Medical, Pharma, Engineering, Science, Technology and Business

^{1}Department of Physics, College of Science, Thi-Qar University, Iraq

^{2}Department of Electronics, College of Engineering, Thi-Qar University, Iraq

- Corresponding Author:
- Abdul-Kareem Mahdi Salih

Department of Physics, College of Science

Thi-Qar University, Iraq

**Tel:**96 47654789654

**E-mail:**[email protected]

**Received date:** December 01, 2015; **Accepted date:** December 21, 2015; **Published date:** December 23, 2015

**Citation:** Salih AKM, Majli AS (2015) Relative Humidity Effect on the Extracted
Wind Power for Electricity Production in Nassiriyah City. J Fundam Renewable
Energy Appl 6:199. doi:10.4172/fundamentals-renewable-energy.1000199

**Copyright:** © 2015 Salih AKM, et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.

**Visit for more related articles at** Journal of Fundamentals of Renewable Energy and Applications

The relative humidity effect on the wind power was extracted as a renewable energy for electricity production in Nassiriyah city - south of Iraq investigated for three years (2011-2013) by theoretical calculations. The study showed that the effect of relative humidity on the annual average of extracted wind power at the minimum altitude which is feasible for electricity production in this city (32 meter for α = 0.4 and 44 meter for α = 0.3) is limited, but it increase with the altitude to be noticeable at high altitude. The percentage loss on the annual average of power for moist air (due to relative humidity effect) uneffective and vary between (0.847% and 1.106%) at altitudes (15 m and 71 m) respectively.

Physics; Renewable energy; Wind energy

The temperature and humidity are important climatic variables that effect on the wind power [1,2]. The previous paper [3] studied the temperature effect on the extracted wind power as a renewable energy in Nassiriyah city (in Iraq) which is located at 31 (east) with 46 (north) intersection lines. This paper is focusing on the study to simulate the relative humidity effect on the extracted wind power in this district. The results are necessary to complement obtained results in reference [3] because of near the district location from Euphrates river, marshes and Shutt Al-Arabe, which make sometimes humid climate features in Nassiriyah city. No data of relative humidity reported at different altitudes in the district just that measured at 10 meter elevation [4]. Software program prepared in this study to compute the relative humidity and investigate its effect on wind power as a function of altitude.

According to the ideal gas law, a cubic meter of air has a certain
number of molecules, and each of those molecules has a certain weight.
Whenever **water** vapour molecules are added to the air, they displaces
some other molecules in the volume of air. Nitrogen molecule is the most
abundant in the air molecules, and it has an atomic weight approach to
14, then the molecules have a weight (atomic mass) approach to 28. For
oxygen, the N_{2} atomic weight is 16, so an O_{2} molecule has a weight of 32.
Hydrogen has an atomic mass of 1, so the molecule of H_{2}O has a weight
of (1+1+16=18). Hence the water molecule is lighter in weight than
either the nitrogen molecule or oxygen molecule. Therefore, the volume
of air that contains some water molecules will be weight less than the
same volume of air without water molecules. This lead to decrease
density which means that the moist air has less density than dry air
at the same temperature [1,5]. Water is extremely found pervasive in
the air as **vapour**. Humidity is the quantity of water vapour present in
air, and there are many varied ways of expressing it such as an absolute
humidity, specific humidity, and relative humidity. Relative humidity is
the amount of water vapour in the air relative to the maximum amount
possible, thus it is at all temperatures and pressures defined as the ratio
of the water vapour pressure to the saturation water vapour pressure,
and it is defined mathematically by the following expression [6-8].

Where RH is the relative humidity, e_{a} is the actual water vapour
pressure, it is contributes to the total atmospheric pressure, defined by
the Antoine equation [9].

