Hardware-In-The-Loop Assessment of Robust Fuzzy Control Solutions for Hydroelectric and Wind Turbine Models

The interest towards renewable energy resources is increasing, and in particular it concerns wind and hydro powers, where the key point regards their efficient conversion into electric energy. To this end, control techniques can be used to meet this purpose, especially the ones relying on fuzzy models, due to their capabilities to manage nonlinear dynamic processes working in different conditions, and affected by faults, measurement errors, uncertainty and disturbances. The design methods addressed in this paper were already developed and validated for wind turbine plants, and important results can be achieved from their appropriate design and application to hydroelectric plants. This is the key issue of the paper, which recalls some considerations on the proposed solutions, as well as their validation to these energy conversion systems. Note that works available in the related literature that consider both wind and hydraulic energy conversion systems investigate a limited number of common issues, thus leading to little exchange opportunities and reduced common research aspects. Another important point addressed in the paper is that the proposed control design solutions are able to take into account the different working conditions of these power plants. Moreover, faults, uncertainty, disturbance and model reality mismatch effects are also considered when analyzing the reliability and robustness features of the derived control schemes. To this end, proper hardware in the loop tools are considered to verify and validate the developed control schemes in more realistic environments. Copyright (C) 2022 The Authors

Energy production by means of pumps as turbines in water distribution networks

This paper deals with the estimation of the energy production by means of pumps used as turbines to exploit residual hydraulic energy, as in the case of available head and flow rate in water distribution networks. To this aim, four pumps with different characteristics are investigated to estimate the producible yearly electric energy. The performance curves of Pumps As Turbines (PATs), which relate head, power, and efficiency to the volume flow rate over the entire PAT operation range, were derived by using published experimental data. The four considered water distribution networks, for which experimental data taken during one year were available, are characterized by significantly different hydraulic features (average flow rate in the range 10-116 L/s; average pressure reduction in the range 12-53 m). Therefore, energy production accounts for actual flow rate and head variability over the year. The conversion efficiency is also estimated, for both the whole water distribution network and the PAT alone.This paper deals with the estimation of the energy production by means of pumps used as turbines to exploit residual hydraulic energy, as in the case of available head and flow rate in water distribution networks. To this aim, four pumps with different characteristics are investigated to estimate the producible yearly electric energy. The performance curves of Pumps As Turbines (PATs), which relate head, power, and efficiency to the volume flow rate over the entire PAT operation range, were derived by using published experimental data. The four considered water distribution networks, for which experimental data taken during one year were available, are characterized by significantly different hydraulic features (average flow rate in the range 10-116 L/s; average pressure reduction in the range 12-53 m). Therefore, energy production accounts for actual flow rate and head variability over the year. The conversion efficiency is also estimated, for both the whole water distribution network and the PAT alone

Comparison of different approaches to predict the performance of pumps as turbines (PATs)

This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs). The considered approaches are four, i.e., one physics-based simulation model ("white box" model), two "gray box" models, which integrate theory on turbomachines with specific data correlations, and one "black box" model. More in detail, the modeling approaches are: (1) a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2) a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3) the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4) an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53-5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed.This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs). The considered approaches are four, i.e., one physics-based simulation model ("white box" model), two "gray box" models, which integrate theory on turbomachines with specific data correlations, and one "black box" model. More in detail, the modeling approaches are: (1) a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2) a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3) the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4) an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53-5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed

Comparison of different approaches to predict the performance of pumps as turbines (PATs)

This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs). The considered approaches are four, i.e., one physics-based simulation model ("white box" model), two "gray box" models, which integrate theory on turbomachines with specific data correlations, and one "black box" model. More in detail, the modeling approaches are: (1) a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2) a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3) the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4) an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53-5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed.This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs). The considered approaches are four, i.e., one physics-based simulation model ("white box" model), two "gray box" models, which integrate theory on turbomachines with specific data correlations, and one "black box" model. More in detail, the modeling approaches are: (1) a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2) a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3) the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4) an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53-5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed

Water level forecasting through fuzzy logic and artificial neural network approaches

In this study three data-driven water level forecasting models are presented and discussed. One is based on the artificial neural networks approach, while the other two are based on the Mamdani and the Takagi-Sugeno fuzzy logic approaches, respectively. <P style='line-height: 20px;'> All of them are parameterised with reference to flood events alone, where water levels are higher than a selected threshold. The analysis of the three models is performed by using the <I>same input and output variables</I>. However, in order to evaluate their capability to deal with different levels of information, two different input sets are considered. The former is characterized by significant spatial and time aggregated rainfall information, while the latter considers rainfall information more distributed in space and time. <P style='line-height: 20px;'> The analysis is made with great attention to the reliability and accuracy of each model, with reference to the Reno river at Casalecchio di Reno (Bologna, Italy). It is shown that the two models based on the fuzzy logic approaches perform better when the physical phenomena considered are synthesised by both a limited number of variables and IF-THEN logic statements, while the ANN approach increases its performance when more detailed information is used. As regards the reliability aspect, it is shown that the models based on the fuzzy logic approaches may fail unexpectedly to forecast the water levels, in the sense that in the testing phase, some input combinations are not recognised by the rule system and thus no forecasting is performed. This problem does not occur in the ANN approach

DNA quantification to assess Zymoseptoria tritici on a susceptible cultivar of durum wheat to establish the best timing for fungicide application in an italian environment

