A MULTI-CRITERIA APPROACH TO SITTING WIND FARMS IN LESVOS, GREECE. Eleni Eleftheriadou, Dias Haralambopoulos, Heracles Polatidis

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1 A MULTI-CRITERIA APPROACH TO SITTING WIND FARMS IN LESVOS, GREECE Eleni Eleftheriadou, Dias Haralambopoulos, Heracles Polatidis University of the Aegean, Department of Environmental Studies, Energy Management Laboratory Mytilene 800, Lesvos, Greece, Tel , Fax , Abstract The complexity of energy planning renders multi-criteria techniques a useful tool in the decision making process. In this paper a methodological framework to sitting renewable energy projects is presented. The multiple dimensions of Renewable Energy Sources (RES) entail the use of multi-criteria analysis due to different aspects (technological, economic, social, energy, environmental) that have to be taken into consideration, and the involvement of various Decision Makers (DMs) in the decision process. The development of such a framework encloses the formulation of alternative scenarios, the establishment of the evaluation criteria, the collection of data, the elicitation of DMs preferences, and the application of a multicriteria technique. The multi-criteria PROMETHEE II (Preference Ranking Organization METhod for Enrichment Evaluation) method has been used. The proposed methodology has been applied in a case study (Kratigos-Lesvos) for the further exploitation of the wind energy potential in the area. Photorealistic pictures of the area were presented to the DMs for the selection and the sitting of the wind farms during a workshop held in Lesvos, funded under the European Commission Fifth Framework Programme (FP5-EESD). Key words: multi-criteria analysis, decision support systems, stakeholder participation, renewable energy sources. Introduction Climate change and environmental awareness have made Renewable Energy Sources (RES) a competitive performer in the energy scenery. Legislative measures have been adopted in order to reduce dependency from imported fossil fuels and to further integrate non-polluting technologies in the electricity production. The European Union aims to raise RES contribution to primary energy consumption from 6% to % by 00 (COM (000) 79 final). Despite the abundance of mature and well-established renewable technologies, still there are barriers and obstacles that must be overcome for their diffusion. Contemporary energy planning is undertaken by energy utilities and governmental institutions whose foremost concerns are market costs and reliability, criteria that favor the use of conventional fuels. The development of RES seems to provide a promising alternative for a sustainable approach to energy utilization. There are, however, physical and technical barriers that limit their application to a regional-local scale, where the most advantageous sites must be identified in order to be fully and efficiently exploited (Sarafidis et al., 999). Furthermore, the local-decentralized character of RES imposes an uneven spatial distribution of their corresponding costs and benefits. In particular, RES entail costs for the local communities (landscape disturbance, noise creation, extensive land use) while the resulting environmental and other benefits are distributed over a wider scale through energy electricity networks (Polatidis et al., 00). Multi-criteria Decision Analysis (MCDA) has been successfully used in energy and environmental decision-making where alternative actions must be formulated, many data have to be accessed, appropriate criteria have to be selected, evaluation scores on the criteria must be obtained, and finally the active involvement of people mostly affected by the decision made is being encouraged (Siskos and Hubert, 98;. Huang et al., 995; Hokkanen and Salminen, 997; Georgopoulou et al., 997). In this paper, a multi-criteria decision support framework has been established and applied to determine appropriate ways for the further exploitation of a wind energy potential in an islandic area (Kratigos-Lesvos). Various Decision Makers (DMs) have participated in a workshop where real-case and imaginary actions were presented. Preferences between the criteria selected were obtained and scenario visualization techniques have been used for enhancing the transparency of the participation process. The PROMETHEE II (Preference Ranking Organization METhod for Enrichment Evaluation) (Brans et al., 986) method has been applied and the results obtained were presented to the DMs, in an iterative process, in order to promote mutual compromise and facilitate group decision-making.

