Economic AsseTurbines and So

Abstract— The paper illustrates economica

grid-connected onshore micro wind turbinesbased on onshore wind speed hourly minimheight in Latvia approximated according totower height. Economical assessment of the gcells is studied based on the real solar cells outResults of performed study show that the uyears for power generation in Latvia is profita

Keywords: power generation economics, w

cells

I. INTRODUCTION In order to preserve the climate bala

carbon dioxide (CO2) emissions per capita 3.8 tons per year. Carbon dioxide emcurrently exceed this specified threshold, reCO2 per capita per year. [1] One of the wemissions is increasing the use of enercreates the least amount of CO2 emissionssun.

Total wind energy potential in Latvia 1.5TWh (at present installed power capac[2,3,4] Therefore, making economical aonshore micro wind turbine for power geneworthwhile.

Average hourly wind speed in Liepaja height shown in Fig.1.

Fig.1. Average hourly wind speed in Liepaja (Latvia) 1 The stochastic fluctuations in the wi

power may have large amplitude at the ver

essment of Onshore Miolar Cells for Power Ge

Latvia Ilze Priedite

Institute of Physical Energetics Aizkraukles 21, Riga, Latvia prieditei@inbox.lv

al assessment of the s. The calculation is mum value of 4 m each wind turbine

grid-connected solar tput data of Latvia.

use of solar cells 25 able.

wind turbines, solar

ance in the world, should not exceed

missions in Latvia eaching 4.1 tons of

ways to reduce CO2 rgy resources that s, such as wind or

is estimated up to city is 0.112TWh). assessment of the eration in Latvia is

(Latvia) 10 meter

10 meter height [5]

ind turbine output ry short-term scale

(at the minute or intra-minugeneration of wind turbines cha10m.s-1 wind speeds. Averagechange in Liepaja (Latvia) 10 m

Fig.2. Average hourly wind speed semeter height [5]

Therefore, calculated outpudependent on what wind speedintra-minute scale.

Potential of solar energy in LTAB

POTENTIAL OF SOLAR

Average annual amount of radiation, hours

Number of cloudy days Number of average annual

sunny days

Average annual amount ofdays and number of average annbetween Baltic Sea area, Riga d

Energy generation from 1kyear 2013, shown in Fig.3.

icro Wind eneration in

ute scale) due to electricity anges markedly between 6 and e hourly wind speed seasonal meter height shown in Fig.2.

asonal change in Liepaja (Latvia) 10

ut power accuracy is highly d data is used- hour, minute or

Latvia is shown in Table I [6]. LE I

R ENERGY IN LATVIA

Baltic Sea area

Riga district (Latvia)

North East

Latvia

1900 1800 1700

100 90 110

< 30 >30 30

f radiation, number of cloudy nual sunny days varies slightly

district and North East Latvia. W solar cell in Riga (Latvia),

ENERGYCON 2014 • May 13-16, 2014 • Dubrovnik, Croatia

978-1-4799-2449-3/14/$31.00 ©2014 IEEE 380

Fig.3. Energy generation of 1kW solar cell in Riga (La Approximately 66% of the annual ele

with solar cells is produced between Aprthere are five months with high productivilow productivity in Latvia.

II. METHOD FOR ECONOMIC ASSESSMENMICRO WIND TURBINE

A case study was carried for 3 types wrated power 1kW, 3kW and 5kW. The studcommercially available wind turbines.

More detailed technical specificationturbines shown in Table II [7].

TABLE III TECHNICAL SPECIFICATION OF WIND TU

1kW Tower height, m 8

Cut-in wind speed, m/s 2,5 Operating wind speed, m/s 2.5-40

Lifetime, years 10 Installed capital cost, EUR 3927.06 7Annual operating expenses,

EUR/year 500

Power curves for these wind generators show

Fig.4. Power curves for 3 types wind turbine with ratkW [7]

Wind speeds map of Latvia shown in was carried out for a five cities- Liepaja, PAinazi and Rezekne using hourly wind spee

atvia), year 2013 [13]

ectricity generated ril to August, i.e., ty and seven- with

NT OF ONSHORE ES wind turbines with dy is conducted for

n of these wind

URBINES

3kW 5kW 9 12 3 3

3.5-40 3.5-40 10 10

7071.26 11891.8

500 500

wn in Fig.4

ed power 1kW, 3kW, 5

Fig.5. Case study avilosta, Mersrags,

ed data [5]

Fig.5. Average yearly wind speed in Lcarried out for circled cities) [8]

In order to estimate the winthe relationship would be rearra

⋅= 0VVh

where Vh- wind speed atV0- wind speed ath0- reference heig

=0.16-0.24 empivaries dependentatmosphere [9].

