Real-time Neural Inverse Optimal Control for Low-Voltage Rid-Through enhancement of Double Fed Induction Generator based Wind Turbines

Djilali, Larbi; Sánchez, Edgar N.; Ornelas‐Tellez, Fernando; Ruz-Hernández, José A.; Ricalde, Luis J.

doi:10.1016/j.isatra.2020.05.021

Cited by 7 publications

(5 citation statements)

References 36 publications

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“…Suppose that i y i s u s e d t o re p re s e nt t he i t h ro w o f eigenvectors in the feature matrix, which will be unitized sequentially so that the absolute value of i y is 1. Finally, new sample nodes are generated using the K-means clustering algorithm, and the model analysis matrix [9] is formed based on the newly generated nodes.…”

Section: Model Construction For Analysis Of Line Variation Relationsh...mentioning

confidence: 99%

Intelligent identification of segmental line losses in low-voltage networks under graphical consistency line variation relationship analysis

Li,

Zhao,

Wei

et al. 2023

Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023)

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The current conventional line loss identification method mainly constructs the similarity matrix by calculating the similarity of line loss data, which leads to poor identification effect due to the lack of effective extraction of line loss data features. In this regard, the intelligent identification method of low-voltage grid segmentation under the analysis of line variation relationship of mapping consistency is proposed. The similarity of voltage time series mapping of low-voltage power grid is calculated to extract line loss feature data, and the EM algorithm is used to cluster and analyze the power operation data of line loss abnormal stations, and the vector features of line loss data under different Gaussian distribution states are calculated by constructing GMM model to realize line loss identification. In the experiments, the proposed method is verified for recognition accuracy. The experimental results show that the algorithm has a high recall rate and possesses a more desirable recognition accuracy when the proposed method is used for line loss data recognition.

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Section: Model Construction For Analysis Of Line Variation Relationsh...mentioning

confidence: 99%

Intelligent identification of segmental line losses in low-voltage networks under graphical consistency line variation relationship analysis

Li,

Zhao,

Wei

et al. 2023

Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023)

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“…It is not difficult to draw the following conclusions by analysing the changed eigenvalue described in formula (20). After taking methods to upgrade the control scheme, the negative real part of the characteristic value of the control system significantly increases, and the distance between the real part and imaginary axis increases as reflected in the root locus.…”

Section: Control Scheme Of the Rotor Side Converter (Rsc) Coordinated...mentioning

confidence: 99%

“…A coordinated sequential control (CSC) strategy and an N-IOC scheme are proposed in refs. [19,20] respectively. In ref.…”

Section: Introductionmentioning

confidence: 99%

Improving fault ride‐through capability for doubly‐fed induction generator based on improved system structure and corresponding control scheme

Xian

Zhang

et al. 2023

IET Energy Syst Integration

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Although there are many methods to improve the fault ride‐through (FRT) capability of doubly‐fed induction generator (DFIG) systems at present, each method has its shortcomings, especially the applicability under different voltage dips (VDs), so an improved system structure with a dynamic switching topology and a corresponding control scheme is proposed. Based on the mechanism analysis that the series impedance of the stator can effectively reduce the overcurrent on the rotor side, and considering the feasibility of the FRT scheme in engineering, the dynamic switching topology is designed. The selection of theoretical parameters in different cases is also analysed and designed. Simultaneously, to cooperate with the hardware measures, the control scheme of the rotor side converter (RSC) under different conditions is also improved. The RSC can use the control scheme of active flux attenuation to effectively and quickly reduce the overcurrent on the rotor side, and use reactive power support to accelerate the voltage recovery. The novelty of the FRT scheme is that the scheme can dynamically adjust the topology structure and control scheme under different voltage dips. Thus, its ride‐through performance during fault is better under different conditions. A simulation model of the improved system structure and control scheme is built on the MATLAB/Simulink platform. Through the comparison of simulation data, the validity and correctness of the proposed FRT scheme are verified.

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“…The Particle Swarm Optimization (PSO) algorithm [33] is used in the IOC procedure to find the matrix that guarantees asymptotic stability in passivity CL-system [15][16][17]21].…”

Section: Metaheuristic Algorithmmentioning

confidence: 99%

“…In [20] an application of both an adaptable fuzzy controller and IOC is proposed with great success in terms of reference tracking in the presence of external dynamics. Furthermore, in [21], a combination of sliding mode controllers and neural IOC was presented, resulting in a robust scheme even in the face of parametric variations and external perturbations, although modeling of hydropower systems is not implemented. While the previously mentioned works have shown good results in their own right, these drive away from the necessity of ensuring optimal trajectory tracking in hydraulic systems, as identifying external perturbations are required.…”

Section: Introductionmentioning

confidence: 99%

Inverse Optimal Control Using Metaheuristics of Hydropower Plant Model via Forecasting Based on the Feature Engineering

et al. 2021

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Optimal operation of hydropower plants (HP) is a crucial task for the control of several variables involved in the power generation process, including hydraulic level and power generation rate. In general, there are three main problems that an optimal operation approach must address: (i) maintaining a hydraulic head level which satisfies the energy demand at a given time, (ii) regulating operation to match with certain established conditions, even in the presence of system’s parametric variations, and (iii) managing external disturbances at the system’s input. To address these problems, in this paper we propose an approach for optimal hydraulic level tracking based on an Inverse Optimal Controller (IOC), devised with the purpose of regulating power generation rates on a specific HP infrastructure. The Closed–Loop System (CLS) has been simulated using data collected from the HP through a whole year of operation as a tracking reference. Furthermore, to combat parametric variations, an accumulative action is incorporated into the control scheme. In addition, a Recurrent Neural Network (RNN) based on Feature Engineering (FE) techniques has been implemented to aid the system in the prediction and management of external perturbations. Besides, a landslide is simulated, causing the system’s response to show a deviation in reference tracking, which is corrected through the control action. Afterward, the RNN is including of the aforementioned system, where the trajectories tracking deviation is not perceptible, at the hand of, a better response with respect to use a single scheme. The results show the robustness of the proposed control scheme despite climatic variations and landslides in the reservoir operation process. This proposed combined scheme shows good performance in presence of parametric variations and external perturbations.

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Real-time Neural Inverse Optimal Control for Low-Voltage Rid-Through enhancement of Double Fed Induction Generator based Wind Turbines

Cited by 7 publications

References 36 publications

Intelligent identification of segmental line losses in low-voltage networks under graphical consistency line variation relationship analysis

Intelligent identification of segmental line losses in low-voltage networks under graphical consistency line variation relationship analysis

Improving fault ride‐through capability for doubly‐fed induction generator based on improved system structure and corresponding control scheme

Inverse Optimal Control Using Metaheuristics of Hydropower Plant Model via Forecasting Based on the Feature Engineering

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