2 . The area under study Lesvos island is located to the northeast of Greece, in the Aegean Sea. Its total area is 66 km, with almost inhabitants. Tourism is the main economic activity in the island (apart from agriculture) and its seasonal characteristic, coupled with hot summers, are the main culprits of the annual fluctuations in electricity demand. Electricity production is based on one autonomous conventional power station, owned by the Public Power Corporation (PPC) and placed in Mytilene. It is fired by crude and diesel oil. Wind potential in the island is high and PPC and other private and municipal investors have employed it for electricity generation. Other RES, geothermal and solar, have also been developed but on a limited scale. Table presents the installed electricity capacity in Lesvos in 00. Table. Installed electricity capacity in Lesvos in 00*. Conventional power station capacity [MW] Wind capacity [MW] Lesvos *source: Regulatory Authority for Energy ( Kratigos is a mountainous area beside the sea, located 0 Km south of Mytilene (Figure ). AIOLIKI S.A. (municipal development company) operates the existing wind park in the site, with total installed capacity of 0.75 MW. Mytilene Kratigos Figure. The area under study. The MCDA framework The main objective of this work is to investigate appropriate ways to further exploit the wind energy potential in the area and to sitting the additional wind mills. For this purpose, several possible wind projects scenarios have been formulated and evaluated according to different criteria by means of the PROMETHEE II method. Local, regional and national stakeholders have been invited to participate in the decision-making process to identify suitable sites for placing further wind turbines. Next paragraphs present the PROMETHEE II method, the alternative scenarios formulated, the evaluation criteria selected and the overall decision-making process.. The Promethee II method The proposed methodology is based on the outranking method PROMETHEE II. This technique has all the advantages of the outranking methods, combined with ease of use and decreased complexity. It performs pair-wise comparisons of alternatives in order to rank them according to a number of criteria. If V i (A) is the value of criterion i of alternative A, then the difference D i between alternatives A and B is calculated: D i (A,B) = V i (A) V i (B) () To render the differences in the evaluation between two alternatives meaningful, the PROMETHEE method utilizes two thresholds, which are considered constant and traditionally are DM-dependent. These thresholds are established as:

3 q i [V i (A)] threshold of indifference for criterion value V i of alternative A, p i [V i (A)] threshold of strict preference for criterion value V i of alternative A. The preference index, P i (A,B) [0,], describing the positive arguments of criterion i supporting the assumption that action A is at least as good as action B, is then defined for the case of linear preference: P i (A,B) = 0 when D i (A,B) q i [V i (B)] () P i (A,B) = when D i (A,B) p i [V i (B)] () P i (A,B) = (V i (A)-V i (B)-q i [V i (B)]) / (p i [V i (B)]-q i [V i (B)]) () when q i [V i (B)] < D i (A,B) < p i [V i (B)]. The DM assigns a set of weights, W=(W, W W n ) to the n criteria and an outranking degree over all criteria is calculated: Π( Α, Β) = WiP i (A, B) Wi (5) i i In PROMETHEE positive and negative flows, used for ranking the alternatives, are defined as: + Φ ( A ) = Π( A, B) /( n ), (6) B A Φ ( Α) = Π( Β, Α) /( n ), (7) B A The net flow Φ(Α) for each alternative, i.e. the difference between positive and negative flows, Φ(A) = Φ + (A)-Φ - (A), (8) expressed as: Φ( Α) = ( W i( Πi( Α, Β) Pi ( Β, Α)))/ Wi ( n ), (9) i B A i was used for the final complete ranking of all alternatives (PROMETHEE II). For simplicity reasons the indifference threshold was taken equal to zero in all cases, which tallies with the technical nature of energy projects (Haralambopoulos and Polatidis, 00).. formulation In this study for the formulation of alternative scenarios two set of actions where adopted: a) The first action represents realistic cases of wind energy development in the area. Under this action the maximum allowed wind electricity capacity to the current grid was assessed (in autonomous grids there is an upper limit allowing only 0% of the peak load). Four () alternatives were developed, starting from a mild utilization of the wind potential and gradually reaching an extensive exploitation scenario. b) The second action embodies four () imaginary alternative scenarios of wind energy development in the area. It is assumed that either there will be a cable connection with the national mainland grid or the current technical barriers will be overcome. It also consists of gradually developed alternatives, including offshore installation of wind parks, and electricity production not only for the current needs of the island but also for exporting the excess electricity produced. For each set of actions digital photos of the sites were taken from different angles, both in and outside the town of Mytilene. An appropriate software tool was used to represent the sites after installing the wind mills. The photorealistic pictures developed, enable a graphical display of the future state of the landscape in the area. Visualization planning tools allow participants to view photorealistic examples of proposed design prototypes that were seamlessly placed into photographic images of the neighborhood. This creates a common base for dialogue, and raises awareness in the environmental decision-making process (Al- Kodmany, 999). Moreover, they directly sketch alternative options and display slide images that are straightforward projected to the public. The latest progress in computers enables planners to use digital visualization techniques to effectively investigate how peoples perceptions interact to designed alternatives.

