Multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process
Introduction
The operation of power plants for electricity production during the past decades provided the energy required for technological and economic development, which led to the rise of our living standard. Power plant operation has both positive and negative effects on employees as well as on local communities. Many new jobs were created and there was a socioeconomic improvement of the regions where power plants were located. Harmful effects such as the release of gases, radioactivity, soil and water contamination were ignored or undervalued, as economic aspects were given the first priority. Today, as figures of serious health problems relating to power plant operation rise, for both employees and the people living in the neighbourhood, we can no more ignore these negative aspects (Cragle et al., 1988; European Community (EESD Programme), 2005; Lipfert, 1980; López et al., 2005; McBride et al., 1978; Mokdad et al., 2004; National Council on Radiation Protection and Measurements (NCRP), 1987a; Pope et al., 2002; Shilnikova et al., 2003; Wang and Mauzerall, 2006). The necessity of power plant operation in our everyday life cannot be argued by anyone, but a balance should be definitely found so that electricity production no more harms public health and its negative effects are minimized.
In this study, 10 of the most important and widely applied types of power plants (coal/lignite, oil, natural gas turbine, natural gas combined cycle, nuclear, geothermal, biomass, photovoltaic, wind, and hydro) are evaluated against 14 criteria and subcriteria (quality of life, socioeconomic aspects, accident fatalities, non-radioactive emissions, radioactivity, land requirement, job creation, compensation rates, social acceptance, non-methane volatile organic compounds (NMVOCs), carbon dioxide equivalent (CO2-eq), nitrogen oxides (NOx), sulphur dioxide (SO2), and particulates or particulate matter (PM)) appropriately grouped under a hierarchy structure. These criteria represent positive and negative factors that affect the people's living standard, thus playing an important role in their everyday life.
Several studies have been carried out on power plant evaluation, electricity production and energy planning. Some of them focus on particular types of power plants like those based on renewable energy resources (Georgopoulou et al., 1997), some others use outranking methods like ELECTRE (Beccali et al., 2003; Buchanan and Vanderpootenb, 2007) and some others focus on economic (Diakoulaki and Karangelis, 2007; Kaldellis and Kavadias, 2007; Kaldellis et al., 2005), environmental (Beér, 2007; Meyer, 2002; Zhang et al., 2005) or technological aspects (Cook and Green, 2005) of power generation. Some studies incorporate the analytic hierarchy process (AHP) for energy conservation promotion (Kablan, 2004), natural resource and environmental management (Zhu and Dale, 2001), energy resource allocation (Ramanathan and Ganesh, 1995) and several other aspects of the energy sector (Elkarmi and Mustafa, 1993; Kim et al., 1999; Vaidya and Kumar, 2006). Nevertheless, no study exists to examine as a whole by use of the AHP the positive and negative impacts on the living standard of the most important and popular types of power plants available today, which are fossil fuel, nuclear and renewable-energy-based power plants.
The purpose of this study is to evaluate 10 types of power plants available at present, regarding their overall impact on the living standard of local communities. Both positive and negative impacts of power plant operation are considered. Positive criteria of power plant operation refer to socioeconomic aspects like jobs’ creation, compensation rates and social acceptance. Negative criteria refer to those factors affecting quality of life like non-radioactive emissions, radioactivity and land requirement or those factors causing the loss of lives like accident fatalities. This paper assumes that cost and technology aspects of power plants, although very important, do not affect directly the living standard of local communities but are primarily a matter of investors’ interest and should be examined in a separate study. In a deregulated market, consumers may buy electricity from different suppliers. Moreover, the money paid by an average consumer for electricity is a quite small percentage of his overall expenses, thus not affecting his living standard. Except for CO2-eq emissions, which have a global warming effect, thus considered of world concern, all other criteria involved affect directly only the local communities.
While it is very difficult to collect data for 10 types of power plants against 14 criteria that are valid for the whole world, effort has been made to use average values that are universally accepted (, 2005, , 2006; Hirschberg et al., 2004; International Atomic Energy Agency (IAEA), 2002; International Energy Agency (IEA), 2005, International Energy Agency (IEA), 2006; World Nuclear Association (WNA), 2006; World Wind Energy Association (WWEA), 2006). The criterion of social acceptance is subjectively evaluated based on preferences considered typical for many local communities in many developed countries rather than countries in the third world. Conclusively, this study evaluates power plants based on average data, the majority of which come from all over the world, although local variations can apply relative to the culture of communities, the power plant size and technology involved, as well as the way they are operated and maintained. The results presented here are illustrative only and user-defined weighting is required to make this study valuable for a specific group of users.