Where A = 8.07131, B = 1730.63, C = 233.426, e_{a} is in mmHg (1mm
Hg=133.322 Pascal), T is the temperature in degrees Celsius (C˚). e_{s} (T)
is the saturation vapour pressure (Pascal) at the same temperature (T),
When air enclose above an evaporating water surface, an equilibrium
is reached between the water molecules escaping and returning to the
water reservoir. At this moment, the air is saturated since it cannot
store any extra water molecules. Many algorithms for determining the
saturation vapour pressure [10,11]. Herman Wobus developed Albeit
formula for determining saturation vapour pressure [1,12] as the
following expression.

Where, (3)

For predict the temperature as a function of altitude (z), the following expression used [13].

(4)Where T_{0} is the temperature at the lower altitude (Z_{0}) (10 m in the
study which is represent the tower elevation of Nassiriyah meteorology
station), R_{a} is the temperature laps rate (0.0065 C^{0}m^{-1}).

From the following equation (Poisson equation) [13].

(5)Where P_{0} is the pressure at the lower altitude, then the pressure of
dry air at any altitude (z) can be calculated by the following expression
[13].

Where R the universal gas constant (8.31432), C_{p} is the constant
- pressure specific heat of air, the amount of . The density
of mixture of dry air molecules and water vapour molecules may be
written in term of total pressure, temperature and actual water vapour
pressure by the following expressions [12]:

Where ρ is the moist density ( (Kg/m^{3}), e_{a} = RH* e_{s} (T), P = P_{d} + e_{a} is
the total pressure , P_{d} is the pressure of dry air (partial pressure), R_{d} is
the gas constant for dry air (J/Kg.K), T is the temperature in (K).

The density of dry air as a function of altitude (ρ (z)) calculated by the following equation [14].

(8)Where (ρ_{0}) is the air density (1.255 Kg/m^{3}), (z) is the altitude. The
wind speed calculated by the flowing equation [13,14].

Where (z_{0}), (z) are represents the lower altitude ((10m) in this
study) and other under study altitudes respectively, v and v_{0} are the
wind speed at altitude (z) and (z_{0}) respectively, α is the ground surface
friction coefficient. The net power of a practical wind turbine can be
described by the following equation [15].

Where A the swept area of turbine blades in m^{2} is, v is the wind
speed in m/Sec. C_{P} is the power coefficient, it’s maximum theoretical
value is a brooch to 0.59, but in practical designs the maximum value
below 0.5 [13-16].

The relative humidity, temperature and wind speed data of
Nassiriyah city where measured at (10 m) altitude only (tower elevation
of Nassiriyah meteorology station) for three years' time interval (2011-
2013). These data where feed to Q-Basic program prepared in this
study for simulation of air density, power, power density, pressure,
temperature, relative humidity, saturation vapor pressure, actual vapor
pressure and percentage losses of power because of relative humidity in
moist air as a function of different altitudes (10-71 m) to estimate the
effect of relative humidity on the extracted wind power at the feasible
altitudes for **electricity** production in Nassiriyah city (32 meter for α
= 0.4 and 44 meter for α = 0.3) [17]. Other data used in computations
listed as: a blade radius (r) =10m, air density ρ_{0} = 1.225 Kg/m^{3}), power
coefficient (C_{P}) = 0.5 [13-16], from reference [15] obtained the following
data : ground surface friction coefficient (α) = 0.3, shape factor (k) = 2
m/sec, scalar factor (C) = 7 m/sec.

The computer subroutine programs execute the average daily computations for temperature, pressure, and the wind speed by using equations (4, 6, 9) respectively. The results has been utilized in equations (2, 3, 1), then it is possible to compute the density of moist and dry air by using equations (7, 8) respectively. The result of equation (7, 8) feed to compute the power by equation (10).

