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A Capacity Estimation Technique of Solar-Wind Hybrid Power System for an Urban Residential Load
Copyright © IFAC Power Plants and Power Systems Control, Seoul, Korea, 2003
ELSEVIER
IFAC PUBLICATIONS www.elsevier.comllocate/ifac
A CAPACITY ESTIMATION TECHNIQUE OF SOLAR-WIND HYBRID POWER SYSTEM FOR AN URBAN RESIDENTIAL LOAD Byeong-Gook Kwon, Seung-Chul Lee, Chan-Eom Park School ofElectrical & Electronic Engineering Chung-Ang University in Seoul Korea
Abstract: In this paper a teclmique that can estimate the required capacity of a SolarWind Hybrid Power(SWHP) system for an unban residential load is presented. The probability distribution of the power output from SWHP system is calculated from the probability density functions(PDFs) of the solar irradiance and the wind speed for each hour. The size of photovoltaic(PV) array and the nwnber of wind turbines are decided so that the total SWHP system output in one day can meet the total daily residential-load. The available power for battery system charging can be obtained from the difference between the SWHP system generation and the load. Consequently, the distribution of the battery charging power is calculated by convolving the PDFs of both the SWHP system output and the load. A typical local residential load curve is used for illustration and promssing result is obtained. Copyright © 2003 IFAC. Keywords : solar, wind, hybrid, power system, substitute energy, battery charge 1. Introduction
of a SWHP system is computed by adding the average output of a PV system and the wind system
Solar and wind energies are excellent alternatives to the conventional fossil energies which are both limited and problematic. However widespread utillizations of these clean and unlimited energies their low power density and intermittent availability in contrast to their relatively high installation costs. In particular, becomes of the lack proper capacity signing tools, a rule of thumb estimation of the required capacity normally ends up with an inappropriate installed capacity, which further the return rate for the investment. In this paper, a technique is proposed that can estimate the appropriate PV array and wind turbine capacities for a typical local urban house load. The teclmique is based on the probabilities of the solar irradiance and wind speed. The SWHP system is proposed to utilize tlle potential compensations between the solar and the wind energies sizing of the battery system is also discussed. A 10 year data of irradiance and wind speed recorded for every hour of a day are used to compute the PDFs of irradiance and wind speed. The irradiance and the wind speed are considered as random variables studies show that tlle irradiance has the Beta distribution while the wind speed exhibits tlle Weibull distribution [1-3]. Nonnally, the output
[4-6].
In this paper, we obtained the output PDF of a SWHP system from the convolution the output PDFs of the two systems. A typical residential load in an urban area is used for illustration. The output of a SWHP system with a battery bank system is used to supply daily load. Since the battery charging powers are random, ilie PDF for ilie battery charging power are derived by convolving the PDFs of the SWHP system output and the load [6,7]. Then the battery charge-discharge curve is plotted using their expected value for each hour. 2. System Configuration A SWHP system equipped Witll the battery backup system and operated in parallel Witll the utility power system network is shown in Fig. 1. The DC power generated from tlle PV modules and the wind turbine is converted to the AC power through the inverter, and is supplied AC power load. The surplus power is stored to the battery bank. When solar and wind power generation is insufficient, power is supplied from the battery bank or the utility power line. The battery bank can be discharged up to 40% of its total capacity.
203
3.2 Wind Power System Output Prediction The wind speed distribution is typically modelled with the Weibull Distribution, which can be given as
k1
k(V~J - exp [( VJk] fv{V) =~ - ~ where, Control System
Solar Array
Fig. I. Solar-Wind Hybrid Power Configuration
(4)
V: wind speed[m/s) c : scale parameter k : shape parameter
Fig. 2 shows the power output characteristics of a typical wind turbine.
