Performance of centrifugal pumps running in reverse as turbine: Part Ⅱ- systematic specific speed and specific diameter based performance prediction. (December 2016)

• Record Type: Journal Article
• Authors: Tan, Xu; Engeda, Abraham
• Is Part Of: Renewable energy. Volume 99(2016)
• Page Start: 188
• Page End: 197
• Publication Date: 2016-12
• Subjects: PAT -- Best efficiency performances -- Performance prediction -- Specific speed -- Specific diameter; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2016.06.052
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: This paper, Part II of a two part paper, presents a comprehensive correlation aimed to bring out the accurate prediction of the turbine mode operation of centrifugal pumps. This work uses experimental data of wide range of pumps representing the centrifugal pump configurations in terms of specific speed. Based on specific speed and specific diameter an accurate correlation is developed to predict the performances at best efficiency point of the centrifugal pump in its turbine mode operation. The proposed prediction method yields very good results to date compared to previous such attempts. The present method is compared to nine previous methods found in the literature. The comparison results show that the method proposed in this paper is the most accurate. The proposed method can be further complemented and supplemented by more future tests to increase its accuracy. The proposed method is meaningful because it is based on both specific speed and specific diameter. Highlights: The ratio between the efficiencies of two running modes increases with the pump's specific speed in a roughly linear trend. With predicted specific speed and diameter, the head and flow in turbine mode can be estimated. This paper compares a newly proposed turbine mode performance prediction approach with nine previously published predictions. This new prediction is the most accurate.