Since the year 2011 there arLatvia. “Start” tariff, i.e., 0.116user’s consumption from 0 to 1months from the 1st April un“Base” tariff, i.e., 0.1515 EURconsumption starting from 120months from the 1st April until

NET billing system for elLatvia implemented in accordanLaw and it is in force from Jsystem means subtracting eleccustomer’s site during the billinsupplied into the customer’s sitecalculating a net charge or credresulting net usage of electric en

If, in accordance with calconsumption and the electricityhousehold has transferred to thenetwork more electricity than amount of electricity is countperiod within the framework obilling system settlement perihousehold whole year produconsumes, the difference betgenerated electricity is transferoperator's network without rece

Latvia 10 meter height (case study was

nd speed at a certain height h, anged to:

α

0hh

(1)

t a certain height h, m/s; t a reference height h0, m/s; ght, m; irically derived coefficient that t upon the stability of the

re two tariffs for households in 64EUR/kWh is applicable to a 1200 kWh over a period of 12

ntil the 31st March next year. R/kWh is applicable to a user’s 01st kWh over a period of 12 the 31st March next year. [10] lectricity micro generation in nce with the Electricity Market January 1, 2014. NET billing ctric energy supplied out of a ng period from electric energy e during the billing period, and

dit to the customer based on the nergy during the billing period. lculated amount of electricity

y generated by micro generator, e distribution system operator's consumed, the corresponding

ed within the next settlement of the one calendar year. NET iod is one calendar month. If uces more electricity than it tween consumption and the rred to the distribution system iving compensation. [11]

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Annual expenditure on electricity produced by onshore micro wind turbines in Latvia can be calculated using algorithm (see. Fig.6.)

Fig.6. Algorithm for annual expenditure on electricity produced by

onshore micro wind turbines or solar cells Brackets used in the algorithm`s diagram correspond to

equation numeration. In case when annual energy consumption is lower than

annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells), annual expenditure on electricity can be calculated using (2).

PCMWAE Ge ⋅= (2) where

MWG- annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells), kWh; PC- prime cost (the same value for all lifetime period), EUR.

In case when annual energy consumption is higher than annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells) but at the same time lower than sum of annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells) and 1200kWh, annual expenditure on electricity can be calculated using (3).

SGCGe TMWMWPCMWAE ⋅−+⋅= )( (3)

where MWC- annual energy consumption, kWh; TS - “Start” tariff, EUR.

In case when annual energy consumption is higher than annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells) and at the same time higher than sum of annual energy generation by wind turbine (or by another renewable energy source, i.e., solar cells) and 1200kWh, annual expenditure on electricity can be calculated using (4).

SBGC

Ge

TTMWMWPCMWAE

⋅+⋅−−++⋅=

1200)1200( (4)

where TB - “Base” tariff, EUR.

III. METHOD FOR ECONOMIC ASSESSMENT OF SOLAR CELLS Global irradiation for optimally-inclined photovoltaic

modules in Latvia is shown in Fig.7. Case study was carried out for Riga.

Fig.7. Global irradiation for optimally-inclined photovoltaic modules in Latvia [12]

A case study was carried for 3 solar cells with rated power

1kW, 3kW and 5kW. The solar-cell system consists of CNPV 205W monocrystalline panels, SMA inverter network Sunnyboys1200 and monitoring system (SMA Webbox and SMA Sensorbox) connected to the internet.

Panels have south-facing orientation on a slanted roof (150

roof angle). The system is connected to the power grid. In moments, when solar energy is insufficient, additional energy is purchased from power grid.

Technical specification of solar cells is shown in Table III [13].

TABLE IIII TECHNICAL SPECIFICATION OF SOLAR CELLS

1kW 3kW 5kW Total area, m2 6.7 20.2 33.6 Lifetime, years 10-25 10-25 10-25

Installed capital cost, EUR 2000 6000 10000 Information of produced electricity amount in Riga with

such solar cells is available in [13]. In calculation is taken into account that CNPV 205W

monocrystalline panels have 25 year 80% output warranty period [14], i.e., annual energy generation by solar cells was calculated using a linear equation of aging (5).

