height of the blade tip at its lowest position (when the blade is vertically down). The minimum practical value was taken as 75 ft. (22.86 m), e.g., Ref. [26].

#### 3.2. Analysis of Wind Turbines for Baengnyeong-Do

#### 3.3. Analysis of Wind Turbines for Seo-San

## 4. Conclusions

## Acknowledgment

## Author Contributions

## Conflicts of Interest

## Nomenclature

f(v) | Weibull PDF |

F(v) | Weibull CDF |

k | Weibull shape parameter |

c | Weibull scale parameter |

v | Wind speed |

B_{t} | Benefits |

C_{t} | Costs |

r | Discount rate |

I_{t} | Investment made in year t |

D_{t} | Depreciation credit |

T_{t} | Tax levy |

v_{m} | Mean wind speed |

t | Time |

n | Number of wind data |

v_{i} | Instantaneous wind speed |

V_{R} | Wind speed at reference height |

y_{gumbel} | Gumbel reduced variate |

F(x) | Probability of annual max. speed |

P_{t}(v) | Wind turbine power at wind speed v |

P_{ave} | Average wind turbine power |

N_{B} | Number of speed bins |

P_{R} | Rated power of wind turbine |

## Greek Letters

Σ | Summation |

Г | Gamma Function |

β | Gumbel location parameter |

α | Gumbel scale parameter |

## Abbreviations

probability density function | |

CDF | cumulative distribution function |

SD | Standard deviation |

IEC | International electro-technical commission |

EWS | Extreme wind speed |

GRV | Gumbel reduced variate |

TI | Turbulence intensity |

AEP | Annual energy production |

CF | Capacity factor |

NPV | Net present value |

IRR | Internal rate of return |

LCOE | levelized cost of electricity |

O&M | Operating and maintenance cost |

PBP | Payback period |

## References

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**Figure 2.**Meteorological masts for wind data measurement (

**a**) Deokjeok-do; (

**b**) Baengnyeong-do; (

**c**) Seo-San.

**Figure 3.**Wind rose diagrams for Deokjeok-do from 2005 to 2015 at 10 m from local ground (

**a**) Winter; (

**b**) Spring; (

**c**) Summer; (

**d**) Autumn; (

**e**) Overall.

**Figure 4.**Weibull distribution of Deokjeok-do from 2005 to 2015 at 10 m from the local ground (

**a**) Winter; (

**b**) Spring; (

**c**) Summer; (

**d**) Autumn; (

**e**) Overall.

**Figure 5.**Wind rose diagrams at 10 m from local ground (

**a**) Baengnyeong-do from 2001 to 2016; (

**b**) Seo-San from 1997 to 2016.

**Figure 6.**Weibull distribution at 10 m from local ground (

**a**) Baengnyeong-do from 2001 to 2016; (

**b**) Seo-San from 1997 to 2016.

**Figure 10.**Effect of hub height on wind turbines economics at discount rate of 5% for Deokjeok-do (

**a**) STX 93/2000; (

**b**) U 93E/2000;(

**c**) U 113/2300; (

**d**) HQ 93/2000; (

**e**) WinDS 134/3000.

**Figure 11.**Season-wise energy production of best suited wind turbine for Deokjeok-do at optimum hub height.

**Figure 12.**Effect of hub height on wind turbines economics at discount rate of 5% for Baengnyeong-do (

**a**) STX 93/2000; (

**b**) U 93E/2000; (

**c**) U 113/2300; (

**d**) HQ 93/2000; (

**e**) WinDS 134/3000.

**Figure 13.**Estimations of important parameters at discount rate of 5% and the optimal hub height for Baengnyeong-do (

**a**) optimal hub height; (

**b**) AEP & CF; (

**c**) LCOE & NPV; (

**d**) IRR & PBP; (

**e**) Season-wise energy production of WinDS 134/3000.

**Figure 14.**Effect of hub height on wind turbines economics at discount rate of 5% for Seo-San (

**a**) WinDS 91.3/3000; (

**b**) HJWT 87/2000; (

**c**) 25s 90/2500; (

**d**) STX 72/2000; (

**e**) U 88/2000.

**Figure 15.**Estimations of important parameters at discount rate of 5% and optimal hub height for Seo-San (

**a**) Optimal hub height; (

**b**) AEP & CF; (

**c**) LCOE & NPV; (

**d**) IRR & PBP; (

**e**) Season-wise energy production of HJWT 87/2000.

Location | Latitude | Longitude | Data Acquisition Period | Height (m) | Time Interval |
---|---|---|---|---|---|

