Design of advanced artificial intelligence protection technique based on low voltage ride-through grid code for large-scale wind farm generators: a case study in Egypt

Noureldeen, Omar; Hamdan, I.; Hassanin, B.

doi:10.1007/s42452-019-0538-9

Cited by 17 publications

(10 citation statements)

References 46 publications

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“…The WES consists of various main parts such as WT rotor, gearbox, generator, power converters, and transformer for grid connection. The DFIG is most popular wind generator in the market among variable-speed WTs, because of their high energy efficiency [17][18][19][20][21]. The main representation of grid integration with DFIG-WT is shown as Fig.…”

Section: Wind Energy Description and Configurationmentioning

confidence: 99%

“…However, the different protection techniques are turned on/off via control strategy called ANFIS. The ANFIS networks depend on the number of fuzzy membership functions and the number of neurons that used for rule base to consist of the main construction of these networks [17][18][19][20][21][22][23]. The ANFIS structures have well known advantages of control and modelling for a highly non-linear system, as it combines the capability of FLC and ANN [24][25][26][27].…”

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confidence: 99%

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An Overview of Control Method with Various Crowbar Techniques of Wind Turbines during Power System Faults

Hamdan

Noureldeen

2021

SVU-International Journal of Engineering Sciences and Applicati

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This paper reviews the various control crowbar methods associated with doubly-fed induction generator (DFIG) wind energy system (WES) during power system faults. The crowbar control methods are designed to improve the fault ride-through (FRT) capability of DFIGs based on WESs. The adaptive neural-fuzzy inference system (ANFIS) is developed to detect the fault conditions and control the crowbar protection techniques. The proposed ANFIS crowbar protection technique detects the fault based on the measurement of the three phase voltages and currents at the terminals of the DFIG wind turbine (WT) to activate the crowbar protection system during fault period and deactivate it after fault clearance. Furthermore, the proposed ANFIS crowbar techniques are investigated to enhance the stability of studied WT generators and also, it designed to protect system components. All these simulations are carried for the model consists of 9 MW DFIG WTs connected to the grid model in Simulink/Matlab. Simulation results also revealed that outer terminal crowbar is more effective as compare with other crowbar techniques via ANFIS control strategy.

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Section: Wind Energy Description and Configurationmentioning

confidence: 99%

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confidence: 99%

An Overview of Control Method with Various Crowbar Techniques of Wind Turbines during Power System Faults

Hamdan

Noureldeen

2021

SVU-International Journal of Engineering Sciences and Applicati

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“…1. Recently, the strategy of the NREA in Egypt aims to supply 12% of the total electricity generation from the wind energy by the end of 2020, which means increasing the installed wind power capacity to 7200 MW [3], [6]. Over recent years, many studies in the field of using the RES in Egypt have been reported.…”

Section: Introductionmentioning

confidence: 99%

“…The study analyzed the availability of vacant areas for installation, environmental conditions, economics profits, and the future developments related to the implementation of the PV stations in the selected sites. Moreover, in terms of using wind energy in Egypt, Noureldeen et al [6], proposed an advanced artificial intelligence protection technique based on Low Voltage Ride-Through (LVRT) for a large-scale grid-connected wind farm.…”

Section: Introductionmentioning

confidence: 99%

Modeling, Control, and Performance Evaluation of Grid-Tied Hybrid PV/Wind Power Generation System: Case Study of Gabel El-Zeit Region, Egypt

et al. 2020

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The potential for utilizing clean energy technologies in Egypt is excellent given the abundant solar irradiation and wind resources. This paper provides detailed design, control strategy, and performance evaluation of a grid-connected large-scale PV/wind hybrid power system in Gabel El-Zeit region located along the coast of the Red Sea, Egypt. The proposed hybrid power system consists of 50 MW PV station and 200 MW wind farm and interconnected with the electrical grid through the main Point of Common Coupling (PCC) busbar to enhance the system performance. The hybrid power system is controlled to operate at the unity power factor and also the Maximum Power Point Tracking (MPPT) technique is applied to extract the maximum power during the climatic conditions changes. Modeling and simulation of the hybrid power system have been performed using MATLAB/SIMULINK environment. Moreover, the paper presented a comprehensive case study about the realistic monthly variations of solar irradiance and wind speed in the study region to validate the effectiveness of the proposed MPPT techniques and the used control strategy. The simulation results illustrate that the total annual electricity generation from the hybrid power system is 1509.85 GWh/year, where 118.15 GWh/year (7.83 %) generates from the PV station and 1391.7 GWh/year (92.17%) comes from the wind farm. Furthermore, the hybrid power system successfully operates at the unity power factor since the injected reactive power is kept at zero.

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“…Artificial intelligence (AI) has become an integral part in many fields like waste generation [6,7], automobiles, international business, educational institution [8], civil engineering applications [9,10], medical [11], image processing [12] and also, electrical power system applications [13]. AI analyze the system and make prediction based on previous available data.…”

Section: Introductionmentioning

confidence: 99%

Electric power load forecasting on a 33/11 kV substation using artificial neural networks

Veeramsetty

Deshmukh

2020

SN Appl. Sci.

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Estimation of electric power load on electric power substation is an essential task for system operator in order to operate the system in a reliable and optimal manner. In this paper, machine learning with artificial neural network is used for forecasting the load at a particular hour of the day on an electric power substation. Historical load data at each hour of the day for the period from September-2018 to November-2018 is taken from 33/11 kV substation near Kakatiya University in Warangal. A new artificial neural network architecture is developed based on the approach used to forecast the load. The developed model is simulated in MATLAB with available historical data to forecast the load on 33/11 kV electric power substation. Based on the analysis it is observed that the proposed architecture forecasts the load with better accuracy.Keywords Artificial neural networks · Electric power load forecasting · Machine learning · Mean square error · Mean absolute percentage error List of symbols L(D, t) Load at Dth day and tth hour L(D, t − 1) Load at Dth day and (t − 1)th hour L(D, t − 2) Load at Dth day and (t − 2)th hour L(D, t − 3) Load at Dth day and (t − 3)th hour L(t, D − 1) Load at (D − 1)th day and tth hour L(t, D − 2) Load at (D − 2)th day and tth hour L(t, D − 3) Load at (D − 3)th day and tth hour L(t, D − 4) Load at (D − 4)th day and tth hour MAPE Mean absolute percentage error MSE Mean square error y Target i Actual output y Predicted i Predicted output m Number of samples R Regression coefficient * Venkataramana Veeramsetty,

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Design of advanced artificial intelligence protection technique based on low voltage ride-through grid code for large-scale wind farm generators: a case study in Egypt

Cited by 17 publications

References 46 publications

An Overview of Control Method with Various Crowbar Techniques of Wind Turbines during Power System Faults

An Overview of Control Method with Various Crowbar Techniques of Wind Turbines during Power System Faults

Modeling, Control, and Performance Evaluation of Grid-Tied Hybrid PV/Wind Power Generation System: Case Study of Gabel El-Zeit Region, Egypt

Electric power load forecasting on a 33/11 kV substation using artificial neural networks

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