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A novel controllable crowbar based on fault type protection technique for DFIG wind energy conversion system using adaptive neuro-fuzzy inference system

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Protection and Control of Modern Power Systems 2018年第1期3卷 337-348页

作者： omar noureldeen I.Hamdan Department of Electrical Engineering Faculty of EngineeringSouth Valley UniversityQena 83523Egypt

This paper proposes a novel controllable crowbar based on fault type(CBFT)protection technique for doubly fed induction generator(DFIG)wind energy conversion system connected to *** studied system consists of six DFIG wind turbines with a capacity of 1.5 MW for each of *** operation mechanism of proposed technique is used to connect a set of crowbar resistors in different connection ways via activation of controllable circuit breakers(CBs)depending on the detected fault *** each phase of DFIG,a crowbar resistor is connected in parallel with a controllable CB and all of them are connected in series to grid *** adaptive neuro-fuzzy inference system(ANFIS)networks are designed to detect the fault occurrence,classify the fault type,activate the CBs for crowbar resistors associated with faulted phases during fault period,and deactivate them after fault *** effectiveness of proposed CBFT protection technique is investigated for different fault types such as symmetrical and unsymmetrical faults taking into account the single-phase to ground fault is the most frequently fault type that occurs in power ***,a comparison between the behaviours of studied system in cases of using traditional parallel rotor crowbar,classical outer crowbar,and proposed CBFT protection techniques is *** fluctuations of DC-link voltage,active power,and reactive power for studied system equipped with different protection techniques are ***,the impacts of different crowbar resistance values on the accuracy of proposed technique are *** simulation results show that,the proposed technique enhances the stability of studied wind turbine generators and contributes in protection of their components during faults.

关键词： ANFIS networks Crowbar Power electronic converters DFIG wind turbines Fault types

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Design of robust intelligent protection technique for large-scale grid-connected wind farm

引用

Protection and Control of Modern Power Systems 2018年第1期3卷 179-191页

作者： omar noureldeen I.Hamdan Electrical Engineering Department Faculty of EngineeringSouth Valley UniversityQena 83523Egypt

This paper presents a design of robust intelligent protection technique using adaptive neuro-fuzzy inference system(ANFIS)approach to detect and classify the fault types during various faults occurrence in large-scale grid-connected wind ***,it is designed to determine the fault location and isolate the wind turbine generators located in the faulted zone during fault occurrence and reconnect them after fault *** studied wind farm has a total rating capacity of 120 MW,where it consists of 60 doubly fed induction generator(DFIG)wind turbines each has a capacity of 2 ***,the wind farm generators are positioned in 6 rows,where each row consists of 10 *** impacts of fault type,fault location,fault duration,cascaded faults,permanent fault and external grid fault on the behaviours of the generated active and reactive power are ***,the impacts of internal and external faults in cases of different transition resistances are *** simulation results indicate that,the proposed ANFIS protection technique has the ability to detect,classify and determine the fault location,then isolate the faulted zones during fault occurrence and reconnect them after fault ***,the wind turbines generators which are located in un-faulted zones can stay to deliver their generated active power to the grid during fault period.

关键词： ANFIS Fault location DFIG Wind farm Active power Reactive power

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