sequence determining of construction of the …

Ekonomika a management

50 2014, XVII, 3 DOI: 10.15240/tul/001/2014-3-005

Introduction

The world oil crisis of the seventies has lead toimportant changes regarding energy resourcesand their exploitation. In the nineties, there wasan increased focus on reducing the negativeeffects that the massive and uncontrolled useof the fossil fuels had on the environment. Thebeginning of the 21st century brought alongnew technologies in the green energy [29].

In recently have been recognized the valueof wind power as a major renewable energysource for long term; because wind is free,clean and renewable [27].

Wind power one is the most deserving of allcleaner energy production options from technical,environmental, socio-economical and socio-political standpoint (geothermal, solar, tidal,biomass, hydro) for more widespreaddeployment [20].

The wind energy is one of the most widelyexploited and rapidly evolved types ofrenewable energy [26].

The World Wind Energy Association (WWEA),claims that a capacity of the wind energyreaching a total value of 1900 GW is likelybefore the year 2020. China, USA, Germany,Spain, India and other countries, especiallyEastern Europe, as well as many Asiancountries and Latin America are expected todemonstrate a significant growth in this market[28].

Europe is the absolute leader in building theoffshore wind turbines. One of the key reasonsfor building the offshore wind turbines is a lackof territory, suitable for the onshore stations.

This situation is highly relevant in denselypopulated countries, such as Germany,Denmark, and Netherlands.

Report of The Wind Energy EuropeanAssociation, on the European level, generateda more detailed estimate for the year 2020 [21]:� 230 GW of installed capacity (190 GW

onshore, 40 GW offshore);� Annual investments of 23.5 billion EUR

(14.7 billion EUR onshore, 8.8 billion EURoffshore);

� Generation of 582 TWh of electric energy(433 TWh onshore, 148 TWh offshore);

� 14–17% of the entire EU energy requestshall be generated by the wind energyproduction;

� Reduction of CO2 emission by 333x106

tons annually.European Wind Energy Association

estimated that in 2030 the offshore windturbines will generate more energy comparedto the onshore wind turbines.

Lithuania, being a member of the EU,should execute its assumed obligations relatedto this field. It is anticipated that in 2020 thewind turbines may produce 10 percent of all theelectric power consumed in Lithuania. Thismeans that the country should establishfavorable conditions to build the wind turbineswith a total power of 500 MW [11].

Onshore wind energy technology is moremature than offshore, but nowadays, there isa considerable trend to the establishment ofoffshore wind farms [26]. Offshore wind poweras an upcoming technology and growingbusiness to deliver renewable energy with no

SEQUENCE DETERMINING OFCONSTRUCTION OF THE OFFSHORE WINDFARM CONSTRUCTION APPLYINGPERMUTATION METHODVygantas Bagoãius, Edmundas Kazimieras Zavadskas, Zenonas Turskis

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Business Administration and Management

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greenhouse gas emissions and withoutdepleting fossil energy resources has startlingperspectives for developers, authorities andsociety [2].

Wind energy is clean and inexpensive, butspace for the turbines is becoming scarce, whichmakes offshore wind an attractive choice.Therefore, offshore wind power has recentlybeen widely focused on and developed, as it isreliable, intensive, and its source is abundantand offers vast offshore areas. It can not onlyease reliance on oil and cut down emissions,but also stimulate the marine economydevelopment and offer job opportunities [10].

Offshore wind farms present higherinvestment, operational and maintenance cost,the significant offshore wind resource potential,the higher quality wind resources located atsea, the ability to use even larger wind turbinesdue to avoidance of certain land and the abilityof construction of even larger power plants thanonshore, as there is no geographical “limit”,form the primary motivations of developingoffshore wind energy [26].

Development of such farms is highlypromising for the distressed coastal regions,with the fishery businesses and shipbuildingcompanies closing down. In order to selecta suitable offshore territory for construction ofthe wind turbines, the entire marine area shouldbe mapped out in detail.