83.1008333.0 +−= xy (5) where

y- level of aging, %; x - year of operation.

The prime cost of electricity was calculated for two cases- solar cell is used 10 years (workmanship warranty period) and solar cell is used 25 years (80% output warranty period).

Annual expenditure on electricity produced by solar cells in Latvia can be calculated using algorithm (see. Fig.5.)

ENERGYCON 2014 • May 13-16, 2014 • Dubrovnik, Croatia

978-1-4799-2449-3/14/$31.00 ©2014 IEEE 382

IV. RESULTS AND DISCUSSIO

Breakdown of households by annual avof electricity in Latvia is shown in Fig.8. Itenergy consumption from year 1996 to ymore than 50% of household electricity coexceeds 1000 kWh per year, but in 2010 household electricity consumption exceeds

Fig.8. Breakdown of households by annual avelectricity in Latvia (%) [15]

Annual expenditure on electricity d

household type by annual average consumis shown in Fig.9. In 2010 more than 5expenditure on electricity exceeds 200.28EU

Fig.9. Annual expenditure on electricity dependingby annual average consumption of electricity in year 20

Increase in annual expenditure on electr

wind turbines for all five cities- Liepaja, PAinazi and Rezekne are so similar that treflected one figure.

Increase in annual expenditure on electrthe household type by annual averageelectricity (due to using 1kW wind turbineIncrease in annual expenditure on electrhouseholds with lower electricity consumptthat a household with lower electricity proportionately higher part of electricity prmicro wind turbine. The prime cost of electonshore micro wind turbine is more thanthan electricity tariff.

ON erage consumption t shows increase in

year 2010. In 1996 onsumption do not more than 50% of 1600kWh per year.

verage consumption of

depending on the mption of electricity

50% of household UR per year.

g on the household type 010

ricity due to using avilosta, Mersrags, the results can be

ricity depending on e consumption of e) shown in Fig.10. ricity more affect tion due to the fact

consumption has roduced by onshore tricity produced by

n 100 times higher

Fig.10. Increase in annual expendihousehold type by annual average con1kW wind turbine)

Increase in annual expenditu

the household type by annuelectricity (due to using 3kW wIncrease in annual expenditure owind turbine is higher than in twind turbine, due to the fact thhas higher investment cost but anot proportional to the amount o

Fig.11. Increase in annual expendi

household type by annual average con3kW wind turbine)

Increase in annual expenditu

the household type by annuelectricity (due to using 5kW wi

Fig.12. Increase in annual expendi

household type by annual average con5kW wind turbine)

All last three figures, i.e. Fig

electricity produced by onshore

iture on electricity depending on the nsumption of electricity (due to using

ure on electricity depending on ual average consumption of wind turbine) shown in Fig.11. on electricity due to using 3kW the case, when using the 1kW hat onshore 3kW wind turbine at the same time productivity is of the investment cost.

iture on electricity depending on the nsumption of electricity (due to using

ure on electricity depending on ual average consumption of ind turbine) shown in Fig.12.

iture on electricity depending on the nsumption of electricity (due to using

.10, Fig.11, Fig.12., shows that e micro wind turbines in Latvia

ENERGYCON 2014 • May 13-16, 2014 • Dubrovnik, Croatia

978-1-4799-2449-3/14/$31.00 ©2014 IEEE 383

is not beneficial. Increase in annual expendproduced by onshore micro wind turbines is

Increase in annual expenditure on electrthe household type by annual averageelectricity (due to using 1kW solar cell 1Fig.13. Increase in annual expenditure oaffect households with lower electricity codue to the fact that a household withconsumption has proportionately higher produced by solar cells. The prime cost of eby solar cells is more than two times high“Start” tariff.

Fig.13. Increase in annual expenditure on electrihousehold type by annual average consumption of e1kW solar cell 10 years)

Increase in annual expenditure on electr

the household type by annual averageelectricity (due to using 3kW solar cell 1Fig.14.

