Performance Prediction of a Pump as Turbine: Sensitivity Analysis Based on Artificial Neural Networks and Evolutionary Polynomial Regression

Balacco, Gabriella

doi:10.3390/en11123497

Cited by 21 publications

(13 citation statements)

References 27 publications

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“…Several models have been proposed for the prediction of the characteristic curve of a PaT. Some models, based on statistical and normalization approaches or artificial neural networks [14,15], are adopted when the geometric parameters of the runner are unknown [16], and they are useful to evaluate the flow rate and the head exploited by the PaTs running at their best efficiency point. At the same time, other models are based on theoretical approach as for the evaluation of the flow characteristics through the machine, as proposed by Barbarelli et al [17], Gülich [18].…”

Section: Introductionmentioning

confidence: 99%

Slip Factor Correction in 1-D Performance Prediction Model for PaTs

Capurso

Stefanizzi

Pascazio

et al. 2019

Water

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In recent years, pumps operated as turbines (PaTs) have been gaining the interest of industry and academia. For instance, PaTs can be effectively used in micro hydropower plants (MHP) and water distribution systems (WDS). Therefore, further efforts are necessary to investigate their fluid dynamic behavior. Compared to conventional turbines, a lower number of blades is employed in PaTs, lowering their capability to correctly guide the flow, hence reducing the Euler’s work; thus, the slip phenomenon cannot be neglected at the outlet section of the runner. In the first part of the paper, the slip phenomenon is numerically investigated on a simplified geometry, evidencing the dependency of the lack in guiding the flow on the number of blades. Then, a commercial double suction centrifugal pump, characterized by the same specific speed, is considered, evaluating the dependency of the slip on the flow rate. In the last part, a slip factor correlation is introduced based on those CFD simulations. It is shown how the inclusion of this parameter in a 1-D performance prediction model allows us to reduce the performance prediction errors with respect to experiments on a pump with a similar specific speed by 5.5% at design point, compared to no slip model, and by 8% at part-loads, rather than using Busemann and Stodola formulas.

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Section: Introductionmentioning

confidence: 99%

Slip Factor Correction in 1-D Performance Prediction Model for PaTs

Capurso

Stefanizzi

Pascazio

et al. 2019

Water

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“…The combined artificial neural networks (ANN) and evolutionary polynomial regression (EPR) algorithms proposed by Balacoo have also been applied to obtain an accurate correlation (Balacco, 2018). Totally, 33 pumps are tested to determine correlations listed in Table 4.…”

Section: Authorsmentioning

confidence: 99%

Performance Prediction and Geometry Optimization for Application of Pump as Turbine: A Review

2022

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Pump as Turbine (PAT) is a technically and economically effective technology to utilize small/mini/micro/pico hydropower, especially in rural areas. There are two main subjects that influence the selection and application of PAT. On the one hand, manufacturers of pumps will not provide their characteristics under the turbine mode, which requires performance prediction methods. On the other hand, PAT efficiency is always slightly lower than that of pump, which requires further geometry optimization. This literature review summarized published research studies related to performance prediction and geometry optimization, aimed at guiding for selection and optimization of PAT. Currently, there exist four categories of performance prediction methods, namely, using BEP (Best Efficiency Point), using specific speed, loss modeling, and polynomial fitting. The using BEP and loss modeling methods are based on theoretical analysis, while using specific speed and polynomial fitting methods require statistical fitting. The prediction errors of published methods are within ±10% mostly. For geometry optimization, investigations mainly focus on impeller diameter and blade geometry. The influence of impeller trimming, blade rounding, blade wrap angle, blade profile, blade number, blade trailing edge position, and guide vane number has been studied. Among published methods, the blade rounding and forward-curved impellers are the most effective and feasible techniques.

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“…In line with this, several studies have been carried out, addressing the already available techno-scientific issues within both of PAT's operating modes [15][16][17]. In this respect, in addition to PAT performance prediction studies [18][19][20][21][22], investigations into PAT flow unsteadiness under off-design operating conditions and respective flow structure formation mechanism have been carried out, which in the long run should lead to the improvement in terms of PAT's well-balanced performance in both of its operating modes. Among the recently published details on the same topic, a drop in PAT's mechanical efficiency has been recorded under part-load conditions, as a result of flow detachment and swirling flows that occurred within the machine flow channels [23].…”

Section: Introductionmentioning

confidence: 98%

Investigation into Pump Mode Flow Dynamics for a Mixed Flow PAT with Adjustable Runner Blades

et al. 2021

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The adoption of pumps as turbines (PATs) in both small-scale hydroelectric plants and water supply systems has brought about various advantages, the most recognized being cost-effectiveness compared to other hydroturbines. However, due to their lack of flow control ability, their intolerance to off-design operations constitutes a tough shortfall. Moreover, since this technology is new, PAT flow dynamics are not yet well understood. Therefore, this study intends to numerically investigate the mixed-flow PAT’s pump mode flow dynamics for five operating conditions from optimum (1 QBEP) to deep part-load (0.41 QBEP) conditions. Moreover, the effect of runner blade angle on them is investigated, considering three angles, namely −2°, 0°, and 2°. PAT flow stability was found to deteriorate as the flow decreased, where associated pressure pulsation level worsened at different flow zones. In addition, the blade angle increase led to correspondingly increasing flow unsteadiness and pressure pulsation levels, where the pulsation frequencies from rotor-stator interactions were dominant for most flow zones. This study’s findings are of crucial importance to both scientific and engineering communities as they contribute to a thorough understanding of PAT flow dynamics.

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Performance Prediction of a Pump as Turbine: Sensitivity Analysis Based on Artificial Neural Networks and Evolutionary Polynomial Regression

Cited by 21 publications

References 27 publications

Slip Factor Correction in 1-D Performance Prediction Model for PaTs

Slip Factor Correction in 1-D Performance Prediction Model for PaTs

Performance Prediction and Geometry Optimization for Application of Pump as Turbine: A Review

Investigation into Pump Mode Flow Dynamics for a Mixed Flow PAT with Adjustable Runner Blades

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