Design and implementation of an intelligent digital pitch controller for digital hydraulic pitch system hardware-in-the-loop simulator of wind turbine

Narayanan, Valayapathy Lakshmi; Ramakrishnan, R.

doi:10.1080/15435075.2020.1814300

Cited by 12 publications

(10 citation statements)

References 32 publications

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“…A more detailed proceeding to obtain this model is presented in [41,42]. In this circuit, 𝜔 is the electrical circular frequency of the PMSG and is calculated according to Equation (12). 𝑅 is the stator phase resistance, 𝐶 is the DC side capacitor, In this circuit, ω e is the electrical circular frequency of the PMSG and is calculated according to Equation (12).…”

Section: Wind System Description and Modelingmentioning

confidence: 99%

“…If the system has not reached its maximum allowable power (partial load region), the control performs the task of maximum power point tracking (MPPT). On the other hand, if the system reaches its maximum power (full-load region), the control increases the rotational resistance of the turbine, limiting its angular velocity and extracted power [12,13]. Due to the importance of the MPPT algorithm in increasing the usage of renewable energy resources and system efficiency, recent research is being conducted in this field.…”

Section: Introductionmentioning

confidence: 99%

“…The model was developed in MATLAB/Simulink (Availabe on: https://la.mathworks.com/products/matlab.html, Accessed 17 November 2023) and implemented on an HIL OP4510 platform (OPAL-RT TECHNOLOGIES, Montreal, Canada). In [12], an HIL simulator was implemented to evaluate wind turbines' pitch angle control system. The simulator is divided into two parts: an emulator reproducing the wind energy conversion system (wind speed, aerodynamics, drive train, and generator) and a digital hydraulic pitch system (hydraulic motor, flow sensor, valves, etc.).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

Martínez-Nolasco,

Sámano-Ortega,

Botello-Álvarez

et al. 2023

Energies

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The use of renewable energies contributes to the goal of mitigating climate change by 2030. One of the fastest-growing renewable energy sources in recent years is wind power. Large wind generation systems have drawbacks that can be minimized using small wind systems and DC microgrids (DC-µGs). A wind system requires a control system to function correctly in different regions of its operating range. However, real-time analysis of a physical wind system may not be feasible. An alternative to counteract this disadvantage is using real-time hardware in the loop (HIL) simulation. This article describes the implementation of an HIL platform in an NI myRIO 1900 to evaluate the performance of control algorithms in a small wind system (SWS) that serves as a distributed generator for a DC-µG. In the case of an SWS, its implementation implies nonlinear behaviors and, therefore, nonlinear equations, and this paper shows a way to do it by distributing the computational work, using a high-level description language, and achieving good accuracy and latency with a student-oriented development kit. The platform reproduces, with an integration time of 10 µs, the response of the SWS composed of a 3.5 kW turbine with a fixed blade pitch angle and no gear transmission, a permanent magnet synchronous generator (PMSG), and a three-phase full-bridge AC/DC electronic power converter. The platform accuracy was validated by comparing its results against a software simulation. The compared variables were the PMSG currents in dq directions, the turbine’s angular speed, and the DC bus’s voltage. These comparisons showed mean absolute errors of 0.04 A, 1.9 A, 0.7 rad/s, and 9.5 V, respectively. The platform proved useful for validating the control algorithm, exhibiting the expected results in comparison with a lab-scale prototype using the same well-known control strategy. Using a well-known control strategy provides a solid reference to validate the platform.

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Section: Wind System Description and Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

Martínez-Nolasco,

Sámano-Ortega,

Botello-Álvarez

et al. 2023

Energies

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show abstract

“…The parameters (hydraulic pump and hydraulic motor) in DHPS are obtained from [34]. The design process involved in sizing the hydraulic orifice in DFCU is shown in Fig.…”

Section: Digital Flow Control Unitmentioning

confidence: 99%

Pitch Control of a Digital Hydraulics Pitch System for Wind Turbine Based on Neuro-Fuzzy Digital Pitch Controller

Narayanan

Ramakrishnan

2021

IJRER

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Digital Hydraulics has been implemented in the hydraulic pitch system of Wind Turbine (WT) which aids in uniform power generation at above-rated wind speeds. A novel Digital Hydraulic Pitch System (DHPS) model which uses a hydraulic motor as the end actuator was established and a wind generator system model was developed. Further, a Neuro-Fuzzy Digital Pitch Controller (NFDPC) with two distinct neuro-fuzzy controllers was employed in the developed models. Two comparative studies are conducted and in these studies, the proposed NFDPC was compared with Proportional-Integral-Derivative Cascade Controller (PIDCC) where PID is implemented in the inner and outer loop. In the first comparative study (considering custom wind speed), results revealed that the proposed controller maintains rated generator speed than PIDCC. The Root Mean Square Error (RMSE) (between rated speed and generated speed) of the generator was 1.23 and 3.73 for the proposed and PIDCC, respectively. Thus, the proposed controller generates uniform power. Consequently, in the second case study (real-time effective wind speed), the proposed controller maintains optimal generator speed with a minimal RMSE of 0.66 when compared to PIDCC with an RMSE of 3.55. Thus, uniform power was developed by the proposed controller. Therefore from these results, the proposed controller generates uniform power at above-rated wind speed with large wind fluctuations.

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“…Although some of the components used in the Simscape model, such as the hydraulic reference, the pressure sensor or the torque source are provided by the foundation Simscape library, most components are Ikerlan's proprietary implementations [90] which draw on the ample literature on the topic [81,[91][92][93][94][95][96][97][98][99][100][101][102][103]. In particular, the accumulator models are, like Liniger et al's [80], based on the Benedict-Webb-Rubin equation of state for molecular nitrogen [104] with Otis and Pourmovahed's heat transfer model [105] (the difference is, of course, that we only use this model to generate validation data, not as part of an observer).…”

Section: Synthetic Datamentioning

confidence: 99%

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

et al. 2021

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Modern wind turbines depend on their blade pitch systems for start-ups, shutdowns, and power control. Pitch system failures have, therefore, a considerable impact on their operation and integrity. Hydraulic pitch systems are very common, due to their flexibility, maintainability, and cost; hence, the relevance of diagnostic algorithms specifically targeted at them. We propose one such algorithm based on sensor data available to the vast majority of turbine controllers, which we process to fit a model of the hydraulic pitch system to obtain significant indicators of the presence of the critical failure modes. This algorithm differs from state-of-the-art, model-based algorithms in that it does not numerically time-integrate the model equations in parallel with the physical turbine, which is demanding in terms of in situ computation (or, alternatively, data transmission) and is highly susceptible to drift. Our algorithm requires only a modest amount of local sensor data processing, which can be asynchronous and intermittent, to produce negligible quantities of data to be transmitted for remote storage and analysis. In order to validate our algorithm, we use synthetic data generated with state-of-the-art aeroelastic and hydraulic simulation software. The results suggest that a diagnosis of the critical wind turbine hydraulic pitch system failure modes based on our algorithm is viable.

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Design and implementation of an intelligent digital pitch controller for digital hydraulic pitch system hardware-in-the-loop simulator of wind turbine

Cited by 12 publications

References 32 publications

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

Pitch Control of a Digital Hydraulics Pitch System for Wind Turbine Based on Neuro-Fuzzy Digital Pitch Controller

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

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