Maximum Efficiency Point Tracking (MEPT) for Variable Speed Small Hydropower Plant With Neural Network Based Estimation of Turbine Discharge

Borkowski, Dariusz

doi:10.1109/tec.2017.2690447

Cited by 29 publications

(25 citation statements)

References 22 publications

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“…While the Francis runner is known to allow a wide variation in its operating flow, changes in the head result in an extreme reduction of efficiency. Figures 6 and 7 present the normalized efficiency curves of Francis runners for four different specific speeds as a function of the normalized flow and for the normalized head at constant rotational speed and head [59][60][61]. Thus, once designed for a specific rated condition, the Francis runner must work within very narrow application limits.…”

Section: Francis Turbine Operating At Variable Head and Speedmentioning

confidence: 99%

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The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines

et al. 2019

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Climate change and environmental degradation has resulted in a reduction in water inflow at hydropower plants, as well as a decrease in reservoir levels. Existing hydropower plants suffer from water head reduction, mainly with decrease in efficiency of energy conversion in hydro turbines. This paper showcases the benefits of operations with variable speed in existing hydropower plants, when working at a lower water head than the rated one. Theoretical analyses and tests were performed in a special constructed laboratorial setup aiming at evaluating the amount of efficiency recovery with variable speed operation. Connection alternatives for a constant frequency grid and applications of the learned concepts in an existent hydropower plant are presented. The investigations were applied to the Furnas hydropower plant. The results point out that economic feasibility of the application can be achieved.

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Section: Francis Turbine Operating At Variable Head and Speedmentioning

confidence: 99%

“…Figure 6and 7 present the normalized efficiency curves of Francis runners for four different specific speeds as a function of the normalized flow and for the normalized head at constant rotational speed and head[59][60][61].…”

mentioning

confidence: 99%

The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines

et al. 2019

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“…1. The SHP contains an axial-flow propeller turbine integrated with the permanent magnet synchronous generator (PMSG) [13]. The turbine is located in the generator rotor.…”

Section: Numerical Modelling 21 Geometry Descriptionmentioning

confidence: 99%

Simulation of water turbine integrated with electrical generator

et al. 2018

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The paper presents the analysis of the small hydropower plant working at variable speed. The hydro-set that consists of the guide vanes and propeller turbine integrated with the permanent magnet synchronous generator is simulated by using Computational Fluid Dynamics (CFD) in Ansys Fluent v18.0. The k-ε and k-ω SST models, as well as the one-equation Spalart-Allmaras (SA) model, were tested. The comparison showed the significant divergence of the calculation results. The turbulence model selection influences the average value of the power and also the speed for which the power is maximal.

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“…A typical example of artificial intelligence control is neural networks (NN) wherein neural network algorithms can improve control performance without direct modeling. In (Liu et al, 2015;Heravi & Eslamdoost, 2015;Borkowski, 2017), these types of algorithm were applied to various power plants. Recently, a hybrid control method exploiting the advantages of NN has been studied (Attaran, Yusof & Selamat, 2016;Azali & Sheikhan, 2016;Sharma et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Development of PINN Controller for Fuel Handling System of Pressurized Heavy Water Reactors

Lim¹,

Park²,

Chong³

2020

STUD INFORM CONTROL

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The required operating pressure of the Wolsong nuclear power plant is currently controlled by a proportional integral (PI) controller. The PI controller has a simple structure and was designed to meet requirements through gain setting. However, these control requirements can be difficult to meet without properly adjusting the gain when certain parameters change, such as the wear and tear in the valves or pipes. To solve these problems, it is important to dynamically change the PI controller gain or compensate for the PI controller output. The purpose of this study is to help design a controller that is capable of providing stable control in order to reduce errors regardless of parameter changes. The proposed PI neural network (PINN) control technique involves a PI controller and a neural network controller combined in parallel. The neural network component which is designed to be robust compensates the output of the controller for changes in the above-mentioned parameters. Because assessing the controller performance straightforwardly in real-time processes can be difficult, a simulator model was developed based on real-time processes, and it showed changes in the parameters involved. The results confirmed that the proposed PINN controller reduced the instability of the fuel supply machine and, hence the aforementioned problem could be properly controlled.

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Maximum Efficiency Point Tracking (MEPT) for Variable Speed Small Hydropower Plant With Neural Network Based Estimation of Turbine Discharge

Cited by 29 publications

References 22 publications

The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines

The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines

Simulation of water turbine integrated with electrical generator

Development of PINN Controller for Fuel Handling System of Pressurized Heavy Water Reactors

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