optimum sizing of a stand-alone wind-diesel system on the basis of life cycle cost analysis
DESCRIPTION
OPTIMUM SIZING OF A STAND-ALONE WIND-DIESEL SYSTEM ON THE BASIS OF LIFE CYCLE COST ANALYSIS. Kaldellis J.K. , Kavadias K. A. Lab of Soft Energy Applications & Environmental Protection, Mechanical Eng. Dept, TEI of Piraeus P.O. Box 41046, Athens 12201, GREECE - PowerPoint PPT PresentationTRANSCRIPT
OPTIMUM SIZING OF A STAND-ALONE WIND-DIESEL SYSTEM ON THE BASIS OF LIFE CYCLE COST ANALYSIS
Kaldellis J.K., Kavadias K.A.
Lab of Soft Energy Applications & Environmental Protection,
Mechanical Eng. Dept, TEI of Piraeus
P.O. Box 41046, Athens 12201, GREECE
Tel. +30-210-5381237, FAX +30-210-5381348
E-mail: [email protected], http://www.sealab.gr
INTRODUCTIONINTRODUCTION(1/(1/22))
• Almost two billion people have no direct access to electrical networks, 500,000 of them living in European Union and more than one tenth of them in Greece.
• An autonomous wind-diesel system is one of the most interesting and environmental friendly technological solutions for the electrification of remote consumers or even entire rural areas.
• The primary objective of this current study is to determine the optimum dimensions of an appropriate stand alone wind-diesel system, able to cover the energy demand of remote consumers, using long-term measurements, under the restriction of minimum life-cycle cost.
• In most previously published works the system configuration selection was based on a minimum first installation cost analysis only.
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
INTRODUCTIONINTRODUCTION((22//22))
• For this purpose an integrated cost-benefit model is developed from first principles, able to estimate the financial behaviour of similar applications on a long-term operational schedule.
• In the proposed algorithm, besides the first installation cost, one takes into account the fixed and variable M&O cost, including fuel escalation and local market inflation rate.
• Using the proposed analysis one may prove that wind-based stand-alone systems, including a properly sized battery, lead to significant reduction of the fuel consumption in comparison with a diesel-only installation, also protecting the diesel generator from increased wear.
• Special emphasis is put on investigating the impact of the operational (service) period of the installation on the corresponding energy production cost.
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
PROPOSED SOLUTIONPROPOSED SOLUTION((11//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
During the system operation, the following energy production scenarios exist:
Energy (AC current) is produced by the micro wind converter and sent directly to the consumption
Energy is produced (AC current) by the small diesel-electric generator and is forwarded to the consumption
The energy output of the wind turbine (not absorbed by the consumption-energy surplus) is stored at the batteries via the charge controller
The battery is used to cover the energy deficit via the DC/AC inverter
PROPOSED SOLUTIONPROPOSED SOLUTION((22//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
This system should be capable of facing a remote consumer’s electricity demand (e.g. a four to six member family), with rational long-term operational cost.
The specific remote consumer investigated is basically a rural household profile (not an average load taken from typical users).
The annual peak load does not exceed 3.5kW, while the annual energy consumption is around 4750kWh.
Typical Electricity Demand Profile
0
500
1000
1500
2000
2500
3000
3500
4000
0 20 40 60 80 100 120 140 160
Time (hours)
Load
Dem
and
(Wh)
Winter ConsumptionSummer Consumption
PROPOSED SOLUTIONPROPOSED SOLUTION((33//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
START
No=Nin
t=0
Meteorological Data, i.e. Wind Speed, Ambient Temperature
Remote Consumer Energy Demand, ND(t)
Wind Turbine Power Curve Nw=Nw(t)
Nw>ND Nw=0
ΔN=Nw-ND
ΔN= ND-Nw
Battery Empty?
Battery Empty?
ND is covered by Battery via Charge
Controller and Inverter
ΔN is covered by Battery via Charge
Controller and Inverter
Battery Full?
Energy is Stored to the Battery via
Rectifier/Charge Controller
t >Δt
Q*=Q
No
Nin, Qin, Mfin, δN, δQ, δMf, Δt, δt, NFIN, QFIN, MfFIN
END
Mf =Mf +δMf
Q=Q+δQ
t=t+δt
Via UPS Nw
ND
YES
YES
YES
NO
YES
NO
NO
YES
NOYES
NO
Energy Storage
YES
To Low Priority Loads
NO
WIND-DIESEL I Algorithm
(No-Q*) curve
NO
=
Q=Q
No=No+δN
fM M
fM
FINfM
in
Q
inf
FINQ
FINN
YES
NO
NO
YES
The governing parameters that should be defined are:
the rated power of the wind turbine
the battery maximum capacity
the annual diesel-oil consumption
The new numerical code is used to carry out the necessary parametrical analysis on an hourly energy production-demand basis, targeting to estimate the wind turbine’s rated power and the battery capacity, given the annual permitted oil consumption.
