2022
Dijk, Marco; Vuuren, Stefanus Johannes; Cavazzini, Giovanna; Niebuhr, Chantel Monica; Santolin, Alberto
Optimizing Conduit Hydropower Potential by Determining Pareto-Optimal Trade-Off Curve Journal Article
In: Sustainability (Switzerland), vol. 14, iss. 13, 2022, ISSN: 20711050.
Abstract | Links | BibTeX | Tags: conduit hydropower, energy recovery, Genetic Algorithm, optimized energy generation, pareto optimality, renewable energy
@article{vanDijk2022,
title = {Optimizing Conduit Hydropower Potential by Determining Pareto-Optimal Trade-Off Curve},
author = {Marco Dijk and Stefanus Johannes Vuuren and Giovanna Cavazzini and Chantel Monica Niebuhr and Alberto Santolin},
doi = {10.3390/su14137876},
issn = {20711050},
year = {2022},
date = {2022-01-01},
journal = {Sustainability (Switzerland)},
volume = {14},
issue = {13},
abstract = {In numerous locations of bulk water supply/distribution systems, energy is dissipated by pressure-reducing devices, whereas it could be recovered by means of turbines or pumps as turbines. These pipe systems, owned and operated by municipalities, water utilities, large water-consuming industries, and mines, could be used as a source of renewable sustainable energy. However, the exploitation of these systems presents several issues related to the complexity of the operational optimization of the hydropower generation facilities and to the potential negative impact on the reliability of the system itself. We have developed a novel procedure to optimize the energy generation in such a conduit system by assessing the interrelationship of storage volumes, demand patterns, operating cycles, and electricity tariff structures. The procedure is a multi-objective genetic algorithm designed to provide a solution to maximize electricity generation and thus revenue and to minimize the risk involved in supplying the demand. A Pareto-optimal trade-off curve is set up, indicating the potential benefit (revenue) versus the reliability index (supply security). The results indicate that a Pareto-optimal trade-off curve was generated from which a solution could be selected which would improve the weekly revenue by up to 7.5%, while still providing a reliable water supply system.},
keywords = {conduit hydropower, energy recovery, Genetic Algorithm, optimized energy generation, pareto optimality, renewable energy},
pubstate = {published},
tppubtype = {article}
}
In numerous locations of bulk water supply/distribution systems, energy is dissipated by pressure-reducing devices, whereas it could be recovered by means of turbines or pumps as turbines. These pipe systems, owned and operated by municipalities, water utilities, large water-consuming industries, and mines, could be used as a source of renewable sustainable energy. However, the exploitation of these systems presents several issues related to the complexity of the operational optimization of the hydropower generation facilities and to the potential negative impact on the reliability of the system itself. We have developed a novel procedure to optimize the energy generation in such a conduit system by assessing the interrelationship of storage volumes, demand patterns, operating cycles, and electricity tariff structures. The procedure is a multi-objective genetic algorithm designed to provide a solution to maximize electricity generation and thus revenue and to minimize the risk involved in supplying the demand. A Pareto-optimal trade-off curve is set up, indicating the potential benefit (revenue) versus the reliability index (supply security). The results indicate that a Pareto-optimal trade-off curve was generated from which a solution could be selected which would improve the weekly revenue by up to 7.5%, while still providing a reliable water supply system.
2020
Bonthuys, Gideon Johannes; Dijk, Marco; Cavazzini, Giovanna
The Optimization of Energy Recovery Device Sizes and Locations in Municipal Water Distribution Systems during Extended-Period Simulation Journal Article
In: Water, vol. 12, iss. 9, pp. 2447, 2020, ISSN: 2073-4441.
Abstract | Links | BibTeX | Tags: energy recovery, Extended-period simulation, Genetic Algorithm, Leakage Reduction, Water distribution
@article{Bonthuys2020,
title = {The Optimization of Energy Recovery Device Sizes and Locations in Municipal Water Distribution Systems during Extended-Period Simulation},
author = {Gideon Johannes Bonthuys and Marco Dijk and Giovanna Cavazzini},
url = {https://www.mdpi.com/2073-4441/12/9/2447},
doi = {10.3390/w12092447},
issn = {2073-4441},
year = {2020},
date = {2020-01-01},
journal = {Water},
volume = {12},
issue = {9},
pages = {2447},
abstract = {Excess pressure within water distribution systems not only increases the risk for water losses through leakages but provides the potential for harnessing excess energy through the installation of energy recovery devices, such as turbines or pump-as-turbines. The effect of pressure management on leakage reduction in a system has been well documented, and the potential for pressure management through energy recovery devices has seen a growth in popularity over the past decade. Over the past 2 years, the effect of energy recovery on leakage reduction has started to enter the conversation. With the theoretical potential known, researchers have started to focus on the location of energy recovery devices within water supply and distribution systems and the optimization thereof in terms of specific installation objectives. Due to the instrumental role that both the operating pressure and flow rate plays on both leakage and potential energy, daily variation and fluctuations of these parameters have great influence on the potential energy recovery and subsequent leakage reduction within a water distribution system. This paper presents an enhanced optimization procedure, which incorporates user-defined weighted importance of specific objectives and extended-period simulations into a genetic algorithm, to identify the optimum size and location of potential installations for energy recovery and leakage reduction. The proposed procedure proved to be effective in identifying more cost-effective and realistic solutions when compared to the procedure proposed in the literature.},
keywords = {energy recovery, Extended-period simulation, Genetic Algorithm, Leakage Reduction, Water distribution},
pubstate = {published},
tppubtype = {article}
}
Excess pressure within water distribution systems not only increases the risk for water losses through leakages but provides the potential for harnessing excess energy through the installation of energy recovery devices, such as turbines or pump-as-turbines. The effect of pressure management on leakage reduction in a system has been well documented, and the potential for pressure management through energy recovery devices has seen a growth in popularity over the past decade. Over the past 2 years, the effect of energy recovery on leakage reduction has started to enter the conversation. With the theoretical potential known, researchers have started to focus on the location of energy recovery devices within water supply and distribution systems and the optimization thereof in terms of specific installation objectives. Due to the instrumental role that both the operating pressure and flow rate plays on both leakage and potential energy, daily variation and fluctuations of these parameters have great influence on the potential energy recovery and subsequent leakage reduction within a water distribution system. This paper presents an enhanced optimization procedure, which incorporates user-defined weighted importance of specific objectives and extended-period simulations into a genetic algorithm, to identify the optimum size and location of potential installations for energy recovery and leakage reduction. The proposed procedure proved to be effective in identifying more cost-effective and realistic solutions when compared to the procedure proposed in the literature.
