Adaptive and Improved Multi-population Based Nature-inspired Optimization Algorithms for Water Pump Station Scheduling

Turci, Luca de Oliveira; Wang, Jingcheng; Brahmia, Ibrahim

doi:10.1007/s11269-020-02588-3

Cited by 19 publications

(5 citation statements)

References 11 publications

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“…The safe and efficient operation of water supply systems is crucial, where digital tools, such as monitoring, hydro-informatics, and optimization algorithms, are key approaches that can play an important role in support decisions [45]. Turci, Wang, and Brahmia, based on traditional multi-population-based nature-inspired optimization algorithms, such as genetic algorithm (GA), ant colony optimization (ACO), and particle swarm optimization (PSO), adapted and improved the models to fit the complex constraints and characteristics of the system [21]. Cimorelli and others also investigated genetic algorithms to approximate solutions to optimal pump scheduling problems (OPS) [22].…”

Section: Discussionmentioning

confidence: 99%

Binary Linear Programming as a Tool of Cost Optimization for a Water Supply Operator

Kowalik

Rzemieniak

2021

Sustainability

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The problem of scheduling pumps is widely discussed in the literature in the context of improving energy efficiency, production costs, emissions, and reliability. In some studies, the authors analyze the available case studies and compare the results; others present their own computational methods. In the paper, a problem of pump scheduling in regular everyday operations of a water supply operator is considered. The issues of water production optimization and energy savings are part of the topic of sustainable development. The objective of the article is the minimization of the cost of electric power used by the pumps supplying water. It is achieved thanks to the variability of both the demand for water and the price of electric power during the day combined with the possibility of storing water. The formulation of an existing electric power cost optimization problem as a binary linear programming problem was improved. An essential extension of the above mathematical model, which enables more flexible management of the pump system, was also proposed. An example containing real-world input data was successfully solved using Microsoft Excel with a free OpenSolver add-in.

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Section: Discussionmentioning

confidence: 99%

Binary Linear Programming as a Tool of Cost Optimization for a Water Supply Operator

Kowalik

Rzemieniak

2021

Sustainability

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“…The work proposed by Quintilliani et al [7] is based on the activation/deactivation of each pump, based on the determination of the electrical time slots with the lowest tariff cost. Using traditional optimization algorithms inspired by nature and based on multi-population, such as the Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization, proposed by Turci et al [8], the aim was to determine the best programming mechanism for pumping stations. In addition, evolutionary multi-target algorithms are a useful tool for solving multi-target optimization problems, such as the one presented by Makaremi et al [9] through the functions: energy cost and the number of pump switches.…”

Section: Efficient Energy Management In Pumpingmentioning

confidence: 99%

Improving Energy Efficiency of Irrigation Wells by Using an IoT-Based Platform

López-Morales

Martı́nez²,

Skarmeta

2021

Electronics

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The irrigation sector has undergone a remarkable transformation in recent decades due to the application of pressurized water distribution technologies, improving the management of limited water resources. As a result of this transformation, irrigation has become, together with agricultural machinery, the primary consumer of energy within the agri-food sector. Furthermore, the energy cost of operating pumping equipment during a farming season represents 30–40% of the crop’s total cost. For this reason, one of the most interesting challenges in this scope is that of improving energy efficiency and reducing economic costs so that productive work become more and more competitive. Energy audit makes possible to determine the efficiency of installations, and enables to determine energy saving protocols (requirements), for this reason the aim of this article is to carry out these by using IoT-based systems. The proposed system improves decision-making on agricultural pumping management by classifying wells’ efficiency and integrating the data sets that determine their efficiency into a single information model. The system monitors energy efficiency according to different parameters such as: infrastructure, energy consumption, electric rates, manometric height or type of installation, making it possible to enhance each pumping operation’s decisions. This solution has been deployed in an irrigation community in southeast Spain whose results have warned about the lack of efficiency in two of its wells: in one of them it is proposed that they be replaced, due to the high cost of pumping water, and in the other, hydraulic mechanisms are implemented to improve the water-energy binomial.

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“…x j (t + 1) = x j (t) + v j (t + 1) (18) where j represents the jth particle; w is inertial weight; c 1 and c 2 are study factors; r 1 and r 2 are two independent random numbers between 0 and 1; v j is the velocity of particle j; x j is the position of particle j; p j is the best experience of particle j; and p g is the best experience of the all particles. Simulated annealing (abbreviating as SA) is based on the physical annealing process of solid matter [26].…”

Section: Simulated Annealing-particle Swarm Optimizationmentioning

confidence: 99%

“…Zhang et al [17] optimized the scheduling of cascade pumping stations in an openchannel water transfer systems based on station skipping. Turci et al [18] reported two adaptive and one improved multi-population-based nature-inspired optimization algorithms for water pump station scheduling, comparing it with GA, PSO and ant colony optimization (ACO) to show its better performance. Dong and Yang [19] proposed a data-driven model to carry out the operation optimization scheduling of water diversion and drainage pumping stations in the presence of complex hydrometeorological constraints.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Parallel Pumping Station Operations in an Open-Channel Water Transfer System Using an Efficient Hybrid Algorithm

Feng¹,

Qiu²,

Wang³

2020

Energies

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This article presents a methodology for optimizing the operation of parallel pumping stations in an open-channel water transfer system. A mathematical model was established for the minimum power with constraints on water level, flow rate and pump unit performance, and related factors. In the objective function, energy consumption of relevant equipment or facilities, such as main pump units, power transmission and transformation equipment, and auxiliary equipment, was considered comprehensively. The model was decomposed to two layers for solving. In the first layer, by using discharge distribution ratio as a variable, the flow rate and water level of the two water channels could be determined by employing the dichotomy approach (DA), and were calculated according to the principle of energy conservation, considering energy loss caused by hydraulic leakage and evaporation losses. In the second layer, the number of running pumps and the flow rate of a single pump were obtained by simulated annealing–particle swarm optimization (SA–PSO). The hybrid of the two algorithms is called the dichotomy approach–simulated annealing–particle swarm optimization (DA–SA–PSO). To verify the efficiency and validity of DA–SA–PSO, SA–PSO is also applied to determine discharge distribution ratio. The results indicate that the computation time using DA–SA–PSO is 1/30 of that using double-layer SA–PSO (dSA–PSO). Compared with the original plan, the optimal solution could result in power savings of 14–35%. Thus, the DA–SA–PSO is highly efficient for optimizing system operation in real time.

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Adaptive and Improved Multi-population Based Nature-inspired Optimization Algorithms for Water Pump Station Scheduling

Cited by 19 publications

References 11 publications

Binary Linear Programming as a Tool of Cost Optimization for a Water Supply Operator

Binary Linear Programming as a Tool of Cost Optimization for a Water Supply Operator

Improving Energy Efficiency of Irrigation Wells by Using an IoT-Based Platform

Optimizing Parallel Pumping Station Operations in an Open-Channel Water Transfer System Using an Efficient Hybrid Algorithm

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