4 . Criteria selected The evaluation criteria should embrace all important economic, technological, environmental, resource and social dimensions of the decision problem. Criteria should not overlap each other or be reduplicated and should be kept on a small number if possible. Quantitative measurements (real values or proxy attributes) and qualitative assessments could be used for their evaluation. For the purpose of our case studies, five commonly used criteria were selected and assessed for both the real and the imaginary actions: a) TOE saved/yr; Represents the extent of the wind field exploitation, in Tones of Oil Equivalent per year, that are saved due to the substitution of fossil fuel by renewable energy. b) Return on investment; Expresses the fraction (%) of the annual profits of the investment to the invested capital. c) Jobs created; It is the number of permanent employment created from the operation of the new wind farms. d) Environmental impact criterion; It is a normalized impact index taking into account the number of Wind Turbines (W/T) installed, their total height and the area occupied by each scenario. e) Local income; It refers to a compensatory payment that has to be appointed to local municipalities (% of the total annual revenue). In Table and the decision matrix of each set of actions, with the scores of the assessment criteria and the alternative scenarios for the real and the imaginary actions are presented respectively. Description Table. The decision matrix of the real case action. Total CRITERIA capacity A B C D E Fuel saved Return on No of Jobs Environmental Local income investment created impact index No. of W/T x MW MW toe/yr yearly earnings/ min: 0 - max: 0 total investment x % x % x % x.+ x % Threshold values* % * Threshold values are calculated as (max-min)/n, e.g (9-8)/=6.5. Description Table. The decision matrix of the imaginary action. Total CRITERIA capacity A B C D E Fuel saved Return on No of Jobs Environmental Local income investment created impact index No. of W/T x MW MW toe/yr yearly earnings/ min: 0 - max: 0 total investment 5 x % x % x % x x % Threshold values* % * Threshold values are calculated as (max-min)/n, e.g (0-80)/=508.. Participation procedure Stakeholders consist of all different people associated with the planning and decision procedure, those who have a legitimate responsibility to participate and/or add a socio-political dimension to the process (Lahdelma et al., 000). The actual DMs are established from these groups and could embrace potentials

5 investors, local authorities, central government representatives, non-governmental organizations, farmers associations, local media, residents of the area, etc. However, there exists no well-defined process for deciding on the different parties who should have a voice in the decision process. They depend on the specific case study. Representatives of renewable energy projects participated in a virtual exercise during a workshop held in the Energy Management Laboratory, University of the Aegean in Mytilene, funded under the European Commission s Fifth Framework Programme (FP5-EESD). The whole process could be followed through the web site: The decision making group comprised of representatives of the following interested parties: Regional Authorities of the N. Aegean RES investors Central government-eu representative Non Governmental Organization (NGOs) - Media In the beginning of the workshop the Energy Management Laboratory scientists presented the PROMETHEE II method, the alternative scenarios, and the evaluation criteria to the participants. In addition, photorealistic pictures were shown to the DMs in order to obtain visual and graphical representations of the whole area after the installation of the wind turbines (Figures and ). Figure. Photorealistic picture of scenario No. of the real action. Figure 6. Photorealistic picture of scenario No. of the imaginary action. Next step included the elicitation of the DMs preferences between the criteria. In most multi-criteria methods a numerical value is assigned to each criterion expressing its relative importance. This reflects the corresponding criterion weight. The analysis of the weights and their interpretation completely depends on the selected decision model (Salminen et al., 998). After presenting the proposed MCDA framework to the workshop participants, weighting factors reflecting their preference between the criteria were directly 5

6 obtained. An -00 per cent point allocation scale for the weights upon the criteria was preferred according to the Direct Rating technique (Hajkowicz et al., 000). After the first extraction of criteria weights, and the initial presentation of results, a productive dialogue among participants made them to reconsider their preferences and to proceed to revising their initial weights to express even better their values. Table presents the final weights of the DMs, for the real case action. Decision makers Table. Decision-Makers weights for the real action. Criteria A B C D E Fuel saved Return on investment No of jobs Environmental impact index Local income Regional authorities of the N. Aegean 0 % 5 % 0 % 5 % 0 % RES investors 0 % 0 % 9 % 0 % % Central government-eu representative 5 % 0 % 0 % 0 % 5 % NGOs-Media % 5 % 0 % 8 % 5 % Similarly, the imaginary action was presented to the DMs along with the photorealistic pictures designed for those alternatives. Final weights were also obtained for the imaginary alternatives as shown in Table 5. Decision makers Table 5.Decision-Makers weights for the imaginary action. Criteria A B C D E Fuel saved Return on investment No of jobs Environmental impact index Local income Regional authorities of the N. Aegean 5 % 5 % 5 % 0 % 5 % RES investors 0 % 0 % 9 % 0 % % Central government-eu representative 5 % 0 % 0 % 0 % 5 % NGOs-Media 0 % 0 % 0 % 00 % 0 % The final step of the process included the application of the PROMETHEE II technique. For this purpose a computer model was developed in order to assist the DMs to directly introduce their weight factors and to immediately visualize their preference between alternatives. In Figures and 5 the alternative scenarios are graphically ranked according to DMs preference and the vertical distance between them corresponds to the overall difference in their performance. By those means, it is possible to identify where conflicts might occur and a common ground of agreement between conflicting groups of DMs could be revealed. 6

