ORCID Profile
0000-0001-6188-0265
Current Organisations
Technical University of Denmark
,
SDU
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Publisher: MDPI AG
Date: 20-04-2021
DOI: 10.3390/EN14082317
Abstract: This paper proposes an algorithm for detection and identification of the location of short circuit faults in islanded AC microgrids (MGs) with meshed topology. Considering the low level of fault current and dependency of the current angle on the control strategies, the legacy overcurrent protection schemes are not effective in in islanded MGs. To overcome this issue, the proposed algorithm detects faults based on the rms voltages of the distributed energy resources (DERs) by means of support vector machine classifiers. Upon detection of a fault, the DER which is electrically closest to the fault injects three interharmonic currents. The faulty zone is identified by comparing the magnitude of the interharmonic currents flowing through each zone. Then, the second DER connected to the faulty zone injects distinctive interharmonic currents and the resulting interharmonic voltages are measured at the terminal of each of these DERs. Using the interharmonic voltages as its features, a multi-class support vector machine identifies the fault location within the faulty zone. Simulations are conducted on a test MG to obtain a dataset comprising scenarios with different fault locations, varying fault impedances, and changing loads. The test results show that the proposed algorithm reliably detects the faults and the precision of fault location identification is above 90%.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2017
Publisher: Institution of Engineering and Technology (IET)
Date: 29-11-2022
DOI: 10.1049/STG2.12097
Abstract: In this study, distributed event‐and self‐triggered (ST) control methods are proposed for accurate load sharing and voltage control in islanded AC microgrids with resistive line impedances. The proposed control framework is comprised of a two‐level control structure. At the primary level, the V‐I droop control method is adopted. In this method, the distributed energy resources (DERs) are synchronised to a common synchronous reference frame and load sharing is accomplished through voltage‐current droop characteristics in this frame. The secondary level, which has a distributed structure, mitigates the voltage deviations induced by the primary level and eliminates the current sharing error caused by the line impedances. The data exchange among the DERs is controlled using event‐ and ST algorithms. In order to reduce the communication burden, the feedback control laws are realised using estimated variables, which are updated at certain event times. The event times are extracted based on Lyapunov stability analysis and by consideration of the V‐I droop characteristics. Comparison of event and ST algorithms shows that while the event‐triggered strategy offers superior dynamic response, the ST approach requires lower network traffic. The efficacy of the proposed scheme is verified through real time simulation results.
Publisher: MDPI AG
Date: 07-01-2016
DOI: 10.3390/EN9010034
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2017
Publisher: IEEE
Date: 05-2016
Publisher: MDPI AG
Date: 23-09-2021
DOI: 10.3390/APP11198863
Abstract: Single phase induction motors (SPIM) are widely used in residential and commercial applications. Enhancement of efficiency of SPIMs can lead to huge energy savings. This paper presents a novel mechanical sensorless control method for SPIM drives. In this method, a machine learning algorithm is used to estimate the slip based on the ratio of main and auxiliary winding currents. To enhance the efficiency, the terminal voltage is reduced under light load conditions. The optimal operating voltage is implicitly obtained by equating the ratio of main and auxiliary winding currents to its optimum value. This optimal operating point is first calculated based on the frequency from a lookup table and then updated by using gradient descent algorithm. This way, the optimal operating point is realized despite motor parameter variations. The proposed scheme is suitable for low-power applications where working at different speeds and load torques is demanded, such as ventilation systems and various household appliances. Simulation results are presented to verify the efficacy of the proposed method.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2021
Publisher: Institution of Engineering and Technology (IET)
Date: 25-10-2023
DOI: 10.1049/STG2.12127
Location: Iran (Islamic Republic of)
Location: Iran (Islamic Republic of)
No related grants have been discovered for Mehdi Savaghebi.