Emphasis is laid on obtainingzero-load rejection operation
PROPOSED SOLUTIONPROPOSED SOLUTION((44//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
Given the "Mf" value and for each "No" and "Qmax" pair, the "WIND-DIESEL I" algorithm is executed for all the time-period selected (e.g. one month or even three years).
The appropriate (Mf, No, Qmax) combinations guarantees the stand-alone system energy autonomy.
SKIROS ISLAND (24Volt, DOD=70%, DOD1=40%)
0
5000
10000
15000
20000
25000
0 2000 4000 6000 8000 10000 12000 14000 16000
Wind Power (Watt)
Ba
tte
ry C
ap
acity
(A
h)
mf=0
mf=25
mf=100
mf=250
mf=500
mf=1000
ICo=20000Euro
ICo=30000Euro
ICo=40000Euro
PROPOSED SOLUTIONPROPOSED SOLUTION((55//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
LIFE CYCLE COST MODELLIFE CYCLE COST MODEL((11//44))
The present value of the entire investment cost of a stand-alone wind-diesel power system during its life cycle is a combination of the
initial installation cost and the corresponding maintenance and operation cost.
First Installation Cost
The initial investment cost includes the market (ex-works) price of the installation components (i.e. wind turbine, battery, diesel generator and electronic devices, including inverter, UPS, rectifier and charge controller cost) and the corresponding balance of the plant cost.
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J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
Fixed Maintenance and Operation Cost
In the present analysis, the fixed M&O cost also considers the fuel cost consumed by the diesel-electric generator.
The annual fixed M&O cost "FCWT“ can be expressed as a fraction "m" of the initial capital invested, furthermore including an annual inflation rate "gm"
The fuel consumption cost "FCD" results by the annual diesel-oil quantity consumed "Mf", the current fuel price "co" and the oil price escalation rate "e"
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12
12
LIFE CYCLE COST MODELLIFE CYCLE COST MODEL((22//44))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
Variable maintenance and operation cost
It depends on the replacement of "ko" major parts of the installation, which have a shorter lifetime "nk" than the complete installation. In the present analysis one takes into account the diesel-electric generator and the battery bank replacement.
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bd
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bbddd
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bdd
bd
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while "hd" and "hb" describe the purchase cost mean annual change combined with the corresponding technological improvement rate
LIFE CYCLE COST MODELLIFE CYCLE COST MODEL((33//44))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
Life Cycle Energy Production Cost
The energy production cost is given by dividing the present value of the installation total cost with the corresponding electricity production.
The energy production cost of the installation strongly depends on the service period "n" of the installation, i.e.:
The current electricity production cost "ce", after n-years of operation:
The proposed model includes the diesel-only solution (i.e. ICo=φ.Nd, No=0, rb=0, Mf=Mmax) as well as the zero-diesel configuration (i.e. ICd=0, rd=0, Mf=0)
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LIFE CYCLE COST MODELLIFE CYCLE COST MODEL((44//44))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
ANALYSIS OF THE PARAMETERS ANALYSIS OF THE PARAMETERS INVOLVEDINVOLVED
The main parameters involved in the electricity production cost procedure are:
The local market capital cost (x,y,z)
The M&O inflation rate (x)
The oil price annual escalation rate (y)
The electricity price annual escalation rate (z)
MAIN ECONOMIC PARAMETERS IMPACT ON THE ELECTRICITY COST (High Capital Cost Case)
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
Years
f w
w=2%, i=8%
w=5%, i=8%
w=8%, i=8%
w=11%, i=8%
MAIN ECONOMIC PARAMETERS IMPACT ON THE ELECTRICITY COST (Low Capital Cost Case)
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
Years
f w
w=2%, i=4%
w=5%, i=4%
w=8%, i=4%
w=11%, i=4%
fooo
e
McICmnnn
ICnc )()()(1)(
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
APPLICATIONS RESULTSAPPLICATIONS RESULTS((11//55))
2.3V
3.5V
5.7V
3.5V
2.3V
h=30m
Naxos Athens
Aegean Sea
Kea
Andros
Skiros
The proposed analysis is being applied to typical remote consumers located in a small island of N. Aegean Sea.
The island of Skiros is a small island of NW Aegean Sea, belonging to the Sporades complex.
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
MONTHLY AVERAGED WIND SPEED VALUES IN SKIROS ISLAND
0
2
4
6
8
10
12
14
16
Janu
ary
Febru
ary
Mar
chApr
ilM
ayJu
ne July
Augus
t
Septe
mbe
r
Octobe
r
Novem
ber
Decem
ber
Month
Win
d S
pe
ed
(m
/s)
Mean Value
Mean Value+Standard Deviation
Mean Value-Standard Deviation
The island has a medium-strong wind potential, taking into consideration that the annual mean wind speed approaches the
6.8m/s at 10m height.