Deokjeok-do | 37.22 | 126.14 | 2005–2015 | 10 | 1 h |

Baengnyeong-do | 37.96 | 124.63 | 2001–2016 | 10 | 1 h |

Seo-San | 36.77 | 126.49 | 1997–2016 | 10 | 1 h |

Year | Max. Speed (m/s) | Mean (m/s) | SD | k (-) | c (m/s) | T (°K) | Density (kg/m^{3}) | WPD (W/m^{2}) |
---|---|---|---|---|---|---|---|---|

2005 | 16.5 | 4.2 | 2.7 | 1.7 | 4.7 | 284.0 | 1.243 | 47.2 |

2006 | 17.7 | 4.0 | 2.4 | 1.7 | 4.5 | 285.0 | 1.238 | 39.5 |

2007 | 17.1 | 3.9 | 2.4 | 1.7 | 4.4 | 285.3 | 1.237 | 37.5 |

2008 | 20.6 | 3.5 | 2.6 | 1.4 | 3.9 | 285.2 | 1.238 | 27.2 |

2009 | 14.8 | 2.6 | 2.3 | 1.2 | 2.8 | 285.3 | 1.237 | 11.2 |

2010 | 24.9 | 4.0 | 3.1 | 1.3 | 4.3 | 284.4 | 1.241 | 38.8 |

2011 | 27.0 | 3.8 | 3.2 | 1.2 | 4.1 | 284.7 | 1.240 | 34.4 |

2012 | 31.5 | 4.1 | 3.4 | 1.2 | 4.4 | 285.0 | 1.239 | 44.1 |

2013 | 23.4 | 3.9 | 3.2 | 1.3 | 4.2 | 285.0 | 1.239 | 36.4 |

2014 | 23.4 | 4.0 | 3.3 | 1.3 | 4.3 | 285.8 | 1.235 | 40.4 |

2015 | 18.0 | 3.8 | 2.4 | 1.6 | 4.2 | 285.6 | 1.236 | 33.1 |

Overall Average | 21.4 | 3.8 | 2.8 | 1.4 | 4.2 | 285.0 | 1.238 | 35.4 |

Year | Max. Speed (m/s) | Mean (m/s) | SD | k (-) | c (m/s) | T (°K) | Density (kg/m^{3}) | WPD (W/m^{2}) |
---|---|---|---|---|---|---|---|---|

