The problem of windfarm location: A social multi-criteria evaluation framework
Introduction
In the last decade, renewable energies, and specially wind energy, have received a big impulse. Wind energy is presented as one of the strategies for tackling global warming and accomplishing the Kyoto Protocol. Although wind energy has the green image, it is not difficult to find unfavorable positions regarding the installation of windfarms. This opposition may depend on the extensive land use of windfarms, their possible impacts on tourism, the creation of territorial inequalities or their visual impact, as well as NIMBY (Never In My Back-Yard) behavior. The policy process itself for deciding the location of the wind turbines can also be a source of conflict. We can then conclude that wind energy location problems are essentially conflict management problems (Giampietro et al., 2006).
As a tool for conflict management, multi-criteria evaluation has demonstrated its usefulness in many environmental and energy policy/management problems (see e.g. Beinat and Nijkamp, 1998; Diakoulaki et al., 2005; Georgopoulou et al., 1998; Goumas and Lygerou, 2000; Munda, 2005a; Tzeng et al., 2005; Uemura et al., 2003). Most applications in the field of energy policy can be classified into the following main groups (Diakoulaki et al., 2005, pp. 876–879):
- 1.
comparative evaluation of power generation technologies,
- 2.
selection among alternative energy plans and policies,
- 3.
sorting out a subset of candidate energy projects,
- 4.
siting and dispatching decisions in the electricity sector.
As a consequence, the use of multi-criteria decision analysis seems very relevant for tackling wind parks location problems. Social multi-criteria evaluation (SMCE) (Munda, 2004), in particular, can supply a powerful framework for energy policy analysis since it is inter/multi-disciplinary (with respect to the research team), participatory (with respect to the local community) and transparent (since all criteria are presented in their original form without any transformations in money, energy or whatever common measurement rod).
The main principles of SMCE can be summarized as follows (Munda, 2004):
- 1.
The classical schematized relationship decision-maker/analyst is indeed embedded in a social framework, which is of a crucial importance in the case of public choice problems such as land use and energy policies.
- 2.
The combination of various participatory methods, which has proven powerful in sociological research, becomes even more so when integrated with a multi-criterion framework. For example, institutional analysis, performed mainly on historical, legislative and administrative documents, as well as on local press and interviews to key persons, can provide a map of the relevant social actors. By means of focus groups, it is possible to have an idea of people's desires and it is then possible to develop a set of policy options and evaluation criteria. Main limitations of the focus group technique are that they are not supposed to be a representative sample of the population and that sometimes people are not willing to participate or to state publicly what they really think (above all in small towns and villages). For this reason, anonymous questionnaires and personal interviews are an essential part of the participatory process (Corral Quintana, 2000; De Marchi et al., 2000; Guimarães-Pereira et al., 2003).
- 3.
Policy evaluation is not a one-shot activity. On the contrary, it takes place as a learning process which is usually highly dynamic, so that judgments regarding the political relevance of items, alternatives or impacts may present sudden changes, hence requiring a policy analysis to be flexible and adaptive in nature. This is the reason why evaluation processes should have a cyclic nature. By this, it is meant the possible adaptation of elements of the evaluation process due to continuous feedback loops among the various steps and consultations among the actors involved. It is extraordinarily important that different participatory and interaction tools are used in different stages throughout the process. This allows for a continuous testing of the assumptions made.
- 4.
Within this framework, mathematical algorithms still play an important role (i.e. to assure that the policy rankings obtained are consistent with the information and the assumptions used). For this reason, multi-criteria algorithms, used in a social context, should be as simple as possible (i.e. with a minimum number of exogenuous parameters) and that their axiomatization should be complete and clear.
Main objective of this article is to show the potentialities of a SMCE framework for dealing with wind park location problems. To achieve this goal a real-world problem is used. This is a location problem recently tackled in Catalonia (a region in the North-East of Spain).
Section snippets
The real-world location problem
The impact zone is located in the west part of the Catalonian central depression (see Fig. 1) between the “comarcas” of Urgell and Conca de Barberà. The projects proposed were two: the Coma Bertran project of 11 windmills of 1.5 MW and the Serra del Tallat project of 33 windmills of 1.5 MW. In addition, there were other two projects of 75 and 15 windmills, respectively.
Early in this location policy process, there were several positions regarding the construction of those windfarms. On one side,
Generation of alternatives
One of the main features of the SMCE framework is that alternatives are constructed considering information from several sources, for instance, the participatory process, the review of the projects, technical interviews, and so on. This process was carried out by the research group. It started considering the preliminary plans of the Coma Bertran (CB-Pre) and Serra del Tallat1
Selection of evaluation criteria
The evaluation criteria are a technical translation of social actors’ needs, preferences and desires operated by the research team. So, the evaluation criteria presented in Table 3 are aimed at representing the general objectives and interests of the identified social actors shown in Table 1. It is worth mentioning that the expected effects of the alternatives are not always foreseeable. There are many uncertainties in this kind of decision-making process, for instance the future wind
Computing criterion scores
This section deals with the criterion scoring process and the construction of the impact matrixes. This is done at the regional scale.
Ranking alternatives
Table 19 presents the multi-criteria impact matrix of the problem we are dealing with. In order to obtain a final ranking of the available alternatives, the criterion scores must be aggregated by means of a mathematical algorithm. Many multi-criteria models have been formulated since the 1960s, each one with advantages and disadvantages (see e.g. Arrow and Raynaud, 1986; Munda, 1995; Roy, 1996). Desirable properties for multi-criteria ranking procedure in the framework of public policy and
Enlightening distributional conflicts
One should note that criteria and criterion scores are not determined directly by social actors. The impact matrix is a result of a technical translation operationalized by the scientific team. Even if the criteria are exactly the ones agreed with the social actors, the determination of the criterion scores is independent of their preferences. For example, an interest group can accept the use of a criterion measuring the effects of the various alternatives on the employment, but the
Conclusion
A proper evaluation of wind park location options needs to deal with a plurality of legitimate values and interests existing in society. In empirical evaluations of public projects and public provided goods, multi-criteria decision analysis seems to be an adequate policy tool since it allows taking into account a wide range of assessment criteria (e.g. environmental impact, distributional equity, and so on) and not simply profit maximization, as a private economic agent would do.
One has to note
Acknowledgments
Thanks are due to all persons representing different social actors, for their kind collaboration in the field work. Assistance by Neus Marti and Eneko Garmendia is gratefully acknowledged. This research has been partly financed by the European Commission, research project: Development and Application of a Multi-Criteria Decision Analysis Software Tool for Renewable Energy Sources (MCDA_RES), Contract NNE5-2001-273. The usual disclaimer applies.
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