7 Regional authorities ranking RES investors ranking,00 0,0-0,0,00 0,0-0,0 Central government ranking NGOs - Media ranking,00 0,0-0,0,00 0,0-0,0 Figure. Graphical presentation of scenarios ranking for the real action. Regional authorities ranking RES investors ranking,00 0,0-0,0,00 0,0-0,0 Central government ranking NGO s - Media ranking,00 0,0-0,0,00 0,0-0,0 Figure 5. Graphical presentation of scenarios ranking for the imaginary action. Table 6 presents the final ranking of alternatives for the real action. Table 6. Ranking of alternatives for the real case action. Decision Makers Ranking of alternatives Regional authorities of the N. Aegean > > > RES investors > > > Central government-eu representative > > > NGOs-Media > > > 7

8 Similarly the ranking of alternative scenarios for the imaginary action is presented in Table 7. Table 7. Ranking of alternatives of the imaginary action. Decision makers Ranking of Alternatives Regional authorities of the N. Aegean > > > RES investors > > > Central government-eu representative > > = NGOs-Media > > > For the real case action all DMs apart from the investors preferred scenario No. (Table 6). However, and since the difference between scenario No. and No. in the investors ranking is minor (Figure ), they agreed to compromise with scenario No.. For the imaginary action, however, and as the number of wind turbines rises, the NGOs-Media preferred by far scenario No. (Figure 5), while all other DMs preferred scenario No.. At first it seemed that group consensus was difficult to be reached in this particular example. Nevertheless, one may suggest that in this case, scenario No. could be a possible compromise solution since it appears as the second best choice in the ranking of three out of four DMs (Table 7). If necessary the whole procedure could be implemented from the beginning, enhanced with new criteria, alternative scenarios and weights.. Conclusions In this paper an analytical methodology for the sitting of wind turbines in Kratigos-Lesvos has been established and applied. The framework is based on the multi-criteria PROMETHEE II method which proved to be an appropriate decision tool in capturing the multiple dimensions of RES projects. The decision making process was enhanced with visual representations of future wind energy scenarios by using appropriate designed photorealistic pictures that offer an innovative way for planning and facility sitting. The PROMETHEE framework coupled with visualization techniques increases the transparency of the procedure and offers the means for identifying and portraying the impact of local constrains on the available wind potential. The whole methodology has been presented to local, regional and national stakeholders during a workshop held in Lesvos regarding the extension of a wind park in the area of Kratigos. Two sets of alternative future actions were established corresponding to a real and an imaginary case. Participants felt comfortable using the proposed approach and even provided their explicit preference for the criteria used to evaluate the alternative scenarios. The developed methodology appears to be a user-friendly approach, promotes the synergy between different actors, and could pave a way towards group consensus. Acknowledgements This research has been financed by the European Commission, research project: Development and Application of a Multi-Criteria Decision Analysis Software Tool for Renewable Energy Sources, Acronym: MCDA-RES, Contract No: NNE5-00-7, References Al-Kodmany K., 999: Using visualization technique for enhancing public participation in planning and design: process, implementation and evaluation. Landscape and Urban Planning, 5, 7-5. Brans J. P., Ph. Vincke, B. Mareschal, 986: How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research,, 8-8. EU Commission, 000: Proposal for a directive on the promotion of electricity from renewable energy sources in the internal electricity market. COM (000) 79 final, Brussels, Belgium, May. Georgopoulou E., D. Lalas, L. Papagiannakis, 997: A Multicriteria Decision Aid approach for energy planning problems: the case of renewable energy options. European Journal of 0perational Research, 0, 8-5. Hajkowicz S. A., G. T. McDonald, P. N. Smith, 000: An Evaluation of Multiple Objective Decision Support Weighting Techniques in Natural Resource Management. Journal of Environmental Planning and Management,, Haralambopoulos D. A. and H. Polatidis, 00: Renewable energy projects: structuring a multi-criteria group decision-making framework. Renewable Energy, 8, Hokannen J. and P. Salminen, 997: Choosing a solid waste management system using multicriteria analysis. European Journal of 0perational Research, 98,

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