3. SWHP System Output Prediction
3.1 PV Module Output Prediction P
For the irradiance distribution analysis, the Beta Distribution is used which was verified by ChiSquare Goodness of Fit Test. Then the probability distribution density(PDF) for the solar irradiance can be expressed as
j,(r)= r(a+p)
a-I[l __r_ J
fJ
_r_
[ J
f(a)rUn rma,
r
r
r[W 1m
2
) :
--,
1
-
(1)
rma.,
Vc ,\
instant irradiance
VI furling
Vr
"cut in
r: Gamma function
where,
.-
rated power
rated Wind Speed (m/s]
Fig. 2. Wind Turbine Output Characteristics
rmax [W I m 2) : maximum irradiance From the figure, the power output from the wind turbine can be expressed as
a : shape parameter ~ : shape parameter
Ps
Then the instant output
and
output PSmax of the PV module can be computed
Pw{V) =
a+bV
M
A=LA",
1] =
=mc::.=l~_ _
a=
(2)
A
m=1
where,
where, n: order
LAm 77",
From
fJ
Smu
~)
r
1
iF (V)
c
in Eq.(4), the cumulative distribution
of the wind speed can be obtained by integration as
[-.!L]a-I[l_ ~]fJ-1
) = f(a + P) l(a)l( R) P.
V)
p. r:,n r Vn _Vn
r
From Eq.(2). the PDF of the solar power generation that can be obtained from the PV module of area A[ m') can be expressed with
Ps
(Vc -
~
(5)
r V n _ Vn
77", : PV module efficiency
r (
(Vf
b=P.
1] : PV array efficiency
} Ps
(Vr ~ V < Vf)
c
A: PV array area Am : PV module area (m=I,2, ... ,M)
(v" < V < Vr>
n
~ 0
from
M
{V~VJ
0
the maximum
(6)
Therefore the cumulative distribution of the wind turbine output can be expressed with
(3)
P.
Smu
204
In this paper, the capacity of the PV array and the wind turbine for satisfying the total daily load is decided simply as
Pw = 0 Fp)Pw )= Fv[V(Pw)-Fv(VJ],O
1- Fv (Vf ) + Fv (Vc),
(13)
I
-a];;
P. where, V(Pw ) = [ ~
where, As : PVarray area[m']
nw : number of wind turbines By differencing
Ps : PV module output [W/ m']
Fpw (Pw ) with Pw , the PDF for
Pw : wind turbine output lW/ea]
the wind turbine output can be obtained as follows;
Fig. 3 shows an example of the typical daily residential load pattern of the urban area in Korea[8]. According to energy statistical research result in 2000 year, a monthly electric power energy used per house in domestic urban areas is about I78[KWh] and a daily electric power energy used is about 6300[Wh]. soo . . , - - - - - - - - - - - - - - - - - ,
3.3 Combined System Output
The PDF for the output of the SWHP system can be obtained by convolving the PDFs shown in Eq.(3) and Eq.(8) as 250
(9)
200
1S0
4. Optimum Battery Bank Size Calculation
to
C(t)
= P(t) -
L(t)
,a
t..
12.
fS
20
22
:2...
TIME rh]
Available battery charging power C(t) is the difference between the SWHP system output and the demand, i.e..
Fig. 3. simulated load pattern of residential house in urban area Expected output values of both the PV and the wind power systems are calculated from Eq.(3) and (8). The output from a 50W PV module is predicted as about 160Wh. The output of a 400W wind turbine is about 290Wh. A 400W wind turbine and 38 x 1.9kW PV array are estimated as appropriate for satisfying the total load. Based on Eq.(l2) and for the house load shown in Figure 3, the hourly battery charge-discharge power is computed and is plotted in Figure 4.
(10)
Because demand load is also random variable as SWHP system output, need to express by statistical method. In this paper, the each hourly assumed to have uniform between the maximum and the minimum load as
800 -,...-
---,
(11)
o
otherwise
Therefore. the PDF of the battery charging power for each hour can be formulated as (12)
Expected value of the battery charging power C becomes positive when battery bank system is charged and negative when discharged.
10
12
14
16
18
20
22
TIME [hour]
Fig. 4 Battery Charge-Discharge Curve 205
24
methods that can reflect the price structure of the utility power to maximize the return for the investment for the SWHP system and the effects of the loss of power supply probability(LPSP).