Increase in annual expenditure on electr3kW solar cell is lower than in case when ucell. This is due to the fact that 3kW solinvestment cost but at the same timproportional to the amount of the investmen

Fig.14. Increase in annual expenditure on electrihousehold type by annual average consumption of e3kW solar cell 10 years)

Increase in annual expenditure on electr

the household type by annual averageelectricity (due to using 5kW solar cell 1Fig.15. Fig.13, Fig.14 and Fig.15, showproduced by solar cells 10 years in Latvia

diture on electricity s more than 264%. ricity depending on e consumption of 0 years) shown in

on electricity more nsumption. This is

h lower electricity part of electricity

electricity produced her than electricity

icity depending on the

electricity (due to using

ricity depending on e consumption of 0 years) shown in

ricity due to using using the 1kW solar lar cell has higher

me productivity is nt cost.

icity depending on the

electricity (due to using

ricity depending on e consumption of 0 years) shown in

ws that electricity a is not beneficial.

Increase in annual expenditursolar cells 10 years is more than

Fig.15. Increase in annual expendihousehold type by annual average con5kW solar cell 10 years)

Increase in annual expenditu

the household type by annuelectricity (due to using 1kW Fig.16.

Fig.16. Increase in annual expendihousehold type by annual average con1kW solar cell 25 years)

Decrease in annual exp

households with annual averafrom <0.4 to 0.8 MWh is at the electricity (~0.8MWh) is generacost (0.09876 EUR) is lower tha

Decrease in annual exphouseholds with annual averafrom 0.9 to 1.19 MWh is sma(~0.8MWh) of electricity is genof the electricity is purchashouseholds with annual averafrom 1.2 to 1.99 MWh decreelectricity is more rapid becauby network increases due to tannual expenditure on electriciaverage consumption of electsmaller due to fact that only pagenerated by solar cell but the rsed from the network for “Start”

Increase in annual expendituthe household type by annu

re on electricity produced by n 20.42%.

iture on electricity depending on the nsumption of electricity (due to using

ure on electricity depending on ual average consumption of solar cell 25 years) shown in

iture on electricity depending on the nsumption of electricity (due to using

enditure on electricity for ge consumption of electricity same level due the fact that all

ated by solar cell and its prime an “Start” tariff. enditure on electricity for ge consumption of electricity

aller due to fact that only part nerated by solar cell but the rest sed from the network. For ge consumption of electricity ase in annual expenditure on se the electricity price offered the “Base” tariff. Decrease in ity for households with annual tricity more than 2 MWh is art (~0.8MWh) of electricity is rest of the electricity is purcha ” and “Base” tariff. ure on electricity depending on ual average consumption of

ENERGYCON 2014 • May 13-16, 2014 • Dubrovnik, Croatia

978-1-4799-2449-3/14/$31.00 ©2014 IEEE 384

electricity (due to using 3kW solar cell 2Fig.17.

Fig.17. Increase in annual expenditure on electri

household type by annual average consumption of e3kW solar cell 25 years)

Decrease in annual expenditure on elect

3kW solar cell is higher than in case whsolar cell due to the fact that 3kW solainvestment cost but at the same timproportional to the amount of the invehouseholds with annual average consumpmore than 1.2 MWh decrease in annuaelectricity is more rapid because the electrby network increases due to the “Base” tarif

Increase in annual expenditure on electrthe household type by annual averageelectricity (due to using 5kW solar cell 2Fig.18.

Fig.18. Increase in annual expenditure on electrihousehold type by annual average consumption of e5kW solar cell 25 years)

Fig.16, Fig.17 and Fig.18, shows that e

by solar cells 25 years in Latvia is profiannual expenditure on electricity producedyears is not less than 10%.

V. CONCLUSIONS Results of performed study show that f

point of view onshore micro wind turbine5kW) for power generation in Latvia are ulow productivity and high initial cost ofoperations. Increase in annual expenditu

25 years) shown in

icity depending on the electricity (due to using

tricity due to using hen using the 1kW ar cell has higher

me productivity is estment cost. For ption of electricity al expenditure on ricity price offered ff. ricity depending on e consumption of 25 years) shown in

icity depending on the

electricity (due to using

lectricity produced itable. Decrease in d by solar cells 25

from the economic es (1kW, 3kW and unprofitable due to f construction and ure on electricity

produced by onshore micro winLess unprofitable is the use of generation in Latvia. In sucexpenditure on electricity produmore than 20.42%. Results oprofitable are the use of solgeneration in Latvia. In sucexpenditure on electricity produnot less than 10%.

It means that considering tofor reduction CO2 emissions is w

VI. ACKNOW

The paper is supported by the "Assessment of wind energenvironmental impact from w2014/0010/1DP/1.1.1.2.0/13/AP

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ENERGYCON 2014 • May 13-16, 2014 • Dubrovnik, Croatia

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