OPTIMUM SIZING OF A STAND-ALONE WIND-DIESEL SYSTEM ON THE BASIS OF LIFE CYCLE COST ANALYSIS

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.


PROPOSED SOLUTIONPROPOSED SOLUTION((11//55))


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



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



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



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



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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1maxox

oo NBNNQ)f1(Nc

Nb

aIC


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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fo

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m

n

mmmo

Dn

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12

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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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bbddd

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bd

d

while "hd" and "hb" describe the purchase cost mean annual change combined with the corresponding technological improvement rate



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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o

fon

on Y1y

1yy

IC

Mc

1x

1xxm)1(ICC

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nfz

n

nfz

nfyMc

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ICnc

z

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yfo

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x

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oe



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)(


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.


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.



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.




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


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


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


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.


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)

Documents

OPTIMUM SIZING OF A STAND-ALONE WIND-DIESEL SYSTEM ON THE BASIS OF LIFE CYCLE COST ANALYSIS