Dynamic state estimation of a permanent magnet synchronous generator‐based wind turbine

Shahriari, Sayyed Ali Akbar; Raoofat, Mahdi; Dehghani, Maryam; Mohammadi, Mohammad; Saad, Maarouf

doi:10.1049/iet-rpg.2015.0502

Cited by 31 publications

(24 citation statements)

References 24 publications

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“…Note that the four reference values come from the speed controller (38), the DC-link voltage controller (40), the reactive power (feedforward) controller (41) and the pitch controller (39), respectively, as introduced in Section 4.1.…”

Section: Reduced-order Model (Rom)mentioning

confidence: 99%

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Hackl¹,

Jané-Soneira²,

Pfeifer³

et al. 2018

Preprint

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Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

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Section: Reduced-order Model (Rom)mentioning

confidence: 99%

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Hackl¹,

Jané-Soneira²,

Pfeifer³

et al. 2018

Preprint

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show abstract

“…Evaluating the accuracy of the simplified state estimator based on these results gives an indication that h(x) offers similar accuracy in situations with normal measurement noise as the raw measurements. The state estimator could be improved by utilizing a more detailed set of state equations as in [11] or [12], however this would simultaneously change the execution time as the detailed model requires an increased number of calculations in finding the solution to the WLS problem.…”

Section: B Test 2: Estimation Accuracymentioning

confidence: 99%

“…In previous work of applying state estimation techniques to wind power plant monitoring [11], [12], the aim has been to investigate the dynamics of the WTGs, for testing and developing control designs, and improving the transient performance of WTGs. For these purposes, comprehensive dynamic models of WTGs are necessary to give the required level of detail.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Simplified State Estimator for Wind Turbine Monitoring on an Embedded System

Rasmussen¹,

Yang²,

Nielsen³

et al. 2017

Annals of Computer Science and Information Systems

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Abstract-The transition towards a cyber-physical energy system (CPES) entails an increased dependency on valid data. Simultaneously, an increasing implementation of renewable generation leads to possible control actions at individual distributed energy resources (DERs). A state estimation covering the whole system, including individual DER, is time consuming and numerically challenging. This paper presents the approach and results of implementing a simplified state estimator onto an embedded system for improving DER monitoring. The implemented state estimator is based on numerically robust orthogonal factorization and used on a set of state equations of a generic wind turbine generator (WTG). The simplified state estimator is tested by simulating a generic WTG model and evaluated based on its execution time and estimation accuracy. Results show its fast execution time, its accuracy in handling normal measurement error and its ability to provide reliable data in the case of gross errors in the set of measurements.

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“…In previous works, various algorithms and models have been developed to estimate the state of the wind turbine and examples of such works are [6,7,8,9,10,11,12,13,14,15,16] (see Table 1). A sensor selection procedure for estimation of wind turbine rotor state and wind-induced load state was presented in [6].…”

Section: Introductionmentioning

confidence: 99%

“…A type of non-linear state estimator called particle filter was utilized in [12] to estimate the wind turbine parameters: tower top displacement, tower stop velocity and the rotor speed. More recently, authors in [13,14,15,16] studied dynamic state estimation of doubly fed induction generator (DFIG) based wind turbine and permanent magnet synchronous generator (PMSG) based wind turbine. However, most of the previous work did not take into account the impact of an unreliable wireless channel (between the wind turbines and the remote controller) on the state estimation of the wind turbine.…”

Section: Introductionmentioning

confidence: 99%

Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System

Noor-A-Rahim

Khyam

et al. 2019

Sensors

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The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors to measure the state of the turbine. Sensor measurements are transmitted to a control center, which is located away from the wind farm, for monitoring and maintenance purposes. It is therefore desirable to ensure reliable wireless communication between the wind turbines and the control center while integrating the observations from different sensors. In this paper, we propose an IoT based communication framework for the purpose of reliable communication between wind turbines and control center. The communication framework is based on repeat-accumulate coded communication to enhance reliability. A fusion algorithm is proposed to exploit the observations from multiple sensors while taking into consideration the unpredictable nature of the wireless channel. The numerical results show that the proposed scheme can closely predict the state of a wind turbine. We also show that the proposed scheme significantly outperforms traditional estimation schemes.

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Dynamic state estimation of a permanent magnet synchronous generator‐based wind turbine

Cited by 31 publications

References 24 publications

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Implementation of a Simplified State Estimator for Wind Turbine Monitoring on an Embedded System

Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System

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Dynamic state estimation of a permanent magnet synchronous generator‐based wind turbine

Cited by 31 publications

References 24 publications

Full- &amp; Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Full- &amp; Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Implementation of a Simplified State Estimator for Wind Turbine Monitoring on an Embedded System

Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System

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Product

Resources

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Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent Magnet Synchronous Generator