The offshore wind energy farms comparedto the onshore wind farms have advantages[13] as follows:� Wind is stronger and steady, thus energy

content is greater by 40%;� Invisible from the shore, thus no issues of

visual or noise-related disturbances;� Territorial restrictions may be avoided;� Greater power generation;� Better connection of electrical network;� Lower wind turbulence means lower

depreciation of installations and almostmaintenance-free operation.There exists main negative aspects for the

offshore wind turbines:� Higher project implementation costs;� More expensive substructure (groundwork);� Adverse weather conditions obstruct

construction works;� Limited industrial experience;� Higher requirements for corrosion resistant

materials, i.e. exposure to salt, water, and air;

Safety and effect issues on flora and faunaas well as natural habitats.

1. Selection Criteria for Wind FarmLocations

The offshore wind turbines opened newpossibilities for service and public utility servicesectors as well as a labor market. Problem ofselection construction for sites wind farms isboth economic, technical and managementproblem.

Good location’s selection leads to successof wind farms construction. There are three keyfactors influencing the location of wind farms asfollows: wind energy output, grid availabilityand construction conditions [15].

Having completed a thorough collection ofdata, entire information is processed in order toselect a potential and appropriate location forthe wind farms – a multiple criteria analysis isconducted.

The choice of energy generation is multi-criteria decision-making process made up ofa number of aspects at different levels [3].

In order to analyze potential locations forconstruction of the wind turbines, it isnecessary to gather and process the data,defining very detailed features and parametersof a specific location intended for construction.These data can be divided into two maincategories [14]:� Information on the restricted areas within

the region of interest;� Information on the relevant characteristics

in the region of interest.The first group is includes all the exceptions

that occur in the marine area being studied,either natural or human imposed, that restrictthe use of a particular region. These areas areused to define exclusion areas, and asa consequence are not used in the analysis[14]:� Harbour entrances and navigation routes;� Areas with environmental restrictions;� Oil and gas extraction;� Military exercise areas;� Underwater cables;� Sand and gravel extraction;� Marine archaeology sites;� Landscape and seascape as public

heritage.The second group determines all the

technical constraints that will allow evaluating

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the locations regarding its suitability for thedeployment of wind and wave energyconversion systems [14]:� Water depth;� Distance to shore;� Wind energy resource;� Investment costs;� Energy production capacity;� Realization time;� CO2 emissions avoided;� Acoustic noise;� Social acceptability;� Seabed Geology;� Safety;� Area of the territory;� Max power on the area;� Other.

2. Application of PermutationMethod for Multi-Criteria Analysis

To solve the problem was selected thepermutation method. The permutation methoduses Jaquet-Lagreze‘s feasible permutations ofall possible rankings and alternatives [6]. Whenapplying this method all permutations ofalternatives according to their preferability arechecked and compared among themselves [30].This method allows dealing with quantitativedata as well as with data expressed in words(lexicographic defined data) and enables usdefine the most appropriate ordering ofalternatives. The method was developed byPaelinck [16].

Suppose a number of alternatives(ai,i=1,2,...,m) have to be evaluated according toattributes (xj,j=1,2,...,n). Decision making matrixis a set up according to the form [24]:

(1)

For a solution of problems there exists anobligatory set of criteria weight coefficients wj:

(2)

The aim is to choose the most appropriatealternative from the m feasible alternatives.That is, one must assign the preferabilityrelationship on the set of alternatives, or what is

same, find the rearrangement of alternativeswhich fit best the system of values [30].

Let us assume there exists 3 feasible. Thenthere exist m! =3×2×1=6 permutations [30]:

In case of the checked order of alternativesis π2 there could to be stated concordancepartial order is: , andthe set of discordance partial order is:

.If in ranking (permutation) of alternatives

the partial ranking ak > al appears, it means thatxkj ≥ xlj will be rated wj and xkh ≤ xlh will be rated(–wh).

The ranking of alternatives βg(g =1,2,...,m!)is carried out as described above.

Let us suppose that there is gth permutation:where ak is pre-

ferable to al. Then to this permutation there isgiven following evaluation criterion βg:

(3)

where,

The best concordant ordering is the onewhich value βg is the largest.

The permutation method requires weightsof criteria. For this purpose there was selectedAHP (Analytic Hierarchy Process) method.AHP [19] is one of the most popular multi-criteria decision-making models. AHP involvesquantification based on comparative andrelative evaluation. It is one of the most widelyused methods to determine criteria weights. Allthe AHP calculations and evaluations werecarried out using a software, MakeltRational[7].