For computation checking; (**Figure 1** (A, B, C)) shows the profile
of relative humidity daily average for air according of measured and
calculated data at (10 m) altitude for the time interval study (2011-
2013) respectively. The figures appeared good consistence behaviour,
the relative humidity daily average values decreases at the number of
days (200 ± 20) which are characterized by high temperature degree.
This behaviour is agree with mathematical relations and physical ideas.
(**Figure 2A**-**2C**) confirms the inverse relation between the temperature
and the relative humidity, and they shows the time variation of the daily
average of each relative humidity and temperature at 35 m altitude
for the years (2011-2013) respectively, the figures are in good identity
with the published literature. While the (**Figure 3A**-**3C**) shows the
relation between the annual average of the relative humidity and the
temperature as a function of altitude, and they displayed the increasing
of relative humidity with the increasing of altitude, on the other hand
they displayed the decreasing of annual average of temperature with the
increasing of altitude, that is related to the decreasing of the air pressure
with increment of altitude.

(**Figure 4A**-**4C**) shows the comparison of annual average values of
dry and moist air density as a function of altitude for the years (2011-
2012). The figures clarified that the moist air density was less than the
dry air density that is related to the moist air mass decrement comparing
with the dry air, but each of their (moist and dry air density) increasing
with altitude increment. For explain; there are two important factors
(temperature and relative humidity) affecting on air density, therefore
we have two cases of behaviour, the first one is resulting from the effect
of temperature degree only (dry air density behaviour) thus it seems
the density increasing with the increment of altitude due to decrease
of temperature. The second one is resulting from the relative humidity
and the temperature degree effects (moist air density behaviour) thus
it seems the density increasing with the increment of altitude. The
study explains that the temperature degree is the dominator factor
from the relative humidity (the effect of relative humidity less than the
temperature effect).

**Figure 5** shows the percentage of loss occurring in the annual
average of air density due to relative humidity as a function of altitude for the study time interval (2011-2013) respectively. It is appear that
the max percentage of loss at the low altitude and vice versa (1.092%,
0.852%, 0.868% at (15 m) altitude for years (2011-2013) respectively
(note: the negative sign refer to losses), while these values became 1.09%,
0.848%, and 0.858% at (71 m) altitude respectively. The study explains
that related to mass decrement effect on air density due to humidity
comparing with the volume decrement effect due to **temperature** decrease with the altitude increasing. In general, cane concludes that
the effect of relative humidity on air density in Nassiriyah city is a little.

(**Figure 6A**-**6C**) shows the variation of the annual average of power
density as a function of altitude for the study interval time (2011-2013)
respectively. It appears that the annual average of the power density of
moist air less than dry air. (**Figure 6D**-**6F**) are enhancing (**Figure 6A**- **6C**) and shows the variation of the annual average of **wind** power for
dry and moist air as a function of altitude for the years (2011-2013)
respectively. It appears that the annual average of the power of moist
air less than dry air and the variance increase with the altitude to be
somewhat noticeable at high altitude, the computations results appear
variance between the dry and the moist air at (15 m) altitude 51 watt,
41 watt, and 44 watt for the years (2011-2013) respectively, while this
variance to be approach to 194 watt, 155 watt, and 174 watt for the same
years respectively at 71 m altitude.

**Figure 6: A, B, C.** The profile of the annual average of power density
for the dry and moist air as a function of altitude for the years 2011-2013
respectively. **D, E, F.** The profile of the annual average of power for the dry
and moist air as a function of altitude for the years 2011-2013 respectively.

**Figure 7** shows the percentage of loss occurring on the annual
average of power due to relative **humidity** as a function of altitude for
the study time interval (2011-2013) respectively. It is appear that the
minimum percentage of loss at the low altitude and vice versa (1.083%,
0.847%, 0.864% at (15 m) altitude for years (2011-2013) respectively,
(note: the negative sign refer to losses) while these values became
1.106%, 0.853%, and 0.876% at (71 m) altitude respectively. In general
cane concludes that the effect of relative humidity on the annual average
of wind power which is extracted in Nassiriyah city is a little, and the
percentage of loss on the annual average of power for moist **air** (due to
humidity effect) is increase with the increment of altitude comparing
with the dry air.

The loss in the extracted power from wind as a renewable **energy** for electricity production due to relative humidity in Nassiriyah city -
south of Iraq it is un effective and vary between (0.847% and 1.106%) at
altitudes (15 m , 71 m ) respectively.

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