With the increase of the world’s nuclear facilities decommissioning activities, people all over the world pay more and more attention to decommissioning strategy. In order to strengthen the exchange of experience related to decommissioning activities in the world, both in 2002 Germany Berlin and in 2006 Greece Athens, IAEA held the international conference on lessons learned from the decommissioning twice. Decommissioning was one of the most important conference topics each time. The meeting also reached a consensus that it is necessary to consider decommissioning as soon as possible.

This paper analyzes and discusses nine kinds of factors influencing decommissioning strategy, including source survey, waste management, government policy, decommissioning step, decommissioning cost, decommissioning technology, public acceptance, soil acceptable level and optimization of radiation protection. These nine factors are chosen for a variety of factors on the comprehensive consideration of affecting degree. In other word, they are more important factors to represent the problem as thoroughly as possible.

Analytic hierarchy process (AHP) is a systematic and hierarchical multi-objective decision analysis method. It is a basic approach to decision making which is proposed by T L. Saaty in 1970s, who is a professor of Pittsburgh University and the primary theoretician of AHP. In this paper, the goal is how to choose the appropriate decommissioning strategy using the method of AHP. The preferred decommissioning strategy should consider various factors, such as policy, economy, radiation protection, public acceptance, waste management and so on. Some factors are quantitative while others are qualitative. At present, there are three kinds of nuclear power plant (NPP) decommissioning strategy including immediate dismantling, deferred dismantling and entombment. The three kinds of decommissioning strategies all have their respective pros and cros.

Analytic hierarchy model includes goal layer, criterion layer and program layer. In this paper, selection of decommissioning strategy is the goal layer. Nine chosen factors make up the criterion layer and three different decommissioning strategies constitute the program layer. The next step is comparative judgment which means the elements on the criterion layer are arranged into a matrix and the goal makes judgment about the relative importance of the elements with respect to the overall goal. The matrixes of pairwise comparisons of facts in criterion layer to program layer are also given in the paper. The fundamental scale of values to represent the intensities of judgments is the 1∼9 scale.

For each pairwise comparison matrix, the maximum eigenvalue and corresponding eigenvector are calculated. Consistency index (CI), random Consistency Index (RI) and consistency ratio (CR) are used to check consistency. In case inspection result meets the conformance requirement, normalized feature vector is the weight vector. On the contrary, it is needed to reconstruct the pairwise comparison matrix. Only by all matrixes go through consistency checking can results meet the satisfied conformance requirements. Meanwhile, the weights of nine factors in pairwise comparison matrixes are also discussed in the paper.

In summary, based on the principle of AHP, an analytic hierarchy model of NPP decommissioning strategy choice has been established. Paired comparison judgments in the AHP are applied to pairs of these factors. The AHP method uses pairwise comparison of factors and contrasts them using a relative scale in order to minimize the difference in the nature of the different factors to compare with each other and also improve accuracy. The calculation results show that deferred dismantling (Weight: 0.4663) is superior to immediate dismantling (Weight: 0.3768), and immediate dismantling is better than entombment (Weight: 0.1569). These factors are ranked according to the weight of calculation results. The top three factors are government policies (Weight: 0.3512), decommissioning cost (Weight: 0.2038) and waste management (Weight: 0.1611).

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