3. Case study

Exph <sup>¼</sup> cpð Þþ <sup>T</sup><sup>2</sup> � <sup>T</sup><sup>1</sup> <sup>T</sup><sup>0</sup> cpln <sup>T</sup><sup>2</sup>

Wind Solar Hybrid Renewable Energy System

exergy for wind energy [3, 5, 14, 15]:

2.3 Energy and exergy efficiencies

8

ð Þ <sup>T</sup> � <sup>T</sup><sup>0</sup>

ln <sup>T</sup>

<sup>þ</sup> <sup>T</sup><sup>0</sup> ð Þ Ra <sup>þ</sup> <sup>ω</sup>Rv ln <sup>1</sup> <sup>þ</sup> <sup>1</sup>:6078ω<sup>0</sup>

and p are measured temperature and pressure in this study.

ciency and exergy efficiency are calculated as, respectively,

� T<sup>0</sup> cp,a þ ωcp, <sup>v</sup>

Exph ¼ cp,a þ ωcp, <sup>v</sup>

T1 

where the first term and the second term on the right side of Eq. (14) are the enthalpy and entropy contributions, respectively. cp is the specific heat of the flow; T0,T1,T2,Tave are the reference temperature, inlet temperature, outlet temperate, and average temperature, respectively; P<sup>1</sup> and P<sup>2</sup> are the inlet pressure and outlet pressure, respectively (see Figure 1); and R is a constant related to the gas and water vapor constants. Ideally, temperature and pressure at both inlet and outlet are needed to calculate the physical exergy. However, it is cumbersome to measure the temperatures and pressures at both inlet and outlet for the WT stream tube in real applications, not to mention the situation when evaluating the wind energy

resource and/or WT efficiency performance before deploying WTs. In addition, the meteorological variable humidity is not considered in Eq. (14). To handle this difficulty, other studies have provided another formula to calculate the physical

> T<sup>0</sup>

1 þ 1:6078ω 

where cp,<sup>a</sup> and cp,<sup>v</sup> are specific heat of air and water vapor, respectively; ω<sup>0</sup> and ω are the humidity ratio of air at the reference state and at the current state, respectively; Ra and Rv are the gas constant and the water vapor constant, respectively; T<sup>0</sup> and P<sup>0</sup> are the reference temperature and atmospheric pressure, respectively; and T

The efficiency for wind energy systems is explained by using energy efficiency η

<sup>η</sup> <sup>¼</sup> Eout Wwind

<sup>ψ</sup> <sup>¼</sup> Eout

where Wwind is the total input wind energy equal to the total kinetic energy given in Eq. (1) and Ex is the total exergy given in Eq. (13). By incorporating the

and exergy efficiency ψ. The former is obtained as the ratio of useful energy produced by a WT to the total input wind energy, while the latter is defined as the useful exergy created by a WT to the total exergy of the air flow. These general definitions of energy and exergy efficiencies have been introduced in several literature (e.g., [3, 5–7, 16]). However, the specific definitions of useful energy/exergy for wind energy systems are often not very clearly explained in the literature. In order to avoid confusion, here we define that both the useful energy and useful exergy are equal to the rate of electricity output Eout that a WT can produce under a wind speed (i.e., Eout equals to actual output power Pout). Thus, the energy effi-

� <sup>R</sup>ln <sup>P</sup><sup>2</sup> P1 

� ð Þ Ra <sup>þ</sup> <sup>ω</sup>Rv ln <sup>p</sup>

P0

<sup>þ</sup> <sup>1</sup>:6078ωRaln <sup>ω</sup>

Ex (17)

ω0

� cpð Þ <sup>T</sup><sup>0</sup> � Tave T<sup>0</sup>

(14)

(15)

(16)

Using the presented thermodynamic analysis methods for wind energy systems, the wind energy potential is evaluated by investigating the energy and exergy efficiencies of a Goldwind 1.5 MW WT (model GW82/1500) [17], which is assumed to be deployed at Ithaca, New York, where 18-year reanalysis meteorological data are obtained from the Modern-Era Retrospective analysis for Research and Application, version 2 (MERRA-2), the latest atmospheric reanalysis of the modern satellite era produced by NASA's Global Modeling and Assimilation Office [18]. This section explains the site; the meteorological data including wind speed, pressure, temperature, and humidity; and the characteristics of the WT used for thermodynamic analysis.