2001 | 16.0 | 4.1 | 2.3 | 1.9 | 4.6 | 284.2 | 1.242 | 41.8 |

2002 | 27.0 | 5.3 | 3.0 | 1.9 | 6.0 | 284.0 | 1.243 | 95.1 |

2003 | 20.3 | 4.8 | 2.6 | 1.9 | 5.4 | 283.4 | 1.245 | 69.7 |

2004 | 21.5 | 5.3 | 2.8 | 2.0 | 6.0 | 284.9 | 1.239 | 91.5 |

2005 | 20.9 | 5.4 | 2.8 | 2.1 | 6.1 | 284.0 | 1.243 | 99.8 |

2006 | 24.7 | 5.2 | 2.8 | 2.0 | 5.9 | 284.4 | 1.241 | 88.4 |

2007 | 24.3 | 5.0 | 2.8 | 1.9 | 5.6 | 284.8 | 1.239 | 76.2 |

2008 | 18.2 | 4.4 | 2.2 | 2.1 | 5.0 | 284.7 | 1.240 | 52.3 |

2009 | 17.6 | 4.6 | 2.4 | 2.0 | 5.1 | 284.9 | 1.239 | 58.5 |

2010 | 17.2 | 4.5 | 2.4 | 2.0 | 5.1 | 284.2 | 1.242 | 56.8 |

2011 | 21.4 | 4.3 | 2.3 | 2.0 | 4.9 | 283.5 | 1.245 | 49.5 |

2012 | 21.0 | 4.6 | 2.5 | 2.0 | 5.2 | 283.8 | 1.244 | 59.8 |

2013 | 19.8 | 4.5 | 2.3 | 2.1 | 5.1 | 283.9 | 1.244 | 58.0 |

2014 | 17.7 | 4.2 | 2.2 | 2.0 | 4.8 | 284.8 | 1.239 | 46.8 |

2015 | 17.4 | 4.1 | 2.4 | 1.8 | 4.6 | 285.1 | 1.238 | 42.1 |

2016 | 19.4 | 3.8 | 2.2 | 1.8 | 4.3 | 285.1 | 1.238 | 34.4 |

Overall Average | 20.3 | 4.6 | 2.5 | 2.0 | 5.2 | 284.4 | 1.241 | 63.8 |

Year | Max. Speed (m/s) | Mean (m/s) | SD | k (-) | c (m/s) | T (°K) | Density (kg/m^{3}) | WPD (W/m^{2}) |
---|---|---|---|---|---|---|---|---|

