Technical Papers
Jan 9, 2018

Energy Recovery in Water Networks: Numerical Decision Support Tool for Optimal Site and Selection of Micro Turbines

Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 3

Abstract

Energy efficiency plays a large role in the sustainability effort of water utilities. In gravity-fed pipe networks that present excessive pressures, the installation of micro turbines or pumps-as-turbines for energy recovery can provide significant benefits. The main obstacles associated with this kind of solution include the high cost of implementation (equipment and installation) and the time-consuming task of searching for potential and feasible sites for the power plant implementation. In this work, a numerical methodology for the analysis of any water supply and distribution network in order to optimally locate sites for maximum energy recovery and to preliminarily select or design turbines is proposed and validated with a case study. The idea of this decision support tool is to facilitate the assessment of the potential for energy production in networks and encourage the implementation of this type of efficiency measure. The proposed approach consists of two main stages: (1) identification of potential sites for energy recovery through an optimization procedure and (2) selection of adequate types of turbine and preliminary feasibility analysis.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 144Issue 3March 2018

History

Received: Dec 2, 2016
Accepted: Aug 22, 2017
Published online: Jan 9, 2018
Published in print: Mar 1, 2018
Discussion open until: Jun 9, 2018

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Authors

Affiliations

Bernardete Coelho
Researcher, Dept. of Mechanical Engineering, Centre for Mechanical Technology and Automation, GRIDS Research Group, Univ. of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
António Andrade-Campos [email protected]
Professor, Dept. of Mechanical Engineering, Centre for Mechanical Technology and Automation, GRIDS Research Group, Univ. of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal (corresponding author). E-mail: [email protected]

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