9 citations to 10.1109/IYCE.2015.7180828 (Crossref Cited-By Service)

1. Michael Negnevitsky, Nikita Tomin, Victor Kurbatsky, Daniil Panasetsky, Alexey Zhukov, Christian Rehtanz, 2015 IEEE Eindhoven PowerTech, 2015, 1  
2. Peyman Razmi, Mahdi Ghaemi Asl, Application of Machine Learning and Deep Learning Methods to Power System Problems, 2021, 357  
3. Rishav Baishya, Rajib Sarkar, “A neural network-based approach for prediction of PGA and significant duration parameters in the Uttarakhand region of India”, Environ Earth Sci, 81, № 13, 2022, 342  
4. Walter M. Villa-Acevedo, Jesús M. López-Lezama, Delia G. Colomé, Jaime Cepeda, “Long-term voltage stability monitoring of power system areas using a kernel extreme learning machine approach”, Alexandria Engineering Journal, 61, № 2, 2022, 1353  
5. Milad Dalali, Hossein Kazemi Karegar, “Voltage instability prediction based on reactive power reserve of generating units and zone selection”, IET Generation, Transmission & Distribution, 13, № 8, 2019, 1432  
6. Yu Zhang, Xiaohui Song, Yong Li, Zilong Zeng, Chenchen Yong, Denis Sidorov, Xia Lv, “Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility”, Energies, 13, № 22, 2020, 5922  
7. N. Tomin, A. Zhukov, V. Kurbatsky, D. Sidorov, M. Negnevitsky, 2017 IEEE Manchester PowerTech, 2017, 1  
8. Walter M. Villa-Acevedo, Jesús M. López-Lezama, Delia G. Colomé, “Voltage Stability Margin Index Estimation Using a Hybrid Kernel Extreme Learning Machine Approach”, Energies, 13, № 4, 2020, 857  
9. Sen Wang, Yonghui Sun, Yan Zhou, Rabea Jamil Mahfoud, Dongchen Hou, “A New Hybrid Short-Term Interval Forecasting of PV Output Power Based on EEMD-SE-RVM”, Energies, 13, № 1, 2019, 87