#### 3.1 Site and data

The wind energy potential is evaluated at Ithaca, which has moderately complex terrain in a landscape dominated by patches of forest, crop fields, hills, waterfalls, and lakes in the Upstate New York (at approximately 42.44° N, 76.50° W, Figure 3). Experiencing a moderate continental climate, Ithaca has long, cold, and snowy winters and warm and humid summers with a dominance of westerly wind flows. The meteorological data are obtained from the MERRA-2 (a meteorological reanalysis data set created by NASA), which has a resolution of 0.5° latitude � 0.625° longitude [19]. Although it does not provide measured data in fields, the meteorological reanalysis is thought as a valuable tool to estimate the long-term variables, such as wind speed and temperature, for subsequent meteorological, climatological, energy, and environmental studies. By specifying the latitude and longitude of Ithaca, five types of meteorological data are retrieved from the

Figure 3. Location of Ithaca, New York, where thermodynamic analysis of a 1.5 WM WT is investigated.

MERRA-2 including 10-m eastward wind U10M (in ms�<sup>1</sup> ), 10-m northward wind V10M (in ms�<sup>1</sup> ), surface pressure PS (in Pa), 10-m air temperature T10M (in K), 10-m specific humidity QV10M (in kg kg�<sup>1</sup> ), as well as their hourly time stamps from January 2000 to December 2017. The 10-m horizontal wind speed U is calculated as <sup>U</sup> <sup>¼</sup> ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi <sup>U</sup>10M<sup>2</sup> <sup>þ</sup> <sup>V</sup>10M<sup>2</sup> , <sup>p</sup> and the humidity ratio <sup>ω</sup> is calculated from the specific humidity as ω ¼ QV10M=ð Þ 1 � QV10M . In total, there are 18 years of hourly meteorological data used for the thermodynamic analysis of the WT, which is assumed to be deployed in Ithaca, New York.

Pout ¼

Table 1.

11

8 >>><

Cut-in wind speed (ms�<sup>1</sup>

Thermodynamic Analysis of Wind Energy Systems DOI: http://dx.doi.org/10.5772/intechopen.85067

Rated wind speed (ms�<sup>1</sup>

Cutout wind speed (ms�<sup>1</sup>

Swept area (m<sup>2</sup>

>>>:

4. Results and discussion

0:0184V<sup>6</sup>

0, V<sup>1</sup> <3 ms�<sup>1</sup> or V<sup>1</sup> >22 ms�<sup>1</sup>

1500 kW, 10:3 ms�<sup>1</sup> <V<sup>1</sup> ≤22 ms�<sup>1</sup>

IEC wind class IIIA Rated power (kW) 15,000

Number of blades 3 Hub height (m) 90

Rated voltage (V) 690

) 3

) 10.3

) 22

) 5325

Power control Active blade pitch control Generator PMDD synchronous generator

Tower Tubular steel tower Foundation Flat foundation

Yaw system 3 induction motors with hydraulic brakes

Converter Full-power convert modular system Control system Microprocessor controlled with remote monitoring

<sup>1</sup> <sup>þ</sup> <sup>30</sup>:8477V<sup>4</sup>

With the available meteorological data and the selected WT properties, assumptions are made for calculating the energy and exergy efficiencies: (1) the air pressure, temperature, and humidity are not significantly changed in the swept area of the WT. Thus, the surface pressure data, 10-m air temperature, and 10-m specific humidity obtained from the MERRA-2 data are directly used for the thermodynamic analyses. (2) Due to the wind shear effect in the atmospheric boundary layer,

the normal wind profile model with a power law exponent of 0.2 is used to convert the 10-m horizontal wind speed to the hub-height (90 m) wind speed according to the IEC standard [20]. It takes about 0.5 hour to convert six channels (five meteorological channels and one channel for time stamps) from the MERRA-2 netCDF4 data to Matlab data and then to calculate 18 years' hourly energy and exergy efficiencies using the developed Matlab scripts. Results and discussion are elaborated in three aspects: (1) WT efficiency variation in time domain, (2) meteorological variables impact on the efficiencies, and (3) uncertainty of meteorological

<sup>1</sup> � <sup>320</sup>:8737V<sup>3</sup>

� <sup>4366</sup>:5508V<sup>1</sup> <sup>þ</sup> <sup>4287</sup>:3549 kW, 3 ms�<sup>1</sup> <sup>≤</sup>V<sup>1</sup> <sup>≤</sup>10:3 ms�<sup>1</sup>

<sup>1</sup> <sup>þ</sup> <sup>1699</sup>:2172V<sup>2</sup>

1

(20)

<sup>1</sup> � <sup>1</sup>:3507V<sup>5</sup>

Technical specifications of the Goldwind 1.5 MW PMDD WT [17].

variables represented by the best-fit distributions.

4.1 Variation of energy and exergy efficiencies in time domain

The energy and exergy efficiencies of the Goldwind WT are calculated by Eqs. (18) and (19), respectively, using the Ithaca meteorological data (wind speed,