When evaluating a composite problem such as the one mentioned above, one has to make trade-offs between the several criteria involved in the assessment of the overall situation. Multicriteria analysis should be applied in order to solve problems of this kind. The AHP is a methodology that supports compensatory multicriteria decision making by aggregating alternatives’ performances against criteria to an overall indicator. Bad performances against one criterion can be compensated by good performances against other criteria. Moreover, AHP simplifies complicated problems by building a criteria and subcriteria hierarchy structure and by the use of a series of pairwise comparisons to evaluate alternatives’ performances against criteria as well as criteria weights (Liberatore and Nydick, 2003; Saaty, 1980, Saaty, 1990a, Saaty, 1990b). Pairwise comparisons prevent decision makers from rough and erroneous estimations by deriving ratio scale priorities, while it is not necessary to elicit utility functions. Other advantages of AHP are the consistency check of pairwise comparisons (Kwiesielewicz and Van Uden, 2004; Ozdemir, 2005), the 1–9 measurement scale, and the capability of using quantitative and qualitative criteria (Hung et al., 2006; Ramanathan and Ganesh, 1995; Wedley, 1990) as well as objective and subjective evaluations (Bantayan and Bishop, 1998; Chatzimouratidis and Pilavachi, 2007). These advantages have made AHP very popular as it is used in a wide range of applications (Bertolini et al., 2006; Karami, 2006; Park and Han, 2002; Ramanathan and Ganesh, 1995; Tiwari and Banerjee, 2001; Vaidya and Kumar, 2006; Wang et al., 2007; Wu et al., 2007; Zhu and Dale, 2001). Thus, AHP is considered to be the most appropriate multicriteria method to carry out the evaluation of this study.
Section snippets
Hierarchy tree
A top-down or bottom-up analysis is carried out for the construction of the hierarchy tree, depending on the available data and the in-depth knowledge available for the alternative options and the criteria. Then criteria weights and alternatives’ scoring against each criterion should be assessed. Evaluation of weighting and scoring can be either objective if true data exist or subjective by pairwise comparisons when no data exist.
The hierarchy tree is constructed with the goal at the top level
Quality of life
Quality of life comprises four subcriteria, which are accident fatalities, non-radioactive emissions, radioactivity and land requirement. These subcriteria are used to measure the negative effects of power plants on people's living standard. The lower the values of these criteria, the better the quality of people's life in the areas where the power plants are located.
Criteria weights
Apart from the alternatives’ scoring against each criterion, the criteria weights, which is the importance of each criterion and subcriterion, have to be specified before the overall evaluation is carried out. The importance of each criterion in each level is assessed with respect to their parent.
While objective data are difficult to alter, subjective assessments can vary among people with different culture, education and experiences. Subjectivity of preferences, among different decision
Analysis of the results
The AHP synthesizes the scores of the alternative options against the criteria presented in the hierarchy tree (see Fig. 1) and the criteria weights to give the overall evaluation of the 10 main types of power plants according to their impact on the living standard. This overall evaluation is presented in Fig. 4. This evaluation is illustrative only and a specific group of users can define their own weighting to make this study valuable for them.
Geothermal power plants with a score of 15.00%
Sensitivity analysis
Because of subjective evaluation criteria weights variations, a sensitivity analysis is required in order to examine the way criteria weight changes affect the overall score and ranking of the 10 types of power plants. Apart from the default case where quality of life had 75% weight while socioeconomic aspects had 25%, two other cases are examined. In the first alternative case, the two main criteria are considered of equal importance; that is, both quality of life and socioeconomic aspects
Conclusions
The evaluation of 10 types of power plant with regard to their impact on the living standard was carried out by application of the AHP. The evaluation of power plants depends on several criteria and weighting, which are specified by people's culture and experiences, resource availability, financial and social factors leading to the selection of the best choice according to each region's particularities. In this study, criteria weights were assessed subjectively based on preferences considered
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