From Figure 4, Area El is the amount of power needed to be discharged from the battery bank system, which is about 4000[Wh). The Ampere-Hour capacity of the battery bank system is calculated from
References
Battery Capacity [AH]
where,
=
C VxUxR
(14)
[1] Imad Abouzahr, "Loss of Power Supply Probability of Stand-Alone Photovoltaic Systems", IEEE Trans. on Energy Conversion, Vo!. 6, No. 1, March 1991 [2] S. H. Karaki, "Probabilistic Performance Assessment of Autonomous Solar-Wind Energy Conversion Systems", IEEE Trans. on Energy Conversion, Vo1.14, No.3, Sep. 1999 [3] Bogdan S. Borowy, "Methodology for Optimally Sizing the Combination of a Battery Bank and PV Array in a WindlPV Hybrid System", IEEE Trans. on Energy Conversion, Vo!. 11, No. 2, June 1996 [4] Ziyad M. Salameh, "Photovoltaic Module-Site Matching Based on the Capacity Factors", IEEE Trans. on Energy Conversion, Vo!. 10, No. 2, June 1995 [5] Bogdan S. Borowy, "Optimum Photovoltaic Array Size for Hybrid WindlPV System", IEEE Trans. on Energy Conversion, Vo!. 9, No. 3, Sep. 1994 l. [6] Fadia M.A.GHALL, "Simulation and Analysis of Hybrid Systems using Probabilistic Techniques", Power Conversion Conference-Nagaoka 1997, Proceedings of the, Vo12, 1997 [7] Imad Abouzahr, "Loss of Power Supply Probability of Stand-Alone Wind Conversion Systems : A Closed Form Solution Approach", IEEE Trans. on Energy Conversion, Vo!. 5, No. 3, September 1990. [8] "Load curve data", Korea Electric Power Corporation, December 2000.
C: charge energy[Wh] V: voltage U : discharge depth rate R : inverter efficiency
In the Equation (14), with the battery bank system voltage of 12V, the discharge depth rate of 60% and the inverter efficiency of 60%, the minimum capacity of battery bank system is calculated as 620[AH]. Currently, the SWHP system shown in Figure 5 and 6 are being installed on the roof of our engineering college for test.
Fig. 5 System Installation
Fig. 6. System Control Panel 5. Conclusion In this paper a technique that can estimated tile appropriate SWHP system capacity for a typical local urban home is proposed. Although the capacity of the SWHP system is computed based on tile total daily demand. further study is needed to develop 206
ELSEVIER
IFAC PUBLICATIONS www.elsevier.comllocate/ifac
A CAPACITY ESTIMATION TECHNIQUE OF SOLAR-WIND HYBRID POWER SYSTEM FOR AN URBAN RESIDENTIAL LOAD Byeong-Gook Kwon, Seung-Chul Lee, Chan-Eom Park School ofElectrical & Electronic Engineering Chung-Ang University in Seoul Korea
Abstract: In this paper a teclmique that can estimate the required capacity of a SolarWind Hybrid Power(SWHP) system for an unban residential load is presented. The probability distribution of the power output from SWHP system is calculated from the probability density functions(PDFs) of the solar irradiance and the wind speed for each hour. The size of photovoltaic(PV) array and the nwnber of wind turbines are decided so that the total SWHP system output in one day can meet the total daily residential-load. The available power for battery system charging can be obtained from the difference between the SWHP system generation and the load. Consequently, the distribution of the battery charging power is calculated by convolving the PDFs of both the SWHP system output and the load. A typical local residential load curve is used for illustration and promssing result is obtained. Copyright © 2003 IFAC. Keywords : solar, wind, hybrid, power system, substitute energy, battery charge 1. Introduction
of a SWHP system is computed by adding the average output of a PV system and the wind system
Solar and wind energies are excellent alternatives to the conventional fossil energies which are both limited and problematic. However widespread utillizations of these clean and unlimited energies their low power density and intermittent availability in contrast to their relatively high installation costs. In particular, becomes of the lack proper capacity signing tools, a rule of thumb estimation of the required capacity normally ends up with an inappropriate installed capacity, which further the return rate for the investment. In this paper, a technique is proposed that can estimate the appropriate PV array and wind turbine capacities for a typical local urban house load. The teclmique is based on the probabilities of the solar irradiance and wind speed. The SWHP system is proposed to utilize tlle potential compensations between the solar and the wind energies sizing of the battery system is also discussed. A 10 year data of irradiance and wind speed recorded for every hour of a day are used to compute the PDFs of irradiance and wind speed. The irradiance and the wind speed are considered as random variables studies show that tlle irradiance has the Beta distribution while the wind speed exhibits tlle Weibull distribution [1-3]. Nonnally, the output
[4-6].