1997 | 28.4 | 4.2 | 3.7 | 1.2 | 4.4 | 285.7 | 1.236 | 45.9 |

1998 | 30.6 | 5.2 | 4.4 | 1.2 | 5.5 | 286.4 | 1.233 | 85.6 |

1999 | 28.4 | 5.1 | 4.2 | 1.2 | 5.5 | 285.5 | 1.236 | 82.5 |

2000 | 43.0 | 5.5 | 4.6 | 1.2 | 5.9 | 284.5 | 1.241 | 103.8 |

2001 | 24.4 | 4.9 | 4.0 | 1.3 | 5.3 | 285.0 | 1.239 | 75.1 |

2002 | 32.4 | 5.6 | 4.3 | 1.3 | 6.1 | 285.0 | 1.238 | 108.4 |

2003 | 24.6 | 4.9 | 3.8 | 1.3 | 5.3 | 285.2 | 1.238 | 71.7 |

2004 | 25.4 | 5.2 | 4.2 | 1.3 | 5.5 | 285.0 | 1.238 | 84.8 |

2005 | 24.0 | 5.7 | 4.0 | 1.4 | 6.3 | 284.7 | 1.240 | 114.4 |

2006 | 25.4 | 5.5 | 4.0 | 1.4 | 6.0 | 285.4 | 1.237 | 100.8 |

2007 | 27.0 | 5.4 | 3.8 | 1.5 | 6.0 | 285.6 | 1.236 | 98.5 |

2008 | 23.6 | 5.0 | 3.9 | 1.3 | 5.5 | 285.3 | 1.237 | 78.5 |

2009 | 28.2 | 5.3 | 4.1 | 1.3 | 5.8 | 285.5 | 1.236 | 93.5 |

2010 | 46.8 | 5.5 | 4.2 | 1.3 | 6.0 | 285.0 | 1.238 | 103.3 |

2011 | 28.0 | 5.8 | 4.1 | 1.5 | 6.4 | 284.9 | 1.239 | 120.5 |

2012 | 32.0 | 4.9 | 3.8 | 1.3 | 5.4 | 284.8 | 1.239 | 74.7 |

2013 | 18.6 | 4.3 | 3.4 | 1.3 | 4.6 | 285.0 | 1.239 | 48.3 |

2014 | 19.2 | 3.7 | 3.1 | 1.2 | 3.9 | 285.6 | 1.236 | 31.0 |

2015 | 21.4 | 4.0 | 3.1 | 1.3 | 4.4 | 285.9 | 1.235 | 40.2 |

2016 | 22.0 | 4.0 | 3.1 | 1.3 | 4.3 | 286.1 | 1.234 | 38.2 |

Overall Average | 27.7 | 5.0 | 3.9 | 1.3 | 5.4 | 285.3 | 1.237 | 80.0 |

IEC Wind Turbine Class | ||||
---|---|---|---|---|

Parameter | I | II | III | S |

Reference wind speed (m/s) | 50 | 42.5 | 37.5 | 30 |

Annual average wind speed (m/s) | 10 | 8.5 | 7.5 | 6 |

50-year return gust (m/s) | 70 | 59.5 | 52.5 | 42 |

1-year return gust (m/s) | 52.5 | 44.6 | 39.4 | 31.5 |

Wind Turbine Model | Manufacturer | Rated Power (MW) | Rotor Diameter (m) | IEC Wind Class | Swept Area (m^{2}) | Power Density (m^{2}/kW) |
---|---|---|---|---|---|---|

STX 93/2000 | STX Wind Power | 2 | 93.3 | IIIB | 6837 | 3.42 |

U93E/2000 | Unison | 2 | 93 | S | 6793 | 3.4 |

U113/2300 | Unison | 2.3 | 112.8 | S | 9994 | 4.35 |

HQ93/2000 | Hyundai | 2 | 93 | IIIB | 6793 | 3.4 |

WinDS134/3000 | Doosan | 3 | 134 | S | 14103 | 4.71 |

Wind Turbine Model | Manufacturer | Rated Power (MW) | Rotor Diameter (m) | IEC Wind Class | Swept Area (m^{2}) | Power Density (m^{2}/kW) |
---|---|---|---|---|---|---|

WinDS 91.3/3000 | Doosan | 3 | 91.3 | IA | 6547 | 2.19 |

HJWT 87/2000 | Hanjin | 2 | 87 | IIA | 5945 | 2.98 |

25s 90/2500 | Samsung | 2.5 | 90 | IIA | 6362 | 2.55 |

STX 72/2000 | STX Wind Power | 2 | 70.65 | IIB | 3921 | 1.97 |

U88/2000 | Unison | 2 | 88 | IIA | 6083 | 3.05 |

Parameter | Value |
---|---|

Inflation rate (%) | 3 |

Nominal discount rate (%) | 5 |

Corporate tax rate (%) | 25 |

Depreciation period (Years) | 20 |

Depreciation method | linear approximation |

Depreciation rate (% per year) | 5 |

Electric tariff (€/MWh) | 0.00015 |

Operations period (Years) | 20 |

Monopole-Type Foundation | |
---|---|

Parameter | Value |

Steel cost (€/kg) | 0.64 |

Steel density (kg/m^{3}) | 7870 |

Monopole diameter (m) | 5.5695 |

Monopole thickness (m) | 0.075 |

Wind Turbine Model | Optimum Hub Height (m) | AEP (GWh) | CF (%) | LCOE (€/kWh) | NPV (Million €) | IRR (%) | PBP (Years) |
---|---|---|---|---|---|---|---|

STX 93/2000 | - | - | - | - | - | - | - |

U93E/2000 | - | - | - | - | - | - | - |

U113/2300 | - | - | - | - | - | - | - |

HQ93/2000 | - | - | - | - | - | - | - |

WinDS134/3000 | 140 | 6.37 | 24.26 | 0.077 | 2.07 | 8.13 | 9.72 |

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**MDPI and ACS Style**

Ali, S.; Lee, S.-M.; Jang, C.-M.
Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data. *Energies* **2017**, *10*, 1442.
https://doi.org/10.3390/en10091442

**AMA Style**

Ali S, Lee S-M, Jang C-M.
Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data. *Energies*. 2017; 10(9):1442.
https://doi.org/10.3390/en10091442

**Chicago/Turabian Style**

Ali, Sajid, Sang-Moon Lee, and Choon-Man Jang.
2017. "Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data" *Energies* 10, no. 9: 1442.
https://doi.org/10.3390/en10091442