تجزیه و تحلیل حساسیت از ارزیابی تاثیر نیروگاه های برق بر استاندارد زندگی با استفاده از فرایند تحلیل سلسله مراتبی

Ten types of power plant were evaluated as to their impact on the living standard. Power plant evaluation incorporates a number of criteria that can be assessed either objectively or subjectively. Objective assessments are usually quantitative and are based on real data, while subjective assessments are rather qualitative and derive from decision makers’ intuition, culture and experience. Because of diversity of decision makers’ opinions, subjective assessments are due to vary. Several scenarios should therefore be examined in order to evaluate what happens under different assessments. Even objective assessments can vary because of data changes due to technology and socioeconomic evolution. This is why the application of a sensitivity analysis is required in order to examine result changes under different input data. This analysis should cover all criteria and subcriteria as well as their possible combinations in the different levels of the hierarchy tree. The results show that the five types of renewable energy based power plant rank in the first five positions regardless of criteria weight variations, due to their balanced high scores against them. Only biomass drops to the eighth position when quality of life has 100% weight. Nuclear power plants show impressive score and ranking variations between the first position for 100% quality of life weight and the tenth for 100% socioeconomic aspects weight. Natural gas based power plants rank slightly higher when quality of life importance increases while coal/lignite and oil have slightly better rankings when priority is given to socioeconomic aspects.

During the last decades, electricity generation contributed to socioeconomic development and changed people’s lives radically. Power plants based their operation mainly on coal and lignite while health and environmental damages were not examined as there were no historic data and their importance was undervalued [1] and [2]. Today, electricity demand is growing rapidly leading to construction of new power plants. Resources are depleting and sustainable solutions are explored. Global warming is no more ignored and international agreements and protocols are signed in order to prevent proliferation of greenhouse gases [3], [4], [5], [6], [7], [8] and [9]. Lately, health issues raised as harmful consequences of power plants, are rising rapidly [10], [11] and [12]. Financial development and the rise of living standards led people to cope with the bad side effects caused by factors that sustained this development for many years. Evaluation of power plants is not simple as several criteria are involved to cover every aspect of modern society. Multicriteria analysis and externalities assessment can be applied to evaluate electricity generation systems on the living standard [13] and [14]. A detailed analysis requires building of a model, the availability of appropriate data and the combination of objective and subjective evaluations. The analytic hierarchy process (AHP) is one of the most widely accepted methods used in multicriteria analysis to decompose complex problems into the appropriate hierarchy [15] and [16]. It incorporates the measurement of scores of alternative solutions against criteria and subcriteria grouped appropriately in several levels of the hierarchy tree. AHP also requires the assessment of criteria weights on which the overall synthesis evaluation is based.

Ten types of power plant were evaluated under several criteria. All factors that affect them were carefully examined in order to assess possible changes in final results when input data and criteria weights vary. The degree of the overall score and ranking alterations of the ten types of power plant under several representative sets of local and global criteria weighting, were thoroughly analyzed and compared. Five types of power plants, namely, photovoltaic, oil, coal/lignite, hydro and wind plants are the most stable with regard to criteria weight changes. Photovoltaics depict a remarkable stability under several criteria weightings, proving to be one of the best investments in the power plant generation sector under the criteria examined. Nuclear plant evaluation depicts the greatest score fluctuation. Nuclear plants rank first when “quality of life” has a 100% weight and last when “socioeconomic aspects” have a 100% weight. On the opposite, biomass ranks second when “socioeconomic aspects” have 100% weight and drops to the eighth position when “quality of life” has 100% weight. A rise in “quality of life” weight favours considerably nuclear and the two types of natural gas plant and less hydro and oil power plants. When the weight of “socioeconomic aspects” rise, biomass and geothermal power plants get the most benefit while wind, coal/lignite and photovoltaic improve less their overall score. Different technology and socioeconomic aspects as well as the decision makers’ culture and experience can lead to the most appropriate choice in each case.