Abstract
Protection is the last obstacle to realizing the idea of microgrid. Some of the main challenges in microgrid protection include topology changes of microgrid, week-infeed
fault, bidirectional power flow effects, blinding of the protection, sympathetic tripping, high impedance fault, and low voltage ride through (LVRT). Besides these challenges, it is desired to eliminate the relays for distribution lines and locate faults based on distributed generations (DGs) voltage or current. On the other hands increasing in the number of DGs and lines would result in high computation burden and degradation the efficiency and accuracy of the methods that utilize all these information. This paper deals with this issue by analyzing only DGs’ voltage. In the first step, a fault is detected by the voltage of each DG, then the DG with the highest voltage collapse injects 333 Hz harmonic to find another DG that the fault occurs within them. Two criteria are defined in such a way to prevent injection of voltage harmonic by the other DGs. Finally, the fault is located in the reduced space of search by wavelet transform and optimized multiclass support vector machine (M-SVM). In the simulation results, the contribution of this method is shown and results also validate the efficiency of the proposed method.
fault, bidirectional power flow effects, blinding of the protection, sympathetic tripping, high impedance fault, and low voltage ride through (LVRT). Besides these challenges, it is desired to eliminate the relays for distribution lines and locate faults based on distributed generations (DGs) voltage or current. On the other hands increasing in the number of DGs and lines would result in high computation burden and degradation the efficiency and accuracy of the methods that utilize all these information. This paper deals with this issue by analyzing only DGs’ voltage. In the first step, a fault is detected by the voltage of each DG, then the DG with the highest voltage collapse injects 333 Hz harmonic to find another DG that the fault occurs within them. Two criteria are defined in such a way to prevent injection of voltage harmonic by the other DGs. Finally, the fault is located in the reduced space of search by wavelet transform and optimized multiclass support vector machine (M-SVM). In the simulation results, the contribution of this method is shown and results also validate the efficiency of the proposed method.
Original language | English |
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Title of host publication | Proceedings of 8th Annual IEEE Energy Conversion Congress & Exposition (ECCE), 2016 |
Number of pages | 6 |
Publisher | IEEE Press |
Publication date | Sept 2016 |
ISBN (Electronic) | 978-1-5090-0737-0 |
DOIs | |
Publication status | Published - Sept 2016 |
Event | 8th Annual IEEE Energy Conversion Congress & Exposition: ECCE 2016 - Milwaukee, WI, United States Duration: 18 Sept 2016 → 22 Sept 2016 http://www.ieee-ecce.org/ |
Conference
Conference | 8th Annual IEEE Energy Conversion Congress & Exposition |
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Country/Territory | United States |
City | Milwaukee, WI |
Period | 18/09/2016 → 22/09/2016 |
Sponsor | IEEE, IEEE Industry Applications Society (IAS), IEEE Power Electronics and Industry Applications Societies (PELS) |
Internet address |
Keywords
- Fault detection
- Wavelet transform
- Support vector machine (SVM)
- Harmonic injection
- Fault location