In this paper, we obtained the output PDF of a SWHP system from the convolution the output PDFs of the two systems. A typical residential load in an urban area is used for illustration. The output of a SWHP system with a battery bank system is used to supply daily load. Since the battery charging powers are random, ilie PDF for ilie battery charging power are derived by convolving the PDFs of the SWHP system output and the load [6,7]. Then the battery charge-discharge curve is plotted using their expected value for each hour. 2. System Configuration A SWHP system equipped Witll the battery backup system and operated in parallel Witll the utility power system network is shown in Fig. 1. The DC power generated from tlle PV modules and the wind turbine is converted to the AC power through the inverter, and is supplied AC power load. The surplus power is stored to the battery bank. When solar and wind power generation is insufficient, power is supplied from the battery bank or the utility power line. The battery bank can be discharged up to 40% of its total capacity.
203
3.2 Wind Power System Output Prediction The wind speed distribution is typically modelled with the Weibull Distribution, which can be given as
k1
k(V~J - exp [( VJk] fv{V) =~ - ~ where, Control System
Solar Array
Fig. I. Solar-Wind Hybrid Power Configuration
(4)
V: wind speed[m/s) c : scale parameter k : shape parameter
Fig. 2 shows the power output characteristics of a typical wind turbine.
3. SWHP System Output Prediction
3.1 PV Module Output Prediction P
For the irradiance distribution analysis, the Beta Distribution is used which was verified by ChiSquare Goodness of Fit Test. Then the probability distribution density(PDF) for the solar irradiance can be expressed as
j,(r)= r(a+p)
a-I[l __r_ J
fJ
_r_
[ J
f(a)rUn rma,
r
r
r[W 1m
2
) :
--,
1
-
(1)
rma.,
Vc ,\
instant irradiance
VI furling
Vr
"cut in
r: Gamma function
where,
.-
rated power
rated Wind Speed (m/s]
Fig. 2. Wind Turbine Output Characteristics
rmax [W I m 2) : maximum irradiance From the figure, the power output from the wind turbine can be expressed as
a : shape parameter ~ : shape parameter
Ps
Then the instant output
and
output PSmax of the PV module can be computed
Pw{V) =
a+bV
M
A=LA",
1] =
=mc::.=l~_ _
a=
(2)
A
m=1
where,
where, n: order
LAm 77",
From
fJ
Smu
~)
r
1
iF (V)
c
in Eq.(4), the cumulative distribution
of the wind speed can be obtained by integration as
[-.!L]a-I[l_ ~]fJ-1
) = f(a + P) l(a)l( R) P.
V)
p. r:,n r Vn _Vn
r
From Eq.(2). the PDF of the solar power generation that can be obtained from the PV module of area A[ m') can be expressed with
Ps
(Vc -
~
(5)
r V n _ Vn
77", : PV module efficiency
r (
(Vf
b=P.
1] : PV array efficiency
} Ps
(Vr ~ V < Vf)
c
A: PV array area Am : PV module area (m=I,2, ... ,M)
(v" < V < Vr>
n
~ 0
from
M
{V~VJ
0
the maximum
(6)
Therefore the cumulative distribution of the wind turbine output can be expressed with
(3)
P.
Smu
204
In this paper, the capacity of the PV array and the wind turbine for satisfying the total daily load is decided simply as
Pw = 0 Fp)Pw )= Fv[V(Pw)-Fv(VJ],O
1- Fv (Vf ) + Fv (Vc),
(13)
I
-a];;
P. where, V(Pw ) = [ ~
where, As : PVarray area[m']
nw : number of wind turbines By differencing
Ps : PV module output [W/ m']
Fpw (Pw ) with Pw , the PDF for
Pw : wind turbine output lW/ea]
the wind turbine output can be obtained as follows;
Fig. 3 shows an example of the typical daily residential load pattern of the urban area in Korea[8]. According to energy statistical research result in 2000 year, a monthly electric power energy used per house in domestic urban areas is about I78[KWh] and a daily electric power energy used is about 6300[Wh]. soo . . , - - - - - - - - - - - - - - - - - ,
3.3 Combined System Output
The PDF for the output of the SWHP system can be obtained by convolving the PDFs shown in Eq.(3) and Eq.(8) as 250
(9)
200
1S0
4. Optimum Battery Bank Size Calculation
to
C(t)
= P(t) -
L(t)
,a
t..
