4.8 Review

Penstock material selection in small hydropower plants using MADM methods

期刊

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 52, 期 -, 页码 240-255

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2015.07.018

关键词

Small hydropower; Penstock; AHP; TOPSIS; Modified TOPSIS; Material selection

资金

  1. Ministry of New and Renewable Energy. Government of India [69-MNRE]

向作者/读者索取更多资源

Small hydropower (SHP) is a promising source of renewable and clean energy. Selection of proper material for different components of SHP projects in general and penstock in particular is one of the most challenging tasks as civil work components contribute substantially in the overall cost of the project. There is no systematic and efficient approach found in the literature for selecting best material and consequently engineers take number of criteria for such selection. In the recent time, the verities of material are increasing very fast with various properties, which make material selection process complicated. In the present study, an effort has been made to apply Multiple Attribute Decision Making (MADM) methods for solving the material selection problem for penstock in SHP installations. Analytic hierarchy process (AHP), technique for order preference by similarity to ideal solution (TOPSIS) and Modified TOPSIS methods are used to select the best material. Four alternative materials such as polyvinyl chloride (PVC), high-density polyethylene (HDPE), glass reinforced polymer (GRP) and mild steel (MS) and five assessment attributes/criteria such as yield strength, life, thickness, cost of material and maintenance cost have been considered in the analysis. Two case studies have also been analyzed and included in the study. It has been found that TOPSIS and Modified TOPSIS methods are best suited for penstock material selection and mild steel is the suitable material as compared to other materials. (C) 2015 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据