AHP method was suggested by Saaty [18]in 1980. Saaty established 9 objects as theupper limit of his integer scale for multiple pairwise comparisons [25]. Generally we canrepresent the comparative importance scale ofcriteria as shown in Table 1.

,

,

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The AHP method is based on the pair-wisecomparison matrix. Experts compare all theevaluation criteria:

(4)

(5)

Thus, when the matrix A is multiplied by thevector formed by each weighting w = (w1, w2,...,wn)T, one gets:

(6)

In the AHP the pair-wise comparisons ina judgment matrix are considered to beadequately consistent if the correspondingconsistency ratio (CR) is less than 10% [18].First the consistency index (CI) needs to beestimated. This is done by adding the columnsin the judgment matrix and multiply theresulting vector by the vector of priorities (i.e.the approximated eigenvector) obtained earlier.This yields an approximation of the maximumeigenvalue, denoted by λmax [23]:

(7)

By this method, one can obtain thecharacteristic vector, referred to as the priorityvector. Besides this Saaty suggested theconsistency index C.I = (λmax – n)/(n – l). Nextthe consistency ratio C.R is obtained bydividing the C.I value by the RandomConsistency index (R.I): C.R=C.I/R.I. R.I asvalues given in table 2.

Tab. 1: Comparative importance scale of critetia

Intensity of importance Definition

1 Criteria i and j have equal importance

3 Criterion i is moderately more important than criterion j

5 Criterion i is strongly more important than criterion j

7 Criterion i is very strongly or demonstrably more important than criterion j

9 Criterion i is extremely more important than criterion j

2, 4, 6, 8 Compromise values between the two adjacent judgments

Reciprocals If activity i has one of the nonzero numbers assigned to it when compared with activity j, nonzero then j has the reciprocal value when compared with i

Source: own

Tab. 2: RI values for different values of n

n 1 2 3 4 5 6 7 8 9 10 11 12

RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.48

Source: own

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3. Case studyWith the issues arising due to a limited use ofthe land, noise generated by the wind turbinesor other issues and seeking to use the entirewind potential of the Baltic Sea, an option of theoffshore wind farms is highly appreciated.

At present tame there is no built offshorewind farms in Lithuania. The internationalproject “Development Prospects of OffshoreWind Energy in Marine Areas of Lithuania,Poland and Russia (POWER)”, was identified

in 2008 the marine area and an exclusiveeconomic zone of Lithuania a potential regionfor construction of the wind farms [22].

It is stated that waters belonging to theRepublic of Lithuania may shelter five wind farms.The main objective of the task is to establisha sequence for the wind turbine construction,a total power of which would approximatelyreach up to 1065 MW. Fig.1 presentsa preliminary layout of the wind farms [5].

Fig. 1: Preliminary layout of the wind farms

Source: The model for economical feasibility study of offshore wind power parks [22]

The key criteria were selected for multi-criteria analysis:� x1 – area of the territory (km2) – Area

covered by the wind farms.� x2 – water depth (m) – The water depth at

the site is a very strong technical limitationand site evaluation. Within the technicallyadmissible range typically the shallower thewater depth the most suitable the location,as it usually means reduced constructioncosts [14].

� x3 – distance to shore (km) – The distanceto shore is measured in straight line, as it ismeant to evaluate the cost of the submarinecable that connects to land [14].

� x4 – average wind velocity (m/s) – Foroffshore wind systems this parameter isessential for the evaluation of the sites.Wind velocity is determined by performingannual wind parameters’ measurements(averaging of observation data of theclosest meteorological station) [12].

� x5 – max power on the area (103 MW) –The power plants park may be constructedvery widely or vice versa. Each separatewind power plant has an operation area itneeds. This way we may assess the powerplants on a certain area [1].

� x6 – amount of energy per year (MWh) –How much energy the wind power plantsfarm produces in fact [1].

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� x7 – investments (106 €) – Construction,electrical connection, grid connection,planning, wind turbines, approvals, utilitiesand management are the main componentsof capital cost for wind farm projects [9].

� x8 – CO2 (103 t) – this is one of the mostimportant criterion why a wind power plants

park is constructed. It is very important inconstruction of wind power plants. It differsin each country [1].The initial criteria for evaluation of

alternatives are given in Table 1 [17].

