Development of an Algorithm for Sustainability Based Assessment of Reservoir Life Cycle Cost Using Fuzzy Theory

Abstract

Sustainability assessment can be used as a basic managerial analysis to evaluate the capability of water resources in supplying associated demands. Alteration of management policies in order to improve the systems' performance and sustainability can lead to additional costs of system operation. In this study a novel framework is proposed for assessing economic life cycle costs of dams considering system's performance from sustainability aspect. For convenience, the term Life Cycle Costs (LCC) is used instead of Economic LCC throughout this paper. First, a fuzzy model is proposed to discount and estimate the LCC of dams in different time intervals of their life span including: Construction, Operation and Maintenance (M&O), and Disposal periods. The model is capable of reflecting uncertainties caused by estimation and previsions of different costs because of fuzzy theory application. Then, sustainability of dam performance in operation period is evaluated through triple criteria of Reliability, Reversibility, and Vulnerability (R-R-V). To provide more realistic results, different system performance levels are defined based on the system's capability to supply demands and the importance of each level is evaluated by weighting them. Furthermore, it is studied how changes in reservoirs operation strategies can reduce the LCC because of higher performance. The proposed methodology is applied to assess the LCC and performance of a dam located at North Eastern part of Iran. The results show that the system's performance is remarkably enhanced when the operating rules are revised and this change will intangibly reduce the economic benefits.

Full Life Cycle Management of Power System Integrated With Renewable Energy: Concepts, Developments and Perspectives

“…Besides, there are two kinds of estimation methods: certainty and uncertainty. For the former, there are more evaluation models (Cole and Sterner, 2000;Vahdat-Aboueshagh et al, 2014); for the latter, there are Monte Carlo method (Ammar et al, 2013;Goh and Sun, 2016), fuzzy set method (Shahata and Zayed, 2013;Plebankiewicz et al, 2020) and neural network (NN) (Ilg et al, 2017). For the existing asset estimation methods, the accuracy of LCC model depends on the choice of calculation method and the certainty of data.…”