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Problems Associated with Hydraulic Turbines

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Harmony Search and Nature Inspired Optimization Algorithms

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 741))

Abstract

Hydropower is a renewable source of energy and considered to be one of the most cost-efficient and environmentally friendly technology for electricity production. Hydropower has operational flexibility like quick starting, stopping and load variations, these help in improving the reliability of power systems by allowing it to work in different conditions. In the late nineteenth century, hydropower became a source for generating electricity. Hydropower is the most important and widely used renewable source of power. The hydropower reserves of India have been estimated by the Central water and power commission to have a potential for installing 411,180 MW. Earlier hydroelectric plants have been used as exclusive sources of power, now the modern trend is bending towards the use of hydropower in an interconnected system with thermal stations. This paper focuses on the recent progress in the study of hydraulic machinery including pumps, and hydro turbines and the problems that revolve around them. Since these instabilities are a vital issue and rather harmful to the operational safety of hydro machines, these problems have been extensively discussed in literature and to some extent in our review. This study provides the in-depth analysis of the problems associated with the hydro machinery like cavitation, material related problems, silt erosion, fatigue, etc., and demands focus on design, manufacturing, operation, and maintenance of the turbines. This is followed by our deduction on what is required to improve their working and a sensor based online inspection model for ease of surveillance and maintenance.

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Correspondence to Kunal Govil .

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Kumar, A., Govil, K., Dwivedi, G., Chhabra, M. (2019). Problems Associated with Hydraulic Turbines. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_60

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