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Penstock material selection in small hydropower plants using MADM methods

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  • Kumar, Ravi
  • Singal, S.K.

Abstract

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.

Suggested Citation

  • Kumar, Ravi & Singal, S.K., 2015. "Penstock material selection in small hydropower plants using MADM methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 240-255.
    • Handle: RePEc:eee:rensus:v:52:y:2015:i:c:p:240-255
    DOI: 10.1016/j.rser.2015.07.018
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    References listed on IDEAS

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    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    2. Sachin K. Patil & Ravi Kant, 2014. "Ranking the barriers of knowledge management adoption in supply chain using fuzzy AHP method," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 8(1), pages 52-75.
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    4. de Souza, Lorena Mendes & Mendes, Pietro A.S. & Aranda, Donato A.G., 2020. "Oleaginous feedstocks for hydro-processed esters and fatty acids (HEFA) biojet production in southeastern Brazil: A multi-criteria decision analysis," Renewable Energy, Elsevier, vol. 149(C), pages 1339-1351.
    5. Qiang Yang & Ping-an Du & Yong Wang & Bin Liang, 2018. "Developing a rough set based approach for group decision making based on determining weights of decision makers with interval numbers," Operational Research, Springer, vol. 18(3), pages 757-779, October.
    6. Urošević, Branka Gvozdenac & Marinović, Budimirka, 2021. "Ranking construction of small hydro power plants using multi-criteria decision analysis," Renewable Energy, Elsevier, vol. 172(C), pages 1174-1183.
    7. Ahmad, Salman & Nadeem, Abid & Akhanova, Gulzhanat & Houghton, Tom & Muhammad-Sukki, Firdaus, 2017. "Multi-criteria evaluation of renewable and nuclear resources for electricity generation in Kazakhstan," Energy, Elsevier, vol. 141(C), pages 1880-1891.
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    9. Lingyun, Guo & Markus, Niffenegger & Jing, Zhou, 2022. "A novel procedure to evaluate the performance of failure assessment models," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    10. Tian, Guangdong & Zhang, Honghao & Feng, Yixiong & Wang, Danqi & Peng, Yong & Jia, Hongfei, 2018. "Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 682-692.
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