APPLICATIONS RESULTSAPPLICATIONS RESULTS((22//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
HYBRID STATION ELECTRICITY PRODUCTION COST VARIATION vs SYSTEM SERVICE PERIOD (Low Oil Contribution, Mf=100kg/year)
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
5
0 2000 4000 6000 8000 10000 12000 14000 16000
WIND TURBINE RATED POWER
EN
ER
GY
CO
ST
(E
uro/
kWh)
5-Year Operation
10-Year Operation
15-Year Operation
20-Year Operation
HYBRID STATION ELECTRICITY PRODUCTION COST VARIATION vs SYSTEM SERVICE PERIOD (High Oil Contribution, Mf=500kg/year)
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
1,8
0 2000 4000 6000 8000 10000 12000 14000 16000
WIND TURBINE RATED POWER
EN
ER
GY
CO
ST
(E
uro
/kW
h)
5-Year Operation10-Year Operation
15-Year Operation20-Year Operation
For a low (Mf=100kg/y) and a high (Mf=500kg/y) annual diesel oil contribution cases, one may observe that there is a remarkable electricity cost decrease with the increase of the installation service period.
APPLICATIONS RESULTSAPPLICATIONS RESULTS((33//55))
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
APPLICATIONS RESULTSAPPLICATIONS RESULTS((44//55))
ELECTRICITY PRODUCTION COST vs ANNUAL DIESEL-OIL CONSUMPTION FOR 5, 10, 15 & 20 YEARS OPERATION
(SKIROS ISLAND)
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
1,8
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Annual Fuel Consumption (kg/year)
Ele
ctric
ity C
ost
(Eur
o/kW
h)
10-Year Operation 15-Year Operation5-Year Operation 20-Year Operation
For zero (wind only) or low diesel-oil contribution cases there is a considerable cost decrease between (5) and (10) years and between (15) and (20) years
The cost decrease between (10) and (15) years is quite small, due to the increase of the variable M&O cost contribution
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
IMPACT OF THE HYBRID STATION SERVICE PERIOD ON THE MINIMUM ENERGY COST (Optimum Configuration)
0,6
0,62
0,64
0,66
0,68
0,7
0,72
5 10 15 20
Years
Ele
ctric
ity C
ost
(Eur
o/kW
h)
IMPACT OF THE HYBRID STATION SERVICE PERIOD ON THE OIL CONSUMPTION (Optimum Configuration)
800
900
1000
1100
1200
0 5 10 15 20
Years
Ann
ual O
il C
onsu
mpt
ion
(kg/
year
)
In all cases examined, the optimum life cycle electricity production cost of the wind-diesel system investigated is slightly above 0.6€/kWh
APPLICATIONS RESULTSAPPLICATIONS RESULTS((55//55))
The minimum electricity production cost is remarkably decreased between the 5th and the 10th year of operation of the system, being accordingly almost constant
There is a significant optimum annual oil consumption decrease (≈300kg/yr) when the service period of the hybrid station increases from 5 to 20 years
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
CONCLUSIONSCONCLUSIONS(1/(1/22))
An integrated cost-benefit model is developed from first principles, able to estimate the financial behaviour of an energy autonomous hybrid wind-diesel-battery system on a long-term operational schedule.
For this purpose one should first define the optimum dimensions of the proposed system, able to cover the energy demand of remote consumers, under the restriction of minimum life-cycle cost.
The main parameters to be predicted are the wind turbine rated power, the corresponding battery capacity and the annual oil consumption required in order to guarantee energy autonomy of the entire stand-alone installation.
Accordingly, a total electricity production cost calculation model is developed, taking explicitly into consideration the desired service period of the complete installation.
J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)
CONCLUSIONSCONCLUSIONS((22//22))
Finally, the application of the complete analysis on a selected typical island region indicates that the proposed hybrid system is a reliable and a cost effective solution for the electrification of numerous isolated consumers.
According to the results obtained, one should point out the remarkable diesel-oil consumption decrease as the desired service period of the hybrid station increases, in order to minimize the corresponding life cycle electricity production cost.
In any case, the estimated long-term electricity production cost of the proposed hybrid system is considerably lower than the current operational cost of several existing small autonomous thermal power stations throughout Aegean Archipelago.
Recapitulating,one may definitely state that a properly sized stand-alone wind-diesel system is a motivating prospect for the energy demand problems of
numerous existing isolated consumers all around Europe. J.K. Kaldellis, K.A. Kavadias (Lab of Soft Energy Applications & Environmental Protection)