12.
fS
20
22
:2...
TIME rh]
Available battery charging power C(t) is the difference between the SWHP system output and the demand, i.e..
Fig. 3. simulated load pattern of residential house in urban area Expected output values of both the PV and the wind power systems are calculated from Eq.(3) and (8). The output from a 50W PV module is predicted as about 160Wh. The output of a 400W wind turbine is about 290Wh. A 400W wind turbine and 38 x 1.9kW PV array are estimated as appropriate for satisfying the total load. Based on Eq.(l2) and for the house load shown in Figure 3, the hourly battery charge-discharge power is computed and is plotted in Figure 4.
(10)
Because demand load is also random variable as SWHP system output, need to express by statistical method. In this paper, the each hourly assumed to have uniform between the maximum and the minimum load as
800 -,...-
---,
(11)
o
otherwise
Therefore. the PDF of the battery charging power for each hour can be formulated as (12)
Expected value of the battery charging power C becomes positive when battery bank system is charged and negative when discharged.
10
12
14
16
18
20
22
TIME [hour]
Fig. 4 Battery Charge-Discharge Curve 205
24
methods that can reflect the price structure of the utility power to maximize the return for the investment for the SWHP system and the effects of the loss of power supply probability(LPSP).
From Figure 4, Area El is the amount of power needed to be discharged from the battery bank system, which is about 4000[Wh). The Ampere-Hour capacity of the battery bank system is calculated from
References
Battery Capacity [AH]
where,
=
C VxUxR
(14)
[1] Imad Abouzahr, "Loss of Power Supply Probability of Stand-Alone Photovoltaic Systems", IEEE Trans. on Energy Conversion, Vo!. 6, No. 1, March 1991 [2] S. H. Karaki, "Probabilistic Performance Assessment of Autonomous Solar-Wind Energy Conversion Systems", IEEE Trans. on Energy Conversion, Vo1.14, No.3, Sep. 1999 [3] Bogdan S. Borowy, "Methodology for Optimally Sizing the Combination of a Battery Bank and PV Array in a WindlPV Hybrid System", IEEE Trans. on Energy Conversion, Vo!. 11, No. 2, June 1996 [4] Ziyad M. Salameh, "Photovoltaic Module-Site Matching Based on the Capacity Factors", IEEE Trans. on Energy Conversion, Vo!. 10, No. 2, June 1995 [5] Bogdan S. Borowy, "Optimum Photovoltaic Array Size for Hybrid WindlPV System", IEEE Trans. on Energy Conversion, Vo!. 9, No. 3, Sep. 1994 l. [6] Fadia M.A.GHALL, "Simulation and Analysis of Hybrid Systems using Probabilistic Techniques", Power Conversion Conference-Nagaoka 1997, Proceedings of the, Vo12, 1997 [7] Imad Abouzahr, "Loss of Power Supply Probability of Stand-Alone Wind Conversion Systems : A Closed Form Solution Approach", IEEE Trans. on Energy Conversion, Vo!. 5, No. 3, September 1990. [8] "Load curve data", Korea Electric Power Corporation, December 2000.
C: charge energy[Wh] V: voltage U : discharge depth rate R : inverter efficiency
In the Equation (14), with the battery bank system voltage of 12V, the discharge depth rate of 60% and the inverter efficiency of 60%, the minimum capacity of battery bank system is calculated as 620[AH]. Currently, the SWHP system shown in Figure 5 and 6 are being installed on the roof of our engineering college for test.
Fig. 5 System Installation
Fig. 6. System Control Panel 5. Conclusion In this paper a technique that can estimated tile appropriate SWHP system capacity for a typical local urban home is proposed. Although the capacity of the SWHP system is computed based on tile total daily demand. further study is needed to develop 206