Tab. 3: Initial decision-making matrix

Optimum CriteriaAlternatives Weights

L1 L2 L3 L4 L5 wi

max x1 18 33 17 48 121 0.098

min x2 38 32 37 26 32 0.103

min x3 52 20 16,5 11,8 31 0.074

max x4 9.50 8.41 8.90 8.1 9.60 0.088

max x5 80 150 75 215 545 0.118

max x6 327.7 519.3 282.5 703.8 2262.2 0.211

min x7 290.4 348.5 192.6 457.3 1160.3 0.246

min x8 205.1 325.1 176.8 440.6 1416.1 0.062

Source: own

The criteria weights were determined by theAHP method based on the answers of 11experts. According to the data obtained fromthe interview in Table 3, one can construct thematrix A and further calculate the weight of

every criteria, the maximum eigenvalue (λmax),the consistency index (C.I) and the consistencyrate (C.R) as follows. An examples show forone expert:

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Based on 11 expert answers criteriaweights were determined as follows: w1=0.098,w2=0.103, w3=0.074, w4=0.088, w5=0.118,w6=0.211, w7=0.246, w8=0.062.

The establishment of preferences ofalternatives according to the set of quantitative

and qualitative criteria was performed using themethod of permutations [4], [8], [30], [31].

At five feasible alternatives of wind farmsthere can be 5! =5×4×3×2×1=120 permutations.The calculation process shortly is presented inTable 4.

Tab. 4: Feasible permutations and calculation process of evaluation criterion (part 1)

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The value β117=1.705 is the largest. Hence,the permutation should be regarded as themost rational and on its base a series of windturbine park alternatives according to theirpreferences should be constructed.

Conclusions

During the last past years, the wind energy hasbecome a widely used source of energyseeking to maximize a use of renewable energysources compared to fossil fuel or nuclearenergy. For this reason, the wind farms isa highly relevant issue, which should beanalyzed in-depth in order to prosper withtechnologically and economically effectiveproduction of the wind energy without harmingthe environment and wellbeing of the society.

Executing obligations to the EuropeanUnion Lithuania has been highly interested andfocused on renewable energy sources andwind energy in particular. Seeking a greaterand more effective use of the wind turbines, itwas determined that an option of building thewind farms in the Baltic Sea does really exist.Considering the experience of other countries,the offshore wind turbines feature a greatpotential.

The marine area, belonging to Lithuania,might potentially shelter five wind farms, a totalpower of which might approximately reach1065 MW.

Calculations were made in order toestimate the best sequence for the wind turbineconstruction related process. Having the keycriteria identified (investments, amount ofenergy per year, max power on the area, waterdepth, area of the territory, average windvelocity, distance to shore, CO2) and using thepermutation method, a construction sequencefor the wind farms in the Baltic Sea, close to thecostal lines of Lithuania, has been established– {L117}={L4 > L5 > L2 > L3 > L1}.

Having all of the possible wind farms builtover the years, Lithuania would not onlyexecute its obligations to the European Union,but would also contribute to building its energydiversification.

References[1] BAGOâIUS, V., ZAVADSKAS, E.K., TURSKIS, Z.Multi-person selection of the best wind turbine basedon multi-criteria integrated additive-multiplicativeutility function. Journal of civil engineering andmanagement. 2014, Vol. 20, Iss. 4, pp. 590-599.ISSN 1392-3730.


