Abstract
AbstractWater supply is energy intensive, resulting in large amounts of greenhouse gas emissions and increased electricity bills for water service providers (WSPs). In recent years, the incorporation of microhydropower (MHP) turbines within water supply networks (WSN) has been shown to be a viable option for pressure reduction and improved water supply sustainability. An option for optimal pressure management of a WSN is presented through the installation of MHP turbines. The optimization objective was to find optimal locations in a WSN to install turbines for maximized power generation. For comparison, a nonlinear programming approach, a mixed integer nonlinear programming (MINLP) approach, and an evolutionary optimization approach, using a genetic algorithm, were employed. The performance and suitability of each method was initially demonstrated on a theoretical five-node WSN. MINLP was found to be the most suitable technique. Further analyses were undertaken of a benchmark 25-node network. It was recom...
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