Zymoseptoria tritici, a globally distributed pathogen, is responsible of Septoria tritici blotch (STB), one of the most damaging wheat diseases. In Italy the incidence of STB has increased during the past few years. The presence of Z. tritici on flag leaves of susceptible durum wheat plants, cultivar San Carlo, after a single artificial inoculation with two inoculum concentrations at different vegetative stages has been evaluated in the plain of Bologna (North of Italy), in a two year field study (2012–2013). The pathogen presence was also assessed in natural infection conditions after a fungicide application in the second year (2013). The results obtained, by visual examination (Incidence, Disease Severity) and DNA quantification by Real time PCR, demonstrated that BBCH 39 (flag leaf stage) is the most susceptible vegetative stage, independently of inoculum concentration and climatic conditions. A good correlation between Disease Severity and DNA quantity was observed in either sampling methods, entire flag leaves and flag leaf discs. Thereafter the most suitable period to obtain the best crop protection with only one fungicide treatment is the flag leaf stage

Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems

[EN] This document is intended to be a presentation of the Special Issue "Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems". The final aim of this Special Issue is to propose a suitable framework supporting insightful hydraulic mechanisms to aid the decision-making processes of water utility managers and practitioners. Its 18 peer-reviewed articles present as varied topics as: water distribution system design, optimization of network performance assessment, monitoring and diagnosis of pressure pipe systems, optimal water quality management, and modelling and forecasting water demand. Overall, these articles explore new research avenues on urban hydraulics and hydroinformatics, showing to be of great value for both Academia and those water utility stakeholders.Herrera Fernández, AM.; Meniconi, S.; Alvisi, S.; Izquierdo Sebastián, J. (2018). Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems. Water. 10(4):1-7. https://doi.org/10.3390/w10040440S1710

Efficacy of adalimumab as second-line therapy in a pediatric cohort of crohn’s disease patients who failed infliximab therapy: The Italian society of pediatric gastroenterology, hepatology, and nutrition experience

Background: Adalimumab (Ada) treatment is an available option for pediatric Crohn’s disease (CD) and the published experience as rescue therapy is limited. Objectives: We investigated Ada efficacy in a retrospective, pediatric CD cohort who had failed previous infliximab treatment, with a minimum follow-up of 6 months. Methods: In this multicenter study, data on demographics, clinical activity, growth, laboratory values (CRP) and adverse events were collected from CD patients during follow-up. Clinical remission (CR) and response were defined with Pediatric CD Activity Index (PCDAI) score ≤10 and a decrease in PCDAI score of ≥12.5 from baseline, respectively. Results: A total of 44 patients were consecutively recruited (mean age 14.8 years): 34 of 44 (77%) had active disease (mean PCDAI score 24.5) at the time of Ada administration, with a mean disease duration of 3.4 (range 0.3–11.2) years. At 6, 12, and 18 months, out of the total of the enrolled population, CR rates were 55%, 78%, and 52%, respectively, with a significant decrease in PCDAI scores (P&lt;0.01) and mean CRP values (mean CRP 5.7 and 2.4 mL/dL, respectively; P&lt;0.01) at the end of follow-up. Steroid-free remission rates, considered as the total number of patients in CR who were not using steroids at the end of this study, were 93%, 95%, and 96% in 44 patients at 6, 12, and 18 months, respectively. No significant differences in growth parameters were detected. In univariate analysis of variables related to Ada efficacy, we found that only a disease duration &gt;2 years was negatively correlated with final PCDAI score (P&lt;0.01). Two serious adverse events were recorded: 1 meningitis and 1 medulloblastoma. Conclusion: Our data confirm Ada efficacy in pediatric patients as second-line biological therapy after infliximab failure. Longer-term prospective data are warranted to define general effectiveness and safety in pediatric CD patients

Measurement of surface velocity in open channels using a lightweight remotely piloted aircraft system

ABSTRACTIn this paper, a low-cost remotely piloted aircraft system (RPAS) technique is proposed for measurement of the surface velocity in rivers or channels with low surface velocity and small discharge. To verify the reliability of the results obtained with the RPAS, we simultaneously measured the surface velocity with other methods based on total stations and close range photogrammetry. The RPAS was used both with ground control points (GCPs) for orientation of the photographic images and without GCPs. The data analysis showed that the RPAS provides valid results even without GCPs. Use of a RPAS without GCPs, relying solely on flight altitude to determine the water velocity, opens the way for its utilization in emergency conditions when it is impossible to access the river banks for the realization and survey of GCPs

On-line hydraulic state prediction for water distribution systems

World Environmental and Water Resources Congress 2009: Great Rivers Proceedings of World Environmental and Water Resources Congress 2009 May 17–21, 2009 Kansas City, MissouriThis paper describes and demonstrates a method for on‐line hydraulic state prediction in urban water networks. The proposed method uses a Predictor‐Corrector (PC) approach in which a statistical data‐driven algorithm is applied to estimate future water demands, while near real‐time field measurements are used to correct (i.e., calibrate) these predicted values on‐line. The calibration problem is solved using a modified Least Squares (LS) fit method. The objective function is the minimization of the least‐squares of the differences between predicted and measured hydraulic parameters (i.e., pressure and flow rates at several system locations), with the decision variables being the consumers' water demands. The a‐priori estimation (i.e., prediction) of the values of the decision variables, which improves through experience, facilitates a better convergence of the calibration model and provides adequate information on the system's hydraulic state for real time optimization. The proposed methodology is demonstrated on a prototypical municipal water distribution system