Source: own

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[2] BRETON, S.P., MOE, G. Status, plans andtechnologies for offshore wind turbines in Europeand North America. Renewable Energy. 2009, Vol.34, Iss. 3, pp. 646-654. ISSN 0960-1481.[3] CAVALLARO, F., CIRAOLO, L. A multicriteriaapproach to evaluate wind energy plants on anItalian island. Energy Policy. 2005, Vol. 33, Iss. 2,pp. 235-244. ISSN 0301-4215.[4] FIEDLER, K., PELDSCHUS, F., ZAVADSKAS,E.K. Methoden der bautechnologischen Enscheidung. Wiss. Berichte der Technischen HochschuleLeipzig. 1986, pp. 17-56.[5] GULBINSKAS, S. Wind energy developmentopportunities in the Baltic sea. In ConferenceWind Energy Development and Prospects. 2009,June 15, Vilnius.[6] HWANG, C.L., YOON, K.S. Multiple AttributeDecision Making. Methods and Applications.Berlin, Heidelberg, New York: Springer-Verlag,1981. 259 pp. ISBN 978-3-642-48318-9.[7] ISHIZAKA, A., NEMERY, P. Multi-criteriadecision analysis: methods and software. WestSussex: Wiley, 2013. 310 pp. ISBN 978-1-119-97407-9.[8] KILDIENE, S., ZAVADSKAS, E.K., TAMO·AI-TIENE, J. Complex assessment model foradvanced technology deployment. Journal of civilengineering and management. 2014, Vol. 20, Iss. 2,pp. 280-290. ISSN 1392-3730.[9] LEE, A.H.I., CHEN, H.H., KANG, H.Y. Multi-criteria decision making on strategic selection ofwind farms. Renewable Energy. 2009, Vol. 34, Iss. 1,pp. 120-126. ISSN 0960-1481.[10] LEUNG, D.Y.C., YANG, Y. Wind energydevelopment and its environmental impact:A review. Renewable and Sustainable EnergyReviews. 2012, Vol. 16, Iss. 1, pp. 1031-1039.ISSN 1364-0321.[11] Ministry of Energy of the Republic ofLithuania. National Energy Independence Strategyof the Republic of Lithuania. Vilnius, Nr. XI-2133,2012. ISBN 978-609-95429-0-4.[12] MARKEVIâIUS, A., KATINAS, V., MARâIU-KAITIS, M. Wind energy development policy andprospects in Lithuania. Energy Policy. 2007, Vol. 35,Iss. 10, pp. 4893-4901. ISSN 0301-4215.[13] MILLER, G.T., SPOOLMAN, S.E. Living in theenvironment. Principles, Connections, andSolutions. 16th ed. Cengage Learning, 2009. 828p. ISBN 978-0495556718.[14] MURPHY, J., LYNCH, K., SERRI, L.,AIRDOLDI, D., LOPES, M. Site Selection Analysisfor Offshore Combined Resource Projects in

Europe. In Results of the FP7 ORECCA ProjectWork Package 2. ORECCA, 28th October, 2011.117 p. Available also from: http://www.orecca.eu/c/document_library/get_file?uuid=1fff9401-0348-463e-8a6f-62dfd21bdfc8&groupId=10129.[15] OZERDEM, B., OZER, S., TOSUN, M.Feasibility study of wind farms: A case study forIzmir, Turkey. Journal of Wind Engineering andIndustrial Aerodynamics. 2006, Vol. 94, Iss. 10,pp. 725-743. ISSN 0167-6105.[16] PAELINCK, J. Qualitative multiple criteriaanalysis: on application to airport location.Netherlands economic institute: paper preparedfor second Tokyo environmental conference. 24 p.Rotterdam, August, 1976.[17] Project POWER [online]. Baltic offshoreenergy cluster, 2008 [cit. 2014-02-10]. Availablefrom: http://www.bosec.lt/eco/eco_lt.html.[18] SAATY, T.L. The Analytic Hierarchy Process:Planning, Priority Setting, Resource Allocation.Mcgraw-Hill. 1980. 287 p. ISBN 978-0070543713.[19] SAATY, T.L., VARGAS, L.G. Models,methods, concepts and applications of the analytichierarchy process. Berlin, Heidelberg, London:Springer, 2012. 353 p. ISBN 978-1-4614-3597-6.[20] TALINLI, I., TOPUZ, E., AYDIN, E., KABAKCI,S. [Chap.] 10, A Holistic Approach for Wind FarmSite Selection by Using FAHP. In SUVIRE, O.G.(ed.). Wind Farm – Technical Regulations,Potential Estimation and Siting Assessment. 2011.246 p. ISBN 978-953-307-483-2.[21] The European wind energy association[online]. Winds energy basics 2014 [cit. 2014-03-15]. Available from: www.ewea.org.[22] The model for economical feasibility study ofoffshore wind power parks. Perspectives ofOffshore Wind Energy development in marineareas of Lithuania, Poland and Russia, Lithuania.2008. 30 p.[23] TRIANTAPHYLLOU, E., MANN, S.H. Usingthe analytic hierarchy process for decision makingin engineering applications: some challenges.International Journal of Industrial Engineering:Applications and Practice. 1995, Vol. 2, Iss. 1, pp. 35-44. ISSN 1072-4761.[24] TURSKIS, Z. Multi-attribute contractorsranking method by applying ordering of feasiblealternatives of solutions in terms of preferabilitytechnique. Baltic Journal on Sustainability. 2008,Vol. 14, Iss. 2, pp. 224-239. ISSN 2029-4913.[25] TURSKIS, Z., ZAVADSKAS, E.K. A new fuzzyadditive ratio assessment method (ARAS-F).Case study: The analysis of fuzzy multiple criteria

