Simulated Annealing in Optimization of Energy Production in a Water Supply Network

Irene Samora (), Mário J. Franca (), Anton J. Schleiss () and Helena M. Ramos ()
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Irene Samora: École Polytecnique Fédérale de Lausanne
Mário J. Franca: École Polytecnique Fédérale de Lausanne
Anton J. Schleiss: École Polytecnique Fédérale de Lausanne
Helena M. Ramos: Instituto Superior Técnico - Universidade de Lisboa

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 4, No 14, 1533-1547

Abstract: Abstract In water supply systems, the potential exists for micro-hydropower that uses the pressure excess in the networks to produce electricity. However, because urban drinking water networks are complex systems in which flows and pressure vary constantly, identification of the ideal locations for turbines is not straightforward, and assessment implies the need for simulation. In this paper, an optimization algorithm is proposed to provide a selection of optimal locations for the installation of a given number of turbines in a distribution network. A simulated annealing process was developed to optimize the location of the turbines by taking into account the hourly variation of flows throughout an average year and the consequent impact of this variation on the turbine efficiency. The optimization is achieved by considering the characteristic and efficiency curves of a turbine model for different impeller diameters as well as simulations of the annual energy production in a coupled hydraulic model. The developed algorithm was applied to the water supply system of the city Lausanne (Switzerland). This work focuses on the definition of the neighborhood of the simulated annealing process and the analysis of convergence towards the optimal solution for different restrictions and numbers of installed turbines.

Keywords: Micro-hydropower; Water supply systems; Pipeline network; Optimization; Simulated annealing (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (20)

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DOI: 10.1007/s11269-016-1238-5

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