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in order to select the logistic centers location.Transport. 2010, Vol. 25, Iss. 4, pp. 423-432. ISSN1648-4142.[26] VAGIONA, D.G., KARANIKOLAS, N.M.A multicriteria approach to evaluate offshore windfarms siting in Greece. Global NEST Journal. 2012,Vol. 14, Iss. 2, pp. 235-243. ISSN 1790-7632.[27] WELCH, J., VENKATESWARAN, A. The DualSustainability of Wind Energy. Renewable andSustainable Energy Reviews. 2009, Vol. 13, Iss. 5,pp. 1121-1126. ISSN 1364-0321.[28] WINDPOWER, DVORAK, P. World WindEnergy Assn sees 1,900 GW by 2020 [online].Windpower, Engineering and development, 2010-09-22 [cit. 2014-03-10]. Available from:http://www.windpowerengineering.com/policy/world-wind-energy-assn-sees-1900-gw-by-2020/.[29] ZAMFIROIU, C.E. Selection of the investmentprojects „Wind farms in Romania“ by using multi-criteria methods for sustainable development.2011. Available also from: http://www.dafi.ase.ro/revista/5/Zamfiroiu%20Carmen%20Elena.pdf.[30] ZAVADSKAS, E.K., PELDSCHUS, F.,KAKLAUSKAS, A. Multiple criteria evaluation ofprojects in construction. Vilnius: Technika, 1994.226 p. ISBN 9986050464.[31] ZAVADSKAS, E.K., TURSKIS, Z.,TAMOSAITIENE, J. Selection of constructionenterprises management strategy based on theSWOT and multi-criteria analysis. Archives of Civiland Mechanical Engineering. 2011, Vol. 11, Iss. 4,pp. 1063-1082. ISSN 1644-9665.

Vygantas BagoãiusVilnius Gediminas Technical University

Klaipeda UniversityFaculty of Civil Engineering

Department of Construction Technology andManagement

[email protected]

prof. Edmundas Kazimieras ZavadskasVilnius Gediminas Technical University

Faculty of Civil EngineeringDepartment of Construction Technology and

[email protected]

prof. Zenonas TurskisVilnius Gediminas Technical University

Faculty of Civil EngineeringDepartment of Construction Technology and

[email protected]

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Abstract

SEQUENCE DETERMINING OF CONSTRUCTION OF THE OFFSHORE WINDFARM CONSTRUCTION APPLYING PERMUTATION METHODVygantas Bagoãius, Edmundas Kazimieras Zavadskas, Zenonas Turskis

Ranking of work or feasible investments is one of high-importance keys for successful economicdevelopment. The share of renewable energy sources in the Lithuanian primary energy supply ison the lowest among EU. Only bio fuel, hydro and wind power can be considered as potentialrenewable energy sources in Lithuania at present time. Wind energy generation mature technologyand comparatively low cost make it promising as an important primary energy source in the nearestfuture.

The aim of this paper is to determine the sequence for the wind turbine construction in thewaters of Lithuania. The key criteria set for was determined for the problem solution: area of theterritory, water depth, distance to shore, average wind velocity, max power on the area, amount ofenergy per year, investments and CO2. AHP method is used to estimate criteria weights. Theproblem was solved applying multi-attribute permutation method. This method allows dealing withqualitative and quantitative as well as with linguistic (verbal) data.

Key Words: Offshore wind turbine, multi-criteria decision-making, permutation method, AHPmethod.

JEL Classification: G34, M12.

DOI: 10.15240/tul/001/2014-3